PATIENT-CENTERED OUTCOMES RESEARCH INSTITUTE

FINAL RESEARCH REPORT

Helping Men With Prostate Cancer Determine Their Preferences for Treatment

Ravishankar Jayadevappa, PhD1,2,3,4,5; Sumedha Chhatre, PhD6; Joseph J. Gallo, MD, MPH7,8; Marsha N.

Wittink, MD, MBE9; Knashawn H. Morales, ScD10; David I. Lee, MD2; Thomas Guzzo, MD, MPH2; Neha

Vapiwala, MD11; Yu-Ning Wong, MD, MSC12; Keith Van Arsdalen, MD3; Alan J. Wein, MD, PhD (Hons)2,5; S.

Bruce Malkowicz, MD2,3,5; J. Sanford Schwartz, MD1,4,5,13

AFFILIATIONS:

1Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia 2Urology, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia 3Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pennsylvania 4Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia 5Abramson Cancer Center, University of Pennsylvania, Philadelphia 6Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia 7General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 8Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland 9Department of Psychiatry, University of Rochester Medical Center, Rochester, New York 10Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia 11Department of Radiation Oncology, University of Pennsylvania, Philadelphia 12Fox Chase Cancer Center, Temple University, Philadelphia, Pennsylvania 13Health Care Management Department, Wharton School of Business, University of Pennsylvania, Philadelphia

Original Project Title: Treatment Difference and Patient-Centered Prostate Cancer Care PCORI Award ID: CE-12-11-4973 Institution Receiving the PCORI Award: Perelman School of Medicine, University of Pennsylvania HSRProj ID: HSRP20143289 ClinicalTrials.gov ID: NCT02032550 _______________________________ To cite this document, please use: Jayadevappa R, Chhatre S, Gallo JJ, et al. (2020). Helping Men With Prostate Cancer Determine Their Preferences for Treatment. Washington, DC: Patient-Centered Outcomes Research Institute (PCORI). https://doi.org/10.25302/04.2020.CE.12114973

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TABLE OF CONTENTS

ABSTRACT ............................................................................................................................. 4

BACKGROUND ....................................................................................................................... 6

Conceptual Framework .............................................................................................................. 9

Figure 1. Factors influencing treatment choices and outcomes of care for patient-centered prostate cancer care .......................................................................................... 10

PARTICIPATION OF PATIENTS AND OTHER STAKEHOLDERS .................................................. 13

Types and Numbers of Stakeholders ....................................................................................... 13

Deciding on and Achieving the Desired Balance of Stakeholder Perspectives ........................ 13

Methods Used to Identify and Recruit Stakeholder Partners .................................................. 13

Methods, Modes, and Intensity of Engagement: Patient and Stakeholder Involvement as Advisory Board Members .................................................................................................... 14

Perceived or Measured Impact of Engagement ...................................................................... 14

How the Engagement of Patient or Other Stakeholder Partners Changed the Research ....... 15

METHODS ........................................................................................................................... 16

Study Overview ........................................................................................................................ 16

Figure 2. Schematic representation of overall study designa ........................................... 17

Study Design ............................................................................................................................. 17

Figure 3. Five steps in the development of PreProCare in phase 1 of the study ............. 18

Study Participants .................................................................................................................... 21

Interventions and Comparators or Controls for Phase 2 ......................................................... 22

Study Outcomes for Phase 2 .................................................................................................... 23

Study Setting ............................................................................................................................ 25

Time Frame for the Study ........................................................................................................ 26

Data Collection and Sources .................................................................................................... 26

Analytical and Statistical Approaches ...................................................................................... 26

Changes to the Original Study Protocol ................................................................................... 32

RESULTS .............................................................................................................................. 33

Phase 1 ..................................................................................................................................... 33

Table 1. Synthesis of Patient-Centered Outcomes Evidence for Localized Prostate Cancer: Summary of the Literature151 .............................................................................. 34

Figure 4. Steps in the development of attributes for the PreProCare tool ...................... 36

Table 2. Final Attributes, Definitions, and Levels for the PreProCare Tool ...................... 39

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Figure 5. PreProCare adaptive conjoint analysis tool snaphot of attribute selection, choice scenarios, and result ............................................................................. 43

Table 3. Pilot Testing Reponses for the PreProCare Tool in Newly Diagnosed Prostate Cancer Patients Who Were Treatment Naive (n = 52)....................................... 44

Phase 2 ..................................................................................................................................... 46

Figure 6. CONSORT diagram showing flow of participants through phase 2 of the study (N = 743) .................................................................................................................. 47

Table 4. Comparison of Baseline Sociodemographic and Clinical Characteristics of Participants From Intervention Group vs Usual Care Group ............................................ 48

Table 5. Comparison of Baseline Control Preference, Trust, and Decision Conflict of Participants From Intervention Group vs Usual Care Group ........................................ 50

Table 6. PreProCare Treatment Attributes and Their Average Importance in Intervention Group Patients (n = 312) .............................................................................. 51

Table 7. Comparison of Satisfaction With Care Scores Across Intervention and Usual Care Groupsa ........................................................................................................... 53

Table 8. Satisfaction With Decision: Comparison of Proportions Satisfied With Decision at Follow-up Points by Intervention Statusa ...................................................... 55

Table 9. Regret With Decision: Comparison of Proportion With No Regret With Decision at Follow-up Points by Intervention Statusa ...................................................... 57

Figure 7. Overall comparison of proportions with different treatment choices across PreProCare intervention status, stratified by prostate cancer risk group (n = 674) ............................................................................................................................ 59

Table 10. Comparison of Generic HRQoL Scores Across Intervention and Usual Care Groups ...................................................................................................................... 62

Table 11. Proportion Returning to Baseline Scores at 3, 6, 12, and 24 Months for Prostate-Specific HRQoL ................................................................................................... 63

Table 12. Comparison of 3 Categories of Urologic Symptoms at Baseline and at 3, 6, 12, and 24 Months Across Intervention and Usual Care Groups Using AUA-SI ........... 65

Table 13. Comparison of 3 Categories of Depression at Baseline and at 3, 6, 12, and 24 Months Across Intervention and Usual Care Groups Using CES-D ....................... 66

Table 14. Latent Profile Analysis of Individual Utilities for the Intervention Group (n = 312) ............................................................................................................................ 68

Table 15. Association between treatments received and attributes of the PreProCare Tool for intervention group, after adjusting for sociodemographic and clinical characteristics (n = 312) ................................................................................. 70

DISCUSSION ........................................................................................................................ 71

Context for the Study Results .................................................................................................. 71

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Generalizability of the Findings ................................................................................................ 72

Implementation of the Study Results ...................................................................................... 72

Subpopulation Considerations ................................................................................................. 74

Study Limitations ...................................................................................................................... 74

Future Research ....................................................................................................................... 75

CONCLUSIONS ..................................................................................................................... 76

REFERENCES ........................................................................................................................ 77

RELATED PUBLICATIONS ...................................................................................................... 89

ACKNOWLEDGMENTS .......................................................................................................... 90

APPENDIX............................................................................................................................ 91

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ABSTRACT

Background: Treatment choice for localized prostate cancer is preference sensitive given that several medically viable and effective treatment options are available, each with specific risks and benefits. Assessing patient treatment preferences is thus critical for effective patient-centered decisions and improved outcomes.

Objectives: To develop a preference assessment intervention, compare its effectiveness with that of usual care, and identify preferred attributes of prostate cancer treatments (including active surveillance) to facilitate patient-centered care.

Methods: In this 2-phase study, we first developed PreProCare, a preference assessment tool, in phase 1. In phase 2, we conducted a multisite randomized controlled trial to study the effectiveness of the PreProCare tool. Patients with newly diagnosed localized prostate cancer who had not yet received treatment were randomly assigned either to the intervention group using the PreProCare tool or to a usual care group. PreProCare is a web-based, preference assessment tool; it has 3 parts and requires an average of 30 minutes to complete. In part I, we provide an introduction to the tool, and in part II, the participant ranks the attributes (for example, urinary function and sexual function) of various treatments. In part III, choice scenarios consisting of combinations of attributes are presented based on the participant’s ranking of the attributes, and the participant selects the combination that he most prefers. The result is a graph and a list of the 5 most preferred attributes that the participant can share with his provider. We administered the PreProCare tool soon after diagnosis and before treatment choice. Our primary outcome was satisfaction with care; secondary outcomes were satisfaction with the treatment decision, treatment choice, health-related quality of life (HRQoL; generic and prostate cancer–specific), and psychological well-being. We assessed outcomes in patients who were blinded to intervention assignment at 3, 6, 12, and 24 months, and analyzed outcomes using repeated-measures analyses. We used intent-to-treat analysis and compared the primary and secondary outcomes, including treatment choice between the intervention and usual care groups for 3 risk categories of prostate cancer.

Results: In phase 1, we developed and pilot tested the PreProCare preference assessment tool. In phase 2, we recruited 743 localized prostate cancer patients and randomly assigned them to either the PreProCare tool group (n = 372) or to the usual care group (n = 371). For the general satisfaction subscale (primary outcome), improvement at 24 months from baseline was significantly different between groups (P = .001). In the intervention group, for the general satisfaction subscale, improvement in mean (SE) score at 24 months from baseline was 0.44 (0.06), or equal to an increase in 0.5 of the SD, which is clinically and statistically significant (P < .0001). For the usual care group, this change was 0.07 (0.06), which is less than 0.1 of the SD, and clinically and statistically not significant (P = .08). The proportion of participants reporting satisfaction with their treatment decision and no regret increased over time and was higher for the intervention group than for the usual care group at 24 months (P < .05). Among low-risk patients, the proportion of the intervention group on active surveillance was higher than the proportion of the usual care group (P < .0001). At 24 months, the generic HRQoL domain of

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social functioning improved more for the intervention group than for the usual care group (P = .022). For prostate cancer-specific HRQoL, at 24 months, a higher proportion of intervention group participants had returned to baseline for urinary function and urinary incontinence domains than had usual care group participants. By 24 months, the proportion of those with severe urinary symptoms and high depression was lower in the intervention group than in the usual care group (P < .0001).

Conclusions: The PreProCare preference assessment intervention improved satisfaction with care and satisfaction with decision, reduced regrets, and aligned treatment choice with the prostate cancer risk category. Our patient-centered study shows the effectiveness of tailoring treatment decision-making to the values of patients in a real-world clinical care setting to improve outcomes. Preference assessment intervention may be a mechanism for enhancing outcomes for men with localized prostate cancer.

Study Limitations: The PreProCare tool-based values clarification exercise is limited by the attributes selected. For the intervention group, we did not measure the quality and quantity of patient-physician interactions postintervention. The physicians did not receive formal training to incorporate the results of preference assessment in treatment discussions. All of our study sites are urban academic institutions. We did not control for the additional time and attention to preferences in care between the intervention and usual care groups. Most of the participants were married, college graduates, and almost two-thirds had an annual household income of $75 000 or higher; thus, future studies should include diverse groups of patients and clinical settings to enhance the generalizability of the findings.

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BACKGROUND

Prostate cancer accounts for 33% of all newly diagnosed malignancies in men, with an

estimated 164 690 new prostate cancer cases and 29 430 prostate cancer-related deaths in

2018.1 For localized prostate cancer, treatment choices include active surveillance, watchful

waiting, or aggressive, potentially curative therapies, such as radical prostatectomy (RP),

robotic-assisted laparoscopic prostatectomy (RALP), external-beam radiation therapy (EBRT),

brachytherapy (BT), and proton therapy (PT), all with clinically significant adverse effects.

Patient-centered care, a key component of high-quality care, involves the application of

scientific knowledge to patient care, tailored to each individual’s unique characteristics,

circumstances, needs, and preferences.2-20 The Crossing the Quality Chasm report (2001) and

various guidelines (American Cancer Society, Agency for Healthcare Research and Quality, and

National Cancer Institute) recommend that health professionals discuss all treatment options

and adverse effects with the patient.10,21,22 Considerable uncertainty exists regarding the

effectiveness of various treatments for prostate cancer. Since most prostate cancer treatments

have adverse effects, choosing one requires balancing the risks and benefits.23 Men with early

stage prostate cancer face difficult treatment decisions.2,6,24-44 Assessment of the preferences

and the uncertainty associated with treatment outcomes for prostate cancer will provide better

insight into the patient decision-making process.45-55

In patient-centered prostate cancer care, concordance between patient preferences and

treatment attributes may optimize outcomes.42,44,56-62 The uncertainties confronted by

physicians and patients in the course of prostate cancer care require improved measures to

understand patient preferences.2-19 This is particularly important because we still know little

about the optimal management strategies for prostate cancer (especially because most

treatments have troublesome adverse effects) and how best to advise patients regarding

treatment choice.2-19,22,34-38,40,63-89 In uncertain and ambiguous situations, such as choosing a

prostate cancer treatment, patients often find it difficult to choose and will defer their

decisions. Although a wealth of information regarding these choices is available, it can often be

confusing for a patient to sort out and can affect the patient-centeredness of care. From a

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patient’s perspective, feeling overwhelmed by potential decisions can also lead to difficulties in

decision-making and/or treatment regrets and can be exasperating to both patient and

provider. An important goal of patient-centered prostate cancer care is to help patients reach

satisfying solutions to difficult problems of treatment decision-making. To facilitate informed

patient-centered prostate cancer decision-making, strategies are being proposed that include

innovative ways of presenting complex information to patients and for the development of

devices that will aid patients in articulating their preferences and facilitate decisions that are

concurrent with their values.10,90

Informed decision-making, which is at the core of patient-centered care, is a process

that implies that a physician’s unbiased knowledge is transferred to the patient, who then has

the knowledge and insight about their preferences necessary to make a decision. Studies have

discussed the nonsystematic process of decision-making in prostate cancer care.91-94 Prostate

cancer treatments frequently are complex and unfamiliar to many patients. A majority of

prostate cancer patients report that their physician’s recommendation was the most important

factor in their treatment choice.2-11,13-19,22,79,80 This is appropriate if the physician is an efficient

agent for the patient, that is, he or she makes the decision the patient would make if the

patient had the physician’s medical knowledge. The physician agency model95 presupposes that

the physician knows and understands the patient’s attitudes, beliefs, preferences, and values.

However, patient and physician beliefs differ in many respects, such as in prioritizing outcomes,

conceptualizing the illness, and ranking available options.2-11,13-19,22,58,67,79,80,96-98 Thus, a

physician’s opinion as a credible source may inappropriately bias a patient’s systematic

decision-making process. We cannot base preferences on misinformation or missing

information, so physicians need to ascertain whether they and their patients have sufficient

knowledge to construct informed preferences in concordance with the patient’s values.

Respecting and responding to patient preferences is the hallmark of patient-centered

care and requires accurately eliciting preferences and aiding patients in constructing them. One

way to explore treatment-related risk-benefit trade-off entails assessing patient preferences for

key outcomes associated with prostate cancer treatment. For example, conjoint analysis is a

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method with strong theoretical roots in mathematical psychology.99 It asks respondents to

make a series of holistic decisions about which bundles of attributes they prefer, from which

trade-offs among conflicting attributes (such as treatment outcomes) can be disentangled and

deduced. Conjoint analysis methods thus seek to uncover the underlying preference function

for a treatment in terms of its attributes.99-103 Conjoint analysis is a method that uncovers

respondent trade-offs among various attributes of competing products or services, such as

treatment options for prostate cancer, and allows the assessment of treatment attribute

weights as opposed to the preferences themselves.

In conjoint analysis, profiles of treatment attributes (value markers or utility levels) are

identified that are associated with particular choices. Conjoint analysis generates a preference

(utility) score that has a numeric value that refers to the part-worth assigned to a particular

attribute and its levels. Part-worth is defined as the estimate (obtained from conjoint analysis)

of the overall preference or utility associated with each level of each attribute of treatment.

Many health-related applications have used conjoint analysis.99-129 For example, conjoint

analysis was employed to study the factors important to patients in choosing a hospital,116 to

elicit patient priorities in women’s health,101,103,118 to establish consumer preferences for dental

services,106,113 and to elicit patient perspectives on medical

conditions.104,111,112,114,117,119,122,124,130 Clinical research is recognizing conjoint analysis as a

valuable means of assessing patient preferences for health care.131-133 It has been successfully

used in older adults to understand their preferences for cataract surgery options,126 hearing

aids,121 and osteoarthritis treatment options.125 Conjoint analysis has been used to assess

features of mental health treatment that low-income Latino primary care patients thought

would improve the acceptability of treatment for depression 109 and to inform the design of an

alcohol and smoking cessation program.110 Relative weights (utilities) derived from conjoint

task analysis can be used to form profiles (sets or patterns of utilities) representing value

markers that may be associated with treatment outcomes. Adaptive conjoint analysis (ACA) is a

type of conjoint analysis in which the computer-based tool customizes the experience for each

respondent in identifying utility levels for each attribute of treatment. Thus, ACA may be helpful

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in clarifying utility levels across attributes of prostate cancer treatment consistent with patient-

centered care. In our study, we classified patients based on utility levels to study the

relationships among profiles (value markers), treatment received, and outcomes, such as

health-related quality of life (HRQoL), satisfaction with care, complications, and psychological

well-being.

Conceptual Framework

Patient-centered care is “providing care that is respectful of and responsive to individual

patient preferences, needs, and values, and ensuring that patient values guide all decisions.”134-

136 Per the Institute of Medicine (now the National Academy of Medicine), patient-centered

care is defined as care in which a patient (1) understands the risk or seriousness of the disease

or condition to be prevented; (2) understands the preventive service, including the risks,

benefits, alternatives, and uncertainties; (3) has evaluated his or her values regarding the

potential benefits and harms associated with treatment; and (4) has engaged in decision-

making at the level at which he or she desires and feels comfortable.10,17,59,134,135,137-140

In Figure 1, we present our conceptual model of individual decision-making in the

context of patient-centered care, which consists of multiple domains (patient and clinical

characteristics, attributes, and values; patient preferences; physician recommendation;

treatment choice; and concordance and outcomes) that influence treatment choice and

outcomes.44,56,141-145

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Figure 1. Factors influencing treatment choices and outcomes of care for patient-centered

prostate cancer care

Abbreviations: HRQoL, health-related quality of life; PSA, prostate-specific antigen; TNM, tumor, nodes, and metastasis.

As depicted in Figure 1, patient preferences, physician recommendations, and factors

such as desire to participate in treatment choice, decision conflict, and trust, influence prostate

cancer treatment choice. The treatment choice in turn is associated with preference/choice

concordance and various outcomes. The entire process of patient-centered care leading to

shared decision-making benefits from information about the choices. As physicians are more

likely to recommend treatments related to their specialty,146 patient-centered care with the

addition of preference assessment can help minimize physician decision bias and help better

inform patients.137,147

Concordance between patient preference (patient’s values for the outcomes they may

experience) and treatment choice is at the core of patient-centered care. Much work on

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“treatment preferences” has focused on treatment choice.7,10,17,34,36,104,111,135,137,138,148 In this

research, we expanded the focus to identify patterns of preferred treatment attributes (value

markers or utility levels) that helped us design better ways to align treatment with patient

preference. This can shed more light on the concept of patient-centered care and its

integration with comparative effectiveness of prostate cancer treatments. We used conjoint

analysis to determine individual-level utilities for treatment attributes and latent profile

analysis to determine common profiles of valued treatment attributes or “value markers.” The

combination of conjoint analysis and latent profile methods is used in the consumer behavior

field to determine market segmentation. This combination has the potential to move beyond

descriptive information about who makes which treatment choices and to tell us more about

the factors underlying the choices and the consequences of treatment alignment with value

markers. The conjoint method holds the promise of improved alignment of preferences with

choice because the focus is on the treatment attributes that men value most.

Implementing patient-centered care and patient choice for localized prostate cancer

care is not without challenges. Our patient-centered research is novel in its aim to close this

knowledge gap. We study the complex interplay of preference and treatment decisions and

their relationship with objective and subjective outcomes in prostate cancer patients receiving

active surveillance, surgery, or radiation. It is important to understand the process of

discovering what patient-centered care will mean and what clinicians and researchers must do

to transform the concept into a safe and effective reality. How much improvement in quality of

life should there be, and what, therefore, is the value of quality of life? Conventional economics

couches its answer in terms of individual preferences for particular outcomes and

demonstrates that something is of instrumental value to the extent that an individual is willing

to pay for that preference. Underlying this approach is the axiomatic assumption that

individuals usually make choices (or express preferences) that benefit or enhance their welfare.

There is little research regarding how patients’ personal values shape and influence their

decisions. No published study related to prostate cancer has addressed treatment decision

criteria, preference assessment factors associated with differential outcomes, and psychological

well-being in treatment choice and outcomes.

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1. The objective of our 2-phase study is to test the comparative effectiveness of an ACA

intervention with that of usual care and identify preferred attributes of prostate cancer

treatments (including active surveillance) that will facilitate patient-centered care. The

overriding study hypothesis is that the ACA-based preference assessment intervention

(ie, PreProCare) will, by aligning choice with preferences, have an effect on primary

outcomes of satisfaction with care, satisfaction with decision, and treatment choice;

secondary outcomes of generic and prostate cancer-specific HRQoL; and psychological

well-being. Additionally, we hypothesize that prostate cancer patients whose treatment

choice is more concordant with their value markers will have improved outcomes. The 4

study-specific aims (adjusting for patient age, race/ethnicity, and stage) are as follows:

To assess (using ACA) patient treatment preferences and identify attributes (utility levels

or value markers) of the treatment most valued

2. To assess the effects of patient decision conflict, physician trust, and preference for

participation in decision-making on treatment choice and objective and subjective

outcomes

3. To assess the comparative effectiveness of a conjoint analysis intervention on

treatment choice, satisfaction with care, satisfaction with decision, regrets, and

outcomes (objective and subjective) compared with that of usual care

4. To analyze the association of concordance between stated individual preferences and

treatment received with objective and subjective outcomes

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PARTICIPATION OF PATIENTS AND OTHER STAKEHOLDERS

We carefully designed our study to receive strong and substantial input from

stakeholders (patients and providers) during all phases of the study to ensure that the research

findings would be highly relevant to the treatment population. Following is a discussion of the

engagement activities.

Types and Numbers of Stakeholders

Our stakeholders consisted of 2 main types: advisory board members and phase 1

participants. The advisory board stakeholders consisted of 4 prostate cancer survivors, 8

physicians, 2 nurse practitioners, and 1 representative from a prostate cancer support group.

The phase 1 stakeholders consisted of 50 prostate cancer survivors and 117 providers.

Deciding on and Achieving the Desired Balance of Stakeholder Perspectives

We planned to engage advisory board stakeholders at the beginning of the study to help

clarify assumptions, explore competing explanations, and develop consensus about the issues

of prostate cancer treatment attributes. Stakeholders also provided input toward survey

design, decision-making tool design, and pilot testing of the tool to ensure that we collected the

most essential and appropriate information. Our stakeholders also engaged in the

interpretation, translation, and dissemination of findings to optimize the usefulness of this

research.

Methods Used to Identify and Recruit Stakeholder Partners

From the pool of prostate cancer patients who had received treatment at any of the

study sites, we randomly invited 10 patients who represented a mix of different treatment

modalities. Four of these patients accepted an invitation to be stakeholders after learning

about the study and its required involvement. The physician stakeholders represent different

specialties and sites and are part of ongoing collaborative research endeavors. Finally, study

investigators identified and recruited a representative from the prostate cancer support group.

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Methods, Modes, and Intensity of Engagement: Patient and Stakeholder Involvement as Advisory Board Members

Our stakeholders (providers and prostate cancer survivors) were also actively involved in

all aspects of the study in their capacity as advisory board members. In both phase 1 and phase

2 of the study, we conducted regular quarterly meetings of the advisory board and discussed

the progress, barriers, and opportunities for various study-related activities. During phase 1, the

advisory board members provided important input for the attributes, levels of the attributes,

and the conjoint tool development. In phase 2 of the study, we received important feedback for

strategies for recruitment, retention, and dissemination of study results.

Stakeholder Involvement in Phase 1

Phase 1 of our study focused on the development of our web-based preference

assessment tool (ie, PreProCare) using conjoint analysis. Providers contributed to the process of

eliciting treatment attributes via focus group participation. Five structured focus group

meetings were organized, consisting of 2 groups with urologists (n = 19) and 1 group each with

radiation oncologists (n = 6), primary care physicians and geriatricians (n = 24), and nurse

practitioners (n = 19).

Patient Involvement in Phase 1

The treatment experience of prostate cancer survivors was captured in one-on-one, in-

depth, in-person interviews with 50 prostate cancer survivors and helped us identify attributes

of treatment that matter most to patients.

Perceived or Measured Impact of Engagement

We did not formally measure the “impact” of our engagement. However, the robustness

of our preference assessment tool, acceptability of our intervention from patients and

providers, and, finally, completed recruitment of 743 patients with localized prostate cancer

across a multicenter environment, with retention of over 75% at 24 months, is a direct

testimony to the overall involvement of our stakeholder advisory group.

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How the Engagement of Patient or Other Stakeholder Partners Changed the Research

The stakeholders contributed to the development of the PreProCare tool and

recruitment, retention, and dissemination strategies for the study. The advisory board

members were instrumental in identifying and reviewing the attributes of prostate cancer

treatment that were fundamental to the development of PreProCare. The discussions were

very informative and centered on the entire spectrum of prostate cancer care, from diagnosis

to the post treatment period. For example, some of the topics were information needs of

prostate cancer patients (sources, level of usage, timing, reliability and validity, and being

unbiased), the importance of adverse effects, etc. The stakeholders also acknowledged the

importance of the PreProCare tool we developed as part of this study. The patient stakeholders

from the advisory board often commented that they wished they had had a similar tool

available during their diagnosis phase. Another novel contribution of our patient stakeholders

from the advisory board was in the form of in-depth discussion during one of the advisory

board meetings about the importance of patient participation in studies and the general

concept of patient-centered care. As a result, the patient stakeholders expressed interest in

discussing their perspective about patient-centered care. Therefore, we initiated a conversation

with our patient stakeholders from the advisory board regarding patient-centered care and

outcomes. A list of broad “talking points” was developed and used to conduct extensive

interviews and conversations with the patient stakeholders to gain insight into their perspective

about patient-centered care and outcomes research. Our team worked very hard to arrange

these meetings, and the results were extremely productive. The outcome is a manuscript

published in the Journal of the Royal Society of Medicine (2017; See Related Publications list).

Additionally, these results were presented at the AcademyHealth Annual Conference on June

27, 2016, in Boston, Massachusetts.

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METHODS

Study Overview

This was a 2-phase, mixed-methods study among patients with localized prostate

cancer, as depicted in Figure 2. In phase 1, we developed our PreProCare tool for preference

assessment among these patients. This web-based tool used a conjoint analysis technique to

elicit preferences. Our comprehensive approach for the development of our PreProCare tool

consisted of a systematic literature review, one-on-one interviews with prostate cancer

survivors, and focus groups of providers. Next, in phase 2 of the study, we employed a

multicenter randomized controlled trial (RCT) to assess the comparative effectiveness of our

PreProCare tool in improving outcomes of care among patients with localized prostate cancer

compared with those receiving usual care. Intervention group participants completed the

PreProCare tool before treatment decisions. We assessed outcomes for the intervention group

and the usual care group at baseline and at 3, 6, 12, and 24 months and used repeated-

measures analysis to compare within-group and between-group effects.

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Figure 2. Schematic representation of overall study designa

Abbreviations: AS, active surveillance/watchful waiting; BT, brachytherapy; CA, conjoint analysis; CPS, Control Preferences Scale; DCS, Decision Conflict Scale; EBRT, external beam radiation therapy; HRQoL, health-related quality of life; inst., instrument; PT, proton therapy; RALP, robotic-assisted laparoscopic prostatectomy; RP, radical prostatectomy; Sat; satisfaction. aPhase 1 consists of the development of conjoint analysis task intervention, and phase 2 consists of a randomized controlled study among localized prostate cancer patients.

Study Design

We adopted a mixed-methods design for this 2-phase study. In phase 1, we used a

systematic literature review and meta-analysis, followed by provider focus groups and one-on-

one interviews with prostate cancer survivors to develop our PreProCare tool, a web-based

preference assessment tool. Phase 2 of the study was a multicenter RCT of patients with

localized prostate cancer, in which we assessed the comparative effectiveness of the

PreProCare tool in improving outcomes compared with patients receiving usual care. We now

describe in detail the design for each study phase.

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Phase 1: Development of the Preference Assessment (PreProCare) Tool

Identification of attributes and their levels that are relevant to patients for decision-

making was the critical component of PreProCare development. Here, we describe our

comprehensive approach of integrating a systematic literature review, patient interviews,

provider focus groups, and stakeholder feedback to determine the attributes and levels that are

relevant to patients with localized prostate cancer. As presented in Figure 3, the 5 steps in the

development of PreProCare 60,149,150 were (1) systematic literature review and meta-analysis; (2)

semistructured patient interviews; (3) provider focus groups; (4) finalization of attributes and

their levels; and (5) tool development and pilot testing. In the following sections, we discuss

each step in detail. The local institutional review board approved the study.

Figure 3. Five steps in the development of PreProCare in phase 1 of the study

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Systematic Literature Review and Meta-analysis. The objective of the systematic

literature review and meta-analysis was to ascertain available information regarding patient-

centered attributes associated with prostate cancer treatment options.151 The literature review

yielded attributes and helped in the development of questions for the semistructured

interviews.

Semistructured Patient Interviews. One issue with many decision aids is that they

use terminology and outcomes deemed important by the medical community; however, these

outcomes may not necessarily align with the way patients think about treatment options or the

terms they use. We therefore set out to capture the attributes driven by the experiences of a

wide range of patients. We sampled prostate cancer survivors who had undergone different

treatment modalities (eg, surgery, hormone therapy, radiation therapy, or active surveillance).

The semistructured interviews included open-ended questions informed by our literature

review (see Appendix). We included questions to probe participants about the outcomes

commonly cited in the literature and to understand their experiences. The questions focused

on what patients understood about treatment options, how they decided on a treatment, their

experience of adverse effects, the impact on HRQoL, and anything they wish they had known

before making a treatment decision. Participants also completed a survey that asked them

about entities that were important sources of information and for decision-making, as well as a

list of attributes to rate. Participants rated each attribute on a scale from 1 (very important) to 5

(not at all important) for decision-making, assuming they were making a treatment decision.

Answers were evaluated to determine the internal validity of the responses.105

We obtained a list of prostate cancer survivors from the study sites and invited them to

participate in this one-on-one, in-person interview. Those who agreed to participate provided

informed consent. The study team reviewed the interview transcripts. Saturation occurred

when we did not observe any additional new themes.

20

Provider Focus Groups. Providers are likely to see different sequelae and have

different perspectives on treatment than do patients. Therefore, the third step in our

PreProCare tool development consisted of focus groups with providers from a range of settings

(academic practice, cancer center, and Veterans Affairs-affiliated practice) and backgrounds

(urologists, radiation oncologists, primary care providers, geriatricians, and urologic nurse

practitioners). The focus groups used a semistructured interview format and were conducted

by a facilitator and audio-recorded. The discussions focused on providers’ experiences in

treating localized prostate cancer, clinical information deemed necessary for effective decision-

making, important attributes and their levels, and barriers to optimum treatment choice. Five

structured focus group meetings were organized, with 2 groups with urologists (n = 19) and 1

group each with radiation oncologists (n = 6), primary care physicians and geriatricians (n = 24),

and nurse practitioners from primary care, as well as urology specialty groups (n = 19). The

study team reviewed the focus group transcripts. Saturation occurred when we did not observe

additional new themes.

Finalization of Attributes And Their Levels. We made a list containing all the

attributes from a systematic literature review, patient interviews, and provider focus groups.

The study team, internal and external collaborators, and stakeholder advisory group that

included 4 prostate cancer survivors (patient stakeholders) reviewed the pool of attributes and

their levels. We achieved consensus through deliberation during a study stakeholders’ advisory

board meeting, and a list of final attributes and their levels was developed.

PreProCare Tool Development and Pilot Testing. To develop the PreProCare tool,

we used Sawtooth software152 and developed choice sets using final attributes. Initially, a

choice set presented the different levels of a particular attribute. Responses for these choice

sets led to choice scenarios that were customized, hypothetical, and paired comparisons of

trade-off questions that required an evaluation of multiple aspects of treatment. These choice

scenarios elicited the conjoint trade-offs.

21

We pilot tested the PreProCare tool to assess its feasibility and acceptability. From the

urology practices of a large urban academic health care system, we obtained a convenience

sample of newly diagnosed prostate cancer patients who were treatment naive. We contacted

these patients during their clinic visit, and those who agreed to participate gave informed

consent. A participant could complete the tool in the office or at home using a URL link,

individualized ID, and password. Each participant who completed the pilot received a $20 gift

card. We assessed the time needed to complete the PreProCare tool and asked the participants

to rate the ease of completion and the tool’s usefulness in clarifying values.

Phase 2: Randomized Controlled Trial

Comparative Effectiveness of the Preference Assessment Intervention. The

overall study methodology has been described previously.153 Briefly, in this multicenter RCT, the

intervention was a web-based ACA tool for preferences assessment, the PreProCare tool, and

the output was a list of 5 attributes the patient valued most. Patients completed the

intervention either during the office visit using a study laptop or at home. If completing the tool

from home, we gave the participant a URL link, individualized user ID, and password. All

participants completed self-administered hard copies of the outcome assessments in person (at

the clinic) or via mail at baseline (before the intervention) and at 3-, 6-, 12-, and 24-month

follow-up. We offered participants a $20 gift card at each assessment as a token of

appreciation. Local institutional review boards approved the study. The study had a

stakeholders’ advisory board and a data and safety monitoring committee.

Study Participants

For phase 1, the participants were prostate cancer survivors who participated in one-on-

one interviews. For phase 2, the participants were men with localized prostate cancer.

The study inclusion criteria for phase 2 were as follows:

1. Newly diagnosed with localized prostate cancer (low risk, PSA ≤ 10 ng/ml, Gleason score

≤ 6, and stage T1c-T2a; intermediate risk, PSA > 10 to ≤ 20 ng/ml, Gleason score 7, or

stage T2b; and high risk, PSA > 20 ng/ml, Gleason score 8-10, or stage T2c)

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2. Treatment naive

3. Age ≥18 years

4. Able to provide informed consent

The exclusion criteria were (1) distant, metastatic, or unstaged prostate cancer at

diagnosis; (2) being unable to communicate in English; and (3) having received treatment for

prostate cancer.

Recruitment and Randomization for Phase 2

Recruitment involved the following steps: (1) obtaining consent from a patient’s

urologist/physician for reviewing medical records; (2) determining eligibility via medical

records; (3) screening to assess willingness to participate; and (4) obtaining informed consent

and HIPAA (Health Insurance Portability and Accountability Act) permissions. The study

biostatistician created randomization sequences for each site using a pseudorandom number

generator with random blocking varying in size from 2 to 6. We placed the treatment

assignments in sealed, opaque envelopes. After completing the baseline assessment, research

coordinators opened the envelope and notified the participants of their group assignment. The

participants and their physicians were aware of the intervention status. We blinded the

nonphysician members of the study team and the analyst to the intervention status.

Interventions and Comparators or Controls for Phase 2

Participants in the intervention group completed the web-based ACA PreProCare tool to

assess their individual treatment preferences. In this 3-part tool, a brief introduction was

provided in part 1. In part 2, the participants ranked the attributes of various treatments (not

important to extremely important). In part 3, we presented choice scenarios consisting of

combinations of attributes based on the attributes’ rankings, with participants selecting the

combination they most preferred. At end of the task, a graph and a list of the 5 attributes most

preferred by the participant were generated. The participant had the option to obtain a

printout of the output to share with his provider. On average, this tool required about 30

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minutes to complete. Usual care group participants received care as usual that consisted of

standard educational material about prostate cancer treatments.

Study Outcomes for Phase 2

Satisfaction with care was the primary outcome, and satisfaction with decision,

treatment decision regret, treatment choice, HRQoL (generic and prostate specific), depression,

and urinary symptoms were secondary outcomes. We measured satisfaction with decision and

decision regret at follow-up time points only, and we measured satisfaction with care and other

outcomes at baseline and all follow-up time points.

Patient Satisfaction Questionnaire

In the Patient Satisfaction Questionnaire-18 (PSQ-18) survey, 18 items are consolidated

into 7 subscales to assess satisfaction with medical care and 6 aspects of care.154 The score on

each subscale ranges from 1 to 5, with a higher score indicating better satisfaction. PSQ-18 has

demonstrated good internal consistency (Cronbach α = .86) and excellent test-retest reliability

(r = 0.92).154

Satisfaction With Decision Scale

This 6-item scale measures satisfaction with health care decisions and has excellent

reliability (Cronbach α = .88).155 The score for each item is on a Likert scale of 1 to 5. The total

score is the sum of all 6 items divided by 6. Thus, the total score on the Satisfaction With

Decision (SWD) scale ranges from 1 to 5, with a higher score indicating better satisfaction with

decision.

Memorial Anxiety Scale for Prostate Cancer–Regret Subscale

The 5-item regret subscale of the Memorial Anxiety Scale for Prostate Cancer (MAX-PC)

measures regret about treatment decisions. The regret score ranges from 0 to 100, with a

higher score indicating greater decision regret. The MAX-PC has high internal consistency and

concurrent and discriminant validity.156

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Generic HRQoL: Medical Outcome Study Short Form

We used the Medical Outcome Study Short Form-36 (SF-36) to measure HRQoL. The SF-

36 is a multi-item scale that assesses 8 health domains. One can self-administer the SF-36, or a

trained interviewer can administer it either in person or by telephone. It has been tested

extensively for reliability (r = 0.80-0.93) and validity (Cronbach α = .92). The scores on each

subscale range from 0 to 100, with higher scores indicating better HRQoL.157-161

Prostate Cancer HRQoL: Expanded Prostate Cancer Index Composite

The Expanded Prostate Cancer Index Composite (EPIC) was developed for

comprehensive assessment of HRQoL in men with prostate cancer. It is a 50-item expanded

edition of the 20-item University of California, Los Angeles Prostate Cancer Index (PCI) and

complements other instruments by measuring a broad spectrum of urinary, bowel, sexual, and

hormonal symptoms. It has good psychometric properties, as test-rest reliability and internal

consistency are high for EPIC and for most of the subscales162-164; construct validity has been

established using the SF-36 as a generic core measure and the Cancer Rehabilitation System-

Short Form, a cancer-related HRQOL instrument162-164; and it is easy to understand and

complete. The scores on each subscale range from 0 to 100, with higher scores indicating better

prostate cancer HRQoL.

Center for Epidemiologic Studies Depression Scale

The Center for Epidemiologic Studies Depression (CES-D) scale is a 20-item, self-report

scale to identify depression in the general population and covers major components of

depression, with an emphasis on the following affective components: depressed mood, feelings

of guilt and worthlessness, feelings of helplessness and hopelessness, psychomotor retardation,

loss of appetite, and sleep disorder.165

American Urological Association Symptom Index

The American Urological Association Symptom Index (AUA-SI), a clinically sensible,

reliable, valid, and responsive index widely used for clinical and research purposes,166 has good

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internal consistency (Cronbach α = .86) and excellent test-retest reliability (r = 0.92) and

sensitivity to change, with preoperative scores decreasing from a mean of 17.6 to 7.1 by 4

weeks after prostatectomy (P < .001). The AUA-SI has 7 subscales, and the sum of the raw

values for these provides the total AUA symptom score. The total AUA symptom score ranges

from 1 to 35, and scores are categorized as 1-7, mild; 8-19, moderate; and 20-35, severe.

Treatment Choice

We obtained data on treatment, such as active surveillance, open radical

prostatectomy, robotic-assisted radical prostatectomy, and radiation therapy (intensity-

modulated radiation therapy, brachytherapy, or proton therapy) via medical charts and self-

report.

Covariates

All participants provided self-reported data on age, income, race and ethnicity,

education, marital status, and employment at baseline. In addition, information about patient

control preference using the Control Preferences Scale (CPS),167 decision conflict using the

Decisional Conflict Scale (DCS),168 and trust in physicians and other health care providers using

the Patient Trust-Wake Forest (PTWF) Physician Trust Scale169-172 was measured at baseline.

Clinical and Sociodemographic Covariates

We also abstracted data on prostate-specific antigen (PSA) levels; tumor, nodes, and

metastasis (TNM) stage; grade and histology; Gleason score; and patients’ height, weight,

smoking status, and health insurance from electronic medical records.

Study Setting

The University of Pennsylvania (site 1) was the primary and coordinating site. Other

study sites were the Corporal Michael J. Crescenz Veterans Administration Medical Center (site

2) and the Fox Chase Cancer Center and Temple University Hospital (site 3). We recruited

participants for phase 1 and phase 2 from these study sites. Based on sample size estimates,

the total target accrual goal for our study was 720 participants.

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Time Frame for the Study

We conducted this 2-phase study between July 1, 2013, and June 30, 2017.

Data Collection and Sources

For phase 1, data were collected using a systematic literature review, structured

interviews with prostate cancer survivors, and provider (physicians and nurse practitioners)

focus groups.

All participants in phase 2 completed self-administered outcome assessments at

baseline (before the intervention) and at 3-, 6-, 12-, and 24-month follow-up. We obtained

clinical data through a structured medical chart review.

Analytical and Statistical Approaches

Analysis for Phase 1

Analysis was consistent with the steps described above. The literature review was

conducted by 3 independent reviewers per the PRISMA (Preferred Reporting Items for

Systematic Reviews and Meta-analyses) criteria.173 For different treatment types, we

summarized the patient-centered outcomes to facilitate identification of attributes and their

levels. Next, patient interviews and focus groups were audio-recorded, transcribed, and

entered into NVivo-10.174 We chose thematic analysis as the methodological framework within

which to analyze the interview and focus group data. This form of analysis is data driven, and it

theorizes broader assumptions, structures, and/or meanings as underpinning what the data

articulate. We used NVivo-10 to organize data and develop consistent and comprehensive

attributes. We performed thematic analysis in 6 phases, including familiarization with data;

initial code generation; searches for attributes among codes; reviews of attributes; definition

and naming of attributes; and synthesis of the final results. Four research team members used

grounded theory for code generation, and verified the method to ensure intercoder agreement.

Discrepancies in coding or attribute definitions were resolved via discussion. Initial codes were

generated using an inductive process, collating data relevant to each code. We developed

potential attributes by collating initial codes into a thematic map of the analysis. Ongoing

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analysis led to a refinement of each attribute and the generation of clear definitions and

names.

Analysis for Phase 2

Power Calculations. Assuming an anticipated dropout rate of 10%, we needed a

sample size of 360 patients per group to detect the following: an effect size as small as 0.2 of

the SD in the outcomes of satisfaction with care and satisfaction with decision, a 2-sided 5%

significance level, power of 80%, conservative intraclass correlation of 0.3, and 4 follow-up

measures per patient%.

We compared the sociodemographic and clinical variables between the intervention

and usual care groups. Additionally, we compared baseline scores of control preference, trust,

and decision conflict between the intervention and usual care groups using a chi-square test.

We tested for differences in patient demographic variables in those who completed the study

compared with those who were lost to follow-up. We performed analysis according to the

intent-to-treat principle. We used mixed-effects models to estimate changes over time for

satisfaction with care, satisfaction with decision, regret subscale of MAX-PC, and generic HRQoL

(SF-36) and prostate cancer HRQoL (EPIC), while accounting for correlation among repeated

measures. The models also assume that outcome measures are missing at random.175 The final

models included indicators for assessment time, indicators for intervention group, the group-

by-time interaction, and study site, which was the stratified randomization factor. The

interaction term allows for a comparison of the longitudinal changes in outcomes between the

intervention groups. We used Bonferroni correction as appropriate.

Specific Aim 2. This aim was to assess the effects of patient decision conflict, physician

trust, and preference for participation in decision-making on treatment choice and objective

and subjective outcomes. For specific aim 2, we first tested the association between decision

conflict, patient trust, and preference for participation in decision-making and treatment

received using a multinomial regression model to adjust for observed covariates. We examined

whether these associations varied across the intervention and usual care control groups, and

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we repeated the model with other independent variables (decision conflict and trust). Next, we

tested the association denoted by direct effect of the DCS, CPS, and trust on outcomes. For

continuous outcomes (ie, HRQoL, AUA-SI, MAX-PC, CES-D, SWD, and PSQ-18), we computed the

area under the curve for each measure for each patient. In our main analysis, we analyzed the

series of functional status measures using linear mixed models that predict the outcome from

time, independent variables, and their interaction. We repeated the analyses by including the

treatment received in the models. To analyze the confounding effect of treatment on the

association between DCS, CPS, or trust and outcomes, we tested whether the observed effects

of DCS, CPS, or trust on outcomes were weaker after controlling for treatment.

Specific Aim 3. This aim was to assess the comparative effectiveness of a conjoint

analysis intervention on treatment choice, satisfaction with care, satisfaction with decision,

regrets, and outcomes (objective and subjective) compared with usual care. To analyze the

association between intervention group and longitudinal outcomes, we used mixed-effects

models. For specific aim 3, each of the 7 subscales of the instrument to measure satisfaction

with care (ie, PSQ-18) was modeled separately using the mixed-effects model to estimate

changes from baseline to follow-up points for the intervention group and usual care group. In

the absence of an established measure of clinically meaningful change in satisfaction with care,

we chose a change of 0.5 times the SD as the minimal clinically important difference (MCID).

For HRQoL (generic and prostate cancer specific), similar item-level analyses were performed.

For satisfaction with decision outcome (ie, SWD scale), we performed 2 sets of analyses. The

first type of analysis for satisfaction with decision was repeated measures of the total score. We

reversed the final score to force a right-skewed distribution and then fitted a mixed-effects

model with gamma distribution of the scores and log link.175 We conducted the second type of

analysis for satisfaction with decision at the item level. The SWD scale has 6 items scored on a

Likert scale (1 = strongly agree, 2 = agree, 3 = neutral, 4 = disagree, and 5 = strongly disagree).

“Strongly agree” and “agree” were combined and reported as “satisfied.” We compared the

proportion satisfied between the intervention and usual care groups at each time point, using

chi-square analysis. Similarly, we performed 2 types of analysis for the regret subscale of MAX-

PC. First, we analyzed the total regret score using a mixed-effects model. The regret subscale

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asks how true each of the 5 statements is for the respondent. Each statement is scored on a

Likert scale (1 = not at all, 2 = a little bit, 3 = somewhat, 4 = quite a bit, and 5 = very much). We

considered those reporting “not at all” as having no regret. We compared the proportions with

no regret between the intervention and usual care groups at each time point, using chi-square

analysis. For depression outcome (using CES-D), we determined the categories of depression

using the total score (score of 0-14, low depression; 15-21, moderate depression; and ≥21, high

depression). We compared the proportion of participants in each depression category between

the intervention group and usual care group over time, using chi-square analysis. Similar

analysis was conducted for 3 categories of urinary symptoms based on AUA symptom score

(score of 1-7, mild; 8-19, moderate; 20-35, severe). We analyzed treatment choice across

prostate cancer risk categories of low, intermediate, and high for the intervention and usual

care groups using chi-square analysis.

As a first step for our specific aims 1 and 4, we began by assessing individual-level

utilities, followed by latent profile analysis based on these individual level utilities, as described

below.

Individual Utilities for Attributes of Treatment (conjoint task analysis)

Our PreProCare tool requires prostate cancer patients to make choices between

hypothetical treatment options based on the attributes. Each participant in the intervention

group who completed the PreProCare tool was asked to express his preference for attributes of

various prostate cancer treatments based on choice scenarios presented, which varied in the

attribute levels of the various treatment choices. The balancing or trade-off of treatment

features was captured in the patient-specific utilities or part-worth associated with the

attribute levels in the study. The basis for discrete choice conjoint analysis is a mixed-effects

logistic model with a pair of fixed and random effects defined for each attribute considered as

a covariate. We assumed 2 attributes, x1 and x2, with binary discrete choice response variable Y.

The corresponding mixed-effects logistic model for the mean of Y (µ = E(Y |x1, x2)) is:

30

log[( − ) = ( + ) x + ( + ) x +

β1 = the log odds ratio for option A vs option B with respect to attribute 1 (estimate of this

parameter will allow us to obtain part-worth for this attribute)

β2 = the log odds ratio for option A vs option B with respect to attribute 2 (estimate of this

parameter will allow us to obtain part-worth for this attribute)

θ = overall patient-level utility

θ1 = patient-level utility for attribute 1

θ2 = overall patient-level utility for attribute 2

The estimation of θ1, θ2 and θ is based on an empirical Bayes approach using maximum

likelihood estimates (MLE) of and Under this approach, we assume that θ1, θ2 and θ have

a multivariate normal distribution with mean zero and variance-covariance Σ MLE of and

and Σ is based on the marginal likelihood derived from integrating θ1, θ2 and θ from the

likelihood. With estimates of and and Σ, we obtain empirical Bayes estimates of θ1, θ2 and

θ. We performed this estimation in SAS (Proc NLMIXED), which allowed us to assess the

sensitivity of this modeling approach to assumptions of normality of the random-effects utility

parameters by trying non-normal random-effects distributions.

Value Markers (Latent Profiles Based on Individual Utilities)

We carried out analyses of individual-level utilities to classify patients according to

profiles or patterns of utilities using latent profile analysis. Latent profile analysis is a technique

used to identify hidden groups from observed data. The profiles derived from the latent profile

analysis facilitate the determination of the value markers representing patterns of treatment

attributes that patients value. One can use the empirical Bayes estimates of the subject-level

utilities as inputs to a growth curve mixture model (ie, latent profile analysis) to obtain patterns

of treatment preferences as represented by the estimated utilities from the conjoint analysis.

Such patterns correspond to latent classes based on a random-effects linear model with a

multivariate set of utilities as the continuous dependent variables. We implemented this model

in Mplus version 6.12 (Muthén & Muthén). The number of classes was determined using the Lo-

31

Mendell-Rubin adjusted likelihood ratio test.176 Mplus reports a bootstrapped P value to

account for departures from model assumptions, such as the multivariate normal distribution

of the attribute-specific utilities. We described these profiles in terms of descriptive statistics of

the multivariate set of attribute set utilities.

We studied value markers or utility levels of the attributes for their relationships with

demographic and clinical characteristics and with outcomes. We performed logistic regression,

with the study outcomes as dependent variables and the utility-based profiles as independent

variables and with and without adjusting for patient characteristics in the model in order to

observe the influence of the characteristic. For each case, we based the evaluation of

association between these profiles and outcomes on a likelihood ratio test of the set of odds

ratios corresponding to dummy variables of the profiles. We also performed a sequence of

pairwise tests of comparisons of the profiles in terms of the proportion of the type of treatment

received, based on Holm’s multiple-comparisons approach.177 This procedure was hierarchical

and identified the utility-based profile at the start of the process before making other

comparisons, thus protecting type I error from additional comparisons. Specifically, Holm’s

approach tests each pairwise comparison in ascending order of P values. Successively larger P

values have less rigorous α. The sequential Holm tests terminate after the first nonsignificant

comparison, so no subsequent comparison is significant.

We analyzed the association of the concordance between (1) patient preference and

attributes of treatment received and (2) outcomes, adjusting for covariates. Understanding and

respecting a patient’s preference is the main feature of concordance.59,61 Thus, the first step in

concordance is understanding the patient’s view, followed by agreeing on the treatment plan

that integrates these views about preferences for treatment attributes. We operationalized

patient preference concordance as “agreement between a patient’s value markers (utility

levels) and attributes of the treatment that the patient receives (choice)” and using κ statistics.

We tested the hypothesis that preference concordance is associated with outcomes. For

outcomes of satisfaction with decision and satisfaction with care, urologic symptoms (AUA-SI),

generic and prostate-specific HRQoL, and depression, we performed inferential analysis with

32

parametric and nonparametric tests. We used log-linear models, with logs of satisfaction with

decision and care, depression, and HRQoL scores as dependent variables. The independent

variables were intervention group status (preference assessment group vs usual care group),

time, interaction of time and intervention group status, and study site. We compared the

proportion returning to baseline (ie, pretreatment) HRQoL values using chi-square analysis and

with logistic regression using “return to baseline” as the dependent variable and preference

concordance as the independent variable. We used a Wilcoxon matched-pairs test for

comparisons within concordant and nonconcordant groups. We defined a “concordant” group

as having at least 75% agreement between value markers (utility levels). We compared baseline

with 6- and 24-month assessments, as the literature suggests these are clinically the most

relevant time points.

Changes to the Original Study Protocol

We made no changes to the original study protocol.

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RESULTS

Phase 1

Systematic Literature Review and Meta-analysis

We reviewed 56 articles that met our criteria. The details of the literature review have

been reported.151 Table 1 presents a synthesis of the comparative evidence for survival, cancer

recurrence, adverse effects, and HRQoL, satisfaction with care, and decision regrets across

treatment groups,151 including conservative management strategies (watchful waiting or active

surveillance. The literature synthesis informed the subsequent semistructured patient

interviews (Appendix) and provider focus groups. The following patient-centered attributes

were revealed from the literature review (see Figure 4): survival (disease specific and

nonspecific); cancer recurrence (eg, metastasis); complications (blood loss, recurrence,

incontinence, and erectile dysfunction); adverse effects (fatigue, nausea, and loss of fertility);

and HRQoL (functional status and generic and prostate cancer-specific HRQoL).

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Table 1. Synthesis of Patient-Centered Outcomes Evidence for Localized Prostate Cancer: Summary of the Literature151

Treatment Survival Cancer recurrence and metastasis Complications

Side effects, HRQoL, anxiety, and depression

Conservative management (WW or AS)

Overall: RP or RT improved survival in men aged 65 to 80 y compared with WW; WW was associated with lower 10-y survival than RP and RT

Disease specific: RP advantage over WW

Bone metastasis was more common with WW than with RP

Weak urinary stream reported by 28% of RP and 44% of WW men after mean 4 y of follow-up

Over mean follow-up of 4 y, bowel function, well-being, anxiety, depression, and QoL were comparable between RP and WW; WW patients had better erectile function and urinary control in the initial 2-5 y postdiagnosis

RP, RARP, or LRP

Overall: RP advantage over WW/RT and WW

Disease specific: with ≥10-y life expectancy, improved survival with RP compared with WW and RT; the survival benefit of RP was largest in men ≤65 y compared to that with WW

RP was associated with lower risk of metastasis than WW; RP had good long-term clinical outcomes and avoided use of ADT in 70% of patients

Common complications in the first 30 d of RP: wound infection, urinary tract infection, surgical repair, bleeding, and urinary catheterization

RARP showed improved surgical margins and less use of postsurgery ADT and RT compared with RP

RT, EBRT, IMRT, BT, or PT

Overall: advantage with RP over EBRT and BT, and with BT over EBRT; survival rates between high-dose and low-dose RT were comparable; with <10 y of life expectancy, RP and RT had comparable survival rates

Superior long-term cancer control with high-dose RT compared with conventional RT

GI and GU toxicities did not differ among RT dose schedules; acute GI/GU toxicity is higher in a shorter schedule than in a

Comparable disease-specific urinary, sexual, and bowel outcomes with RT compared with RP; no differences between RT and WW in fatigue, nausea/vomiting, and pain; RT had decreased social functioning

35

Treatment Survival Cancer recurrence and metastasis Complications

Side effects, HRQoL, anxiety, and depression

Disease specific: RP advantage over RT

longer schedule, and late toxicity was low in both

compared with WW due to hematuria, urinary incontinence, and mucus as well as decreased daily activity due to GI problems

ADT Overall: Primary ADT had no survival benefit over 5 y compared with WW; no difference in post-op mortality with neoadjuvant ADT compared with RP alone; no survival benefit with primary ADT compared with WW; survival benefit with ADT plus RP compared with ADT alone

Disease-specific: No survival benefit with primary ADT; increased survival with ADT plus RP compared with ADT alone

No improvement in biochemical recurrence or metastasis with neoadjuvant ADT vs RP alone

No difference in perioperative blood loss, operating time, need for transfusion, or length of stay with neoadjuvant ADT (before RP) compared with RP

Common adverse effects with ADT included hot flashes, diarrhea, nausea with or without vomiting, and abnormalities in liver function tests; compared with EBRT, neoadjuvant ADT with EBRT showed increase in mild to moderate gynecomastia and severe impotence

Abbreviations: ADT, androgen deprivation therapy; AS, active surveillance; BT, brachytherapy; EBRT, external beam radiation therapy; GI, gastrointestinal; GU, genitourinary; IMRT, intensity-modulated radiation therapy; LRP, laparoscopic radical prostatectomy; PT, proton therapy; QoL, quality of life; RARP, robotic-assisted radical prostatectomy; RP, radical prostatectomy; RT, radiation therapy: WW, watchful waiting.

36

Figure 4. Steps in the development of attributes for the PreProCare tool

Semistructured Patient Interviews

We conducted 50 one-on-one, face-to-face interviews with prostate cancer survivors.

These interviews revealed the complexity of treatment decisions beyond clinical characteristics.

The mean (SD) age of these prostate cancer survivors was 65.8 (7.9) years, and about two-

thirds (67%) of the survivors were white. Sixty-five percent had undergone surgery, 25% had

received radiation therapy, and 10% were on active surveillance. The mean (SD) time since

diagnosis was 3.8 (3.7) years. On average, each interview was 30 minutes long. In addition to

the attributes discussed in the literature (eg, survival and adverse effects), patients identified

the following attributes (Figure 4): impact of treatment, impact on social life, recovery pattern,

emotional concerns (depression and anxiety), caregiver burden, and out-of-pocket costs.

37

Patients noted that the burden on caregivers varies across treatments. For example, compared

with radiation, surgery requires more support from family; therefore, patients with less family

support may avoid surgery. One-on-one patient interviews were critical in identifying unique

patient experiences and perspectives.

Provider Focus Groups

Five structured focus group meetings were organized, with 2 groups with urologists

(n = 19) and 1 group each with radiation oncologists (n = 6), primary care physicians and

geriatricians (n = 24), and nurse practitioners (n = 19). Each meeting was conducted by a

facilitator and was 2 hours long on average. The following attributes emerged from provider

focus groups (Figure 4): treatment adverse effects, complications, survival, and short- and long-

term prostate cancer–related HRQoL. Similar to patients, providers noted that certain

treatments could cause more (or less) caregiver burden. Providers differed from both patients

and the literature regarding the nuances in the timing of complications. Urologists and

radiation oncologists made an important distinction between short-term and long-term

outcomes in terms of severity and importance. Geriatricians and primary care physicians saw

their role as patient advocates and noted that erectile dysfunction and urinary incontinence

each affect men differently, in that men accept erectile dysfunction more easily than they

accept urinary incontinence, which has an impact on everyday function. Nurse practitioners and

registered nurses discussed the effects of treatment on quality of life. Provider focus group

participants completed a brief survey to determine the face validity of the attributes we had

identified from the literature review.

Finalizing Attributes and Levels

We narrowed the patient-centered outcomes into the following 5 broad categories:

survival; cancer recurrence; prostate cancer treatment consequences and treatment specifics;

emotional concerns and impact on social life; and burden of prostate cancer. We shared the

attributes belonging to these categories and their ideal wordings with the stakeholders’

advisory group (Figure 4). In cases of disagreement, we reached consensus by deliberation. As

38

we had obtained attributes from different sources, we achieved validation using data

triangulation. The study team, internal and external collaborators, and stakeholders’ advisory

group that included 4 prostate cancer survivors (patient stakeholders) developed the final list of

attributes (Table 2). We employed best practices to ensure that the attributes (1) did not

exceed a sixth-grade reading level, as measured by the Flesch-Kincaid grade level standard; (2)

minimized ambiguity or cognitive difficulty; (3) were concise and simply worded; and (4) were

easy to translate into languages other than English.149,178,179

39

Table 2. Final Attributes, Definitions, and Levels for the PreProCare Tool

Attribute (broad category) Definitions Levels

1. Survival (survival)

Overall and prostate cancer–specific survival

• Low, 85% of the patients survive 10 y

• Medium, 95% of the patients survive 10 y

• High, 98% of the patients survive 10 y

2. Cancer recurrence or progression (recurrence)

Prostate cancer progression or recurrence is defined clinically, may not be reflected in how you feel or in your overall survival

• Low, 10%

• Medium, 20%

• High, 30%

3. Change in urinary function or bother (treatment consequences)

Problem with urinary function or bother refers to leaked urine, blood in urine, pain/burning with urination, urine control, need for pads or catheter, straining urine, or weak urine stream

Short term

• Low, 20%

• Medium, 30%

• High, 60% Long term

• Low, 10%

• Medium, 20%

• High, 30%

4. Change in sexual function or bother (treatment consequences)

Problem with sexual function or bother refers to low sexual desire/libido, impotence or erectile dysfunction, change in penis length, or wearing a condom

Short term

• Low, 20%

• Medium, 30%

• High, 60% Long term

• Low, 10%

• Medium, 20%

• High, 30%

5. Change in bowel function or bother (treatment consequences)

Problem with bowel function or bother refers to rectal urgency, gastrointestinal problems, stool leakage, or pain during bowel movement

Short term

• Low, 10%

• Medium, 30%

• High, 50% Long term

• Low, 5%

• Medium, 15%

• High, 30%

40

Attribute (broad category) Definitions Levels

6. Psychological distress (emotional concerns and impact on social life)

Stress, anxiety, or depression during the postdiagnosis period

Short term

• Low, 10%

• Medium, 20%

• High, 30% Long term

• Low, 5%

• Medium, 15%

• High, 20%

7. Adverse effects (treatment consequences)

Fatigue, toxicity, loss of energy/weakness, hot flashes, weight changes

Short term

• Low, 10%

• Medium, 20%

• High, 30% Long term

• Low, 10%

• Medium, 30%

• High, 40%

8. Treatment duration (treatment specifics)

Total length of treatment, including hospital stay or multiple treatment sessions

• Low, 4 d

• Medium, 2 mo

• High, 3 mo

9. Need for cutting (treatment specifics)

Treatment involves cutting or surgery • None, no cutting

• Medium, minimal cutting/surgery

• High, involves cutting/surgery

10. Radiation or seed implants (treatment specifics)

Treatment involves radiation-related burns or seed implants

• None, no radiation burns or seed implants

• Medium, moderate

• High, extensive

11. Recovery time (treatment specifics)

Average time to recover to your pretreatment functioning

• Low, 3 mo

• Medium, 6 mo

• High, 24 mo

41

Attribute (broad category) Definitions Levels

12. Cancer control (treatment consequences)

Some treatments aim for complete “cancer control,” while some may be for monitoring cancer

• Low, monitor cancer closely

• Medium, medium cancer control

• High, high cancer control

13. Out-of-pocket expenses (burden of prostate cancer)

Although your health insurance may cover the major treatment-related expenses, there will be some out-of-pocket expenses related to treatments, such as co-pays, travel, parking, meals, etc

• Low, $50

• Medium, $500

• High, $5000

14. Caregiver burden (burden of prostate cancer)

Your spouse, partner, and/or family members may help you during your treatment; below is an assessment of the average time spent by your spouse, partner, or caregiver(s) in helping you

• Low, 1 h/d

• Medium, 2 h/d

• High, >2 h/d

15. Social interaction (emotional concerns and impact on social life)

Some treatments may make it hard to be around others, ie, you may need to stay away from children and pregnant women for short term, and you may have decreased social activity or self-esteem

• Low, minimal problems with social interaction

• Medium, hard with social interaction

• High, very hard with social interaction

Development of the PreProCare Tool

We used the Sawtooth ACA program to create the computer-based PreProCare tool

consisting of 15 attributes. All possible resulting “pair comparisons” were reviewed for

language and clarity. Our final version of the tool consists of 3 parts. Figure 5 presents an

example of each part. The tool begins with a brief introduction and instructions. We provided

descriptions and definitions for important terms and levels. Part I identifies attributes that are

important to the respondent (values clarification component). The tool presents the participant

with a hypothetical choice of 2 different treatments with varying levels of an attribute. The

participant is asked how important the difference in the levels is to them, ranging from not

important to very important. The participant goes through 9 such comparisons, and the

42

answers form the basis for part II, where choice scenarios and a vignette for individual

attributes are presented. Each choice scenario is a comparison of 2 hypothetical treatments.

Each treatment is a “bundle” of 3 attributes whose levels differ across the hypothetical

treatments. The participant decides which treatment he prefers after “evaluating” the

associated bundle of attributes and levels. Based on the input from parts I and II, the tool

generates a list of 5 attributes deemed most important by the participant (part III). This list is in

a printable format, and participants are encouraged to share it with their physicians.

43

Figure 5. PreProCare adaptive conjoint analysis tool snaphot of attribute selection, choice scenarios, and result

44

Pilot Testing of the PreProCare Tool

Stakeholder members of the study advisory board reviewed the final version of the

PreProCare tool in the presence of a research staff member and provided feedback about the

comprehensiveness and flow, adopting a think-aloud technique. Based on this feedback, we

revised the content by simplifying the language, adding images, and presenting the results as a

printable list of the top 5 attributes. Next, to determine the usability and acceptability of the

PreProCare tool, 52 newly diagnosed prostate cancer patients who were treatment naive

completed the tool. There was no overlap between these patients and the members of our

stakeholder advisory board. On average, the patients required 30 minutes to complete the tool.

Patients also completed a 1-page survey about its usability and feasibility. As shown in Table 3,

of the 52 participants, 49 (94%) said that the definitions were easy to understand, 45 (86%) felt

that the tool was helpful in deciding treatment, and 46 (88%) said they would discuss the

results with their physicians.

Table 3. Pilot Testing Reponses for the PreProCare Tool in Newly Diagnosed Prostate Cancer

Patients Who Were Treatment Naive (n = 52)

Response = “yes” No. (%)

Age group, y

<50 1 (2)

50-65 10 (20)

66-75 28 (55)

>75 12 (23)

Introduction section

Was easy to understand 50 (96)

Text and examples were clear 48 (92)

Information was patient friendly 51 (98)

Are changes recommended? 2 (4)

Part I: attributes selection

45

Response = “yes” No. (%)

Was easy to understand 51 (98)

Text and examples were clear 48 (92)

Information was patient friendly 50 (96)

Are changes recommended? 1 (2)

Part II: making selection vignette

Was easy to understand 45 (86)

Text and examples were clear 48 (92)

Information was patient friendly 45 (86)

Are changes recommended? 5 (10)

Part III: results section

Was easy to understand 50 (96)

Text and examples were clear 51 (98)

Information was patient friendly 48 (92)

Are changes recommended? 2 (4)

Overall

Definition of terms easy to understand 49 (94)

Instrument was helpful in deciding treatment 45 (86)

I will discuss the results with my physicians 46 (88)

46

Phase 2

Baseline Demographics and Clinical Characteristics

We enrolled 743 patients with localized prostate cancer between January 1, 2014, and

March 1, 2015. Figure 6 presents the CONSORT (Consolidated Standards of Reporting Trials)

flow diagram. Across the 3 study sites, we assessed 4558 patients for eligibility; 3317 patients

were excluded for various reasons, and 743 patients were randomly assigned (371 to the

intervention group and 372 to the usual care group). At 24 months, the retention rate was

74.2%. Baseline characteristics were comparable between the intervention and usual care

groups (Table 4). The mean (SD) age of the participants was 63.7 (7.8) years; 82% of the

participants were white, 81% were married, and 61% had at least a college degree. Almost two-

thirds (63%) of the participants had an annual income in excess of $75 000. Table 4 presents a

comparison of the clinical variables from the medical charts. During recruitment, all patients

satisfied the criterion of stage T2c or less. At a later stage, the pathological stage for some

patients was revealed to be T3. Baseline control preferences (CPS), trust (PTWF), and decision

conflict (DCS) were comparable between the groups (Table 5). In Table 6, we present the list of

the attributes and mean utility levels for the intervention group.

47

Figure 6. CONSORT diagram showing flow of participants through phase 2 of the study (N = 743)

48

Table 4. Comparison of Baseline Sociodemographic and Clinical Characteristics of Participants

From Intervention Group vs Usual Care Group

Group (N = 743)a

Intervention (n = 372) Usual care (n = 371)

Age, mean (SD), y 63.9 (8.0) 63.5 (7.6)

Site, no. (%)

1 278 (75) 273 (74)

2 11 (3) 12 (3)

3 83 (22) 86 (23)

Race/ethnicity, no. (%)

White 301 (84) 289 (81)

African American 50 (14) 52 (15)

All other 9 (3) 16 (4)

Annual income, no. (%), $

≤40 000 50 (16) 53 (17)

40 001-75 000 62 (20) 66 (22)

≥75 000 198 (64) 188 (61)

Marital status, no. (%)

Married 294 (81) 293 (82)

Single/divorced/widowed 68 (19) 66 (18)

Education, no. (%)

Some college or less 117 (37) 133 (42)

Complete college/advanced degree 202(63) 186(58)

Employment, no. (%)

Full time/part time 189 (59) 180 (57)

Retired 131 (41) 138 (43)

No. of people in household, mean (SD)

2.3 (1.0) 2.4 (1.0)

49

Group (N = 743)a

Intervention (n = 372) Usual care (n = 371)

Smoking, no. (%)

No 212 (59) 210 (58)

Prior history 119 (33) 129 (36)

Yes 28 (8) 24 (7)

Insurance, no. (%)

Medicaid 1 (1) 5 (1)

Medicare (alone or with managed care)

136 (38) 131 (37)

Managed care alone 181 (51) 177 (50)

Private only 35 (9) 42 (12)

T stage, no. (%)

T1a-T1c 162 (51) 170 (54)

T2a-T2c 129 (41) 124 (40)

T3a-T3b 25 (8) 21 (7)

Gleason score, mean (SD) 6.7 (0.75) 6.7 (0.86)

PSA, mean (SD) 8.5 (14.6) 8.4 (7.4)

Abbreviation: PSA, prostate-specific antigen. aMissing values: age, n = 22; race/ethnicity, n = 26; annual income, n = 126; marital status, n = 22; education, n = 105; employment, n = 105; household, n = 106; smoking, n = 21; insurance, n = 32; stage, n = 112; Gleason score, n = 22; and PSA, n = 32.

50

Table 5. Comparison of Baseline Control Preference, Trust, and Decision Conflict of

Participants From Intervention Group vs Usual Care Group

No. (%) by group (N = 551) P value

Intervention (n = 274)

Usual care (n = 277)

CPS items

Make the final selection about which treatment I will receive

16 (6) 16 (6) 0.384

Make the final selection after seriously considering my doctor’s opinion

148 (56) 153 (58)

Have my doctor and I share responsibility for deciding which treatment is best

83 (31) 83 (31)

Have my doctor make the final decision but consider my opinion

18 (7) 10 (4)

Leave all decisions regarding treatment to my doctor

1 (0.4) 4 (2)

PTWFa

Total score, mean (SD) 19.3 (6.0) 19.8 (6.4) 0.397

DCSb

Total score, mean (SD) 33.9 (7.3) 34.1 (6.9) 0.711

Abbreviations: CPS, Control Preferences Scale; DCS, Decision Conflict Scale; PTWF, Patient Trust-Wake Forest Physician Trust Scale. aScore can range from 10-50. Lower score indicates higher trust. bScore can range from 0-100. Lower score indicates lower decision conflict.

51

Table 6. PreProCare Treatment Attributes and Their Average Importance in Intervention

Group Patients (n = 312)

Attribute Average importance

SD

1. Cancer recurrence or progression 8.44 2.39

2. Change in bowel function 8.27 2.57

3. Change in urinary function 7.85 2.23

4. Adverse effects 7.09 2.27

5. Change in sexual function 7.06 2.73

6. Survival 7.05 2.63

7. Recovery time 6.64 2.22

8. Radiation or seed implants 6.45 2.46

9. Social interaction constraints 6.37 2.49

10. Need for cutting 6.11 2.63

11 Psychological distress 6.03 2.36

12. Cancer control 6.02 2.66

13. Caregiver burden 5.65 2.29

14. Treatment duration 5.50 2.13

15. Out-of-pocket expenses during treatment year

5.46 2.73

52

Satisfaction With Care

Table 7 presents the results for the primary outcome of satisfaction with care (PSQ-18),

including estimated changes from baseline to follow-up points for the intervention group and

usual care group for the 7 subscales of the PSQ-18. Positive change values indicate

improvement in satisfaction with care from baseline values. All subscales showed significant

improvement for the intervention group compared with the usual care group. For example,

although general satisfaction improved for both groups, the improvement was larger for the

intervention group. For the general satisfaction subscale, the improvement in the mean (SE)

score at 24 months from baseline was 0.44 (0.06), or equal to 0.5 of the SD, which is clinically

(according to our assigned threshold value) and statistically significant. For the usual care

group, the mean (SE) change was 0.07 (0.06), which is <0.1 of the SD and clinically and

statistically not significant (P = 0.08). Additionally, as shown in the last column of Table 7, the

test of difference between groups for the general satisfaction subscale indicated a significant

group-by-time interaction (F test = 5.39; df = 4,635; P = 0.0003). We observed similar results for

the other subscales of satisfaction with care.

53

Table 7. Comparison of Satisfaction With Care Scores Across Intervention and Usual Care Groupsa

Satisfaction with care (PSQ-18) subscales

Intervention group Usual care group

Test of differ-ence

between groups, P value

Observed mean (SD)

Model estimate change from baseline, mean (SE)

Test of differ-ence over time,

P value

Observed mean (SD)

Model estimate change from baseline, mean (SE)

Test of differ-ence over time,

P value Baseline (n = 274)

3 mo (n = 255)

6 mo (n = 261)

12 mo (n = 251)

24 mo (n = 249)

Baseline (n = 277)

3 mo (n = 254)

6 mo (n = 261)

12 mo (n = 252)

24 mo (n = 240)

General satisfaction

3.96 (0.74)

0.26 (0.05)

0.28 (0.05)

0.31 (0.05)

0.44 (0.06)

<0.0001 3.80 (0.81)

0.07 (0.05)

0.06 (0.05)

0.15 (0.05)

0.07 (0.06)

0.075 0.0003

Technical quality

4.01 (0.64)

0.23 (0.04)

0.21 (0.04)

0.22 (0.04)

0.42 (0.05)

<0.0001 3.93 (0.68)

0.04 (0.04)

0.06 (0.04)

0.11 (0.04)

0.004 (0.05)

0.035 <0.0001

Interpersonal manner

4.19 (0.56)

0.13 (0.04)

0.12 (0.04)

0.13 (0.04)

0.25 (0.05)

0.0002 4.06 (0.66)

–0.0002 (0.04)

0.002 (0.04)

0.001 (0.04)

–0.06 (0.05)

0.737 0.002

Commun-ication

4.08 (0.62)

0.16 (0.04)

0.16 (0.04)

0.23 (0.04)

0.34 (0.05)

<0.0001 4.03 (0.63)

–0.03 (0.04)

–0.02 (0.04)

0.004 (0.04)

–0.09 (0.05)

0.313 <0.0001

Financial aspects

3.81 (0.77)

0.20 (0.05)

0.21 (0.05)

0.28 (0.05)

0.48 (0.06)

<0.0001 3.82 (0.86)

–0.04 (0.05)

–0.02 (0.05)

0.02 (0.05)

–0.04 (0.06)

0.555 <0.0001

Time spent with doctor

3.83 (0.76)

0.23 (0.05)

0.17 (0.05)

0.23 (0.05)

0.39 (0.06)

<0.0001 3.74 (0.80)

0.03 (0.05)

0.001 (0.05)

0.06 (0.05)

–0.02 (0.06)

0.551 0.0002

Accessibility and convenience

3.88 (0.58)

0.19 (0.04)

0.16 (0.04)

0.21 (0.04)

0.41 (0.05)

<0.0001 3.80 (0.66)

0.03 (0.04)

0.02 (0.04)

0.03 (0.04)

–0.03 (0.05)

0.739 <0.0001

Abbreviation: PSQ-18, Patient Satisfaction Questionnaire-18. aSatisfaction with care scores range from 1 to 5. Higher score indicates better satisfaction with care. Positive change indicates higher satisfaction with care compared with the baseline values.

54

Satisfaction With Decision

The results of the log-gamma model of change in total score for satisfaction with

decision indicated that satisfaction with decision improved in both groups (data not reported).

However, the improvement was significantly greater for the intervention group than for the

usual care group. The model estimate of change in mean (SE) score at 24 months from 3

months was –0.142 (0.03) for the intervention group and –0.016 (0.03) for the usual care group

(the negative change score indicates higher value of the score at 24 months compared with the

value at 3 months).

A test of difference between groups for the satisfaction with decision score indicated

significant group-by-time interaction (F test = 6.88; df = 3, 1262; P = 0.0001). There is no

established MCID for this scale. The observed change was 0.3 of the SD for intervention group

and <0.1 of the SD for the usual care group.

In Table 8, we present the longitudinal analysis of comparison of proportion satisfied by

intervention status for each item of the SWD scale. At 3 months, the proportion satisfied was

higher for the intervention group than for the usual care group. However, this difference was

not statistically significant. Compared with the usual care group, a higher proportion of the

intervention group was satisfied for 5 of the 6 items of the SWD scale at 6 months, for 4 items

at 12 months, and for 5 items at 24 months (all P < 0.05).

55

Table 8. Satisfaction With Decision: Comparison of Proportions Satisfied With Decision at Follow-up Points by Intervention Statusa

SDS scale individual item

Proportion satisfied with decision, no. (%)

3 mo 6 mo 12 mo 24 mo

Inter-vention group

(n = 255)

Usual care

group (n = 254)

P value

Inter-vention group

(n = 261)

Usual care

group (n = 261)

P value

Inter-vention group

(n = 251)

Usual care

group (n = 253)

P value

Inter-vention group

(n = 249)

Usual care

group (n = 240)

P value

1. I am satisfied that I am adequately informed about the issues important to my decision

215 (92) 208 (90) .413 233 (95) 217 (88) .016 238 (97) 230 (94) .081 244 (98) 217 (91) .001

2. The decision I made was the best decision possible for me personally

215 (93) 204 (88) .078 230 (94) 216 (88) .044 241 (98) 225 (92) .001 246 (99) 214 (90) .0002

3. I am satisfied that my decision was consistent with my personal values

217 (94) 208 (91) .123 231 (94) 221 (89) .139 240 (97) 229 (94) .041 236 (95) 224 (94) .014

4. I expect to successfully carry out (or continue to carry out) the decision I made

219 (95) 212 (92) .193 238 (96) 222 (90) .007 241 (98) 233 (95) .042 246 (99) 223 (93) .009

5. I am satisfied that this was my decision to make

218 (94) 218 (95) 1.0 241 (98) 229 (93) .018 240 (98) 238 (97) .559 244 (98) 226 (95) .071

6. I am satisfied with my decision

214 (93) 209 (90) .403 233 (95) 214 (87) .005 240 (98) 225 (92) .002 244 (98) 216 (90) .001

Abbreviation: SDS scale, Satisfaction With Decision scale. aEach item of the SDS instrument is scored on a Likert scale (1 = strongly agree, 2 = agree, 3 = neutral, 4 = disagree, and 5 = strongly disagree). “Strongly agree” and “agree” are combined and reported as “satisfied.”

56

Treatment Decision Regret

The results of the mixed-effects model of for change in regret score indicated that

regret declined in both groups (data not reported). However, the decline was greater for the

intervention group. Changes in the estimated mean (SE) scores at 24 months from 3 months

were –2.52 (1.27) for the intervention group and –0.61 (1.23) for the usual care group. A

negative change indicates a decline in regret. A test of difference between groups indicated

significant group-by-time interaction (F test = 3.02; df = 3, 587; P = 0.04).

In Table 9, we present the longitudinal analysis results from a comparison of the

proportions with no regret for the 5 items of the MAX-PC regret subscale. At 3 months, for 4 of

the 5 items, the proportion with no regret was significantly higher for the intervention group

than for the usual care group. Compared with the usual care group, a higher proportion of the

intervention group reported no regret for all items of the scale at 6, 12, and 24 months.

57

Table 9. Regret With Decision: Comparison of Proportion With No Regret With Decision at Follow-up Points by Intervention

Statusa

MAX-PC decision regret subscale individual items

Proportion with no decision regret, No. (%)

3 mo 6 mo 12 mo 24 mo

Inter-vention group

(n = 255)

Usual care

group (n = 254)

P value

Inter-vention group

(n = 261)

Usual care

group (n = 261)

P value

Inter-vention group

(n = 251)

Usual care

group (n = 253)

P value

Inter-vention group

(n = 249)

Usual care

group (n = 240)

P value

I wonder if I would have been better off with a different treatment

183 (72) 167 (66) 0.143 198 (76) 168 (65) 0.004 203 (81) 169 (66) 0.001 183 (73) 144 (60) 0.005

I sometimes wonder whether it was worthwhile being treated at all

197 (77) 176 (69) 0.042 210 (84) 195 (75) 0.007 216 (86) 189 (76) 0.002 213 (85) 175 (73) 0.002

I sometimes feel the treatment I had was the wrong one for me

209 (83) 181 (71) 0.004 227 (87) 193 (74) 0.0002 222 (88) 194 (78) 0.001 220 (88) 171 (71) <0.0001

If I had it to do over, I would choose some other treatment

210 (82) 184 (73) 0.008 228 (87) 198 (55) 0.001 217 (85) 193 (77) 0.006 216 (86) 175 (73) 0.0004

I sometimes wish I could change my mind about the kind of treatment I chose for my prostate cancer

215 (84) 187 (74) 0.003 227 (87) 196 (76) 0.001 220 (88) 194 (77) 0.002 217 (86) 175 (73) 0.002

Abbreviation: MAX-PC, Memorial Anxiety Scale for Prostate Cancer. aThe regret subscale of MAX-PC asks how true each of the 5 statements is for the respondent. Each statement is scored on a Likert scale (1 = not at all, 2 = a little bit, 3 = somewhat, 4 = quite a bit, and 5 = very much). Those reporting “not at all” are considered as having no regret (a lower score indicates less regret).

58

Treatment Choice According to Prostate Cancer Risk Category

Figure 7 shows the treatment choice comparison between the intervention and usual

care groups by prostate cancer risk category. The overall distribution between groups was

statistically significant. In the low-risk group, a higher proportion of intervention group

participants had active surveillance (66%) than usual care participants (54%). For the

intermediate-risk group, 19% of the intervention group received active surveillance, compared

with 20% of the usual care group. In the high-risk group, a higher proportion of intervention

group participants had active treatment (90%) than usual care participants (85%).

59

Figure 7. Overall comparison of proportions with different treatment choices across PreProCare intervention status, stratified by

prostate cancer risk group (n = 674)

60

Generic HRQOL

In Table 10, we present the repeated-measures analysis results for generic HRQoL using

SF-36. Generic HRQoL scores range from 0 to 100. A higher score indicates better generic

HRQoL. A positive change indicates better HRQoL compared with baseline values. Compared

with the baseline physical function score, the scores at all follow-up time points were lower.

However, by 24 months, the difference was smaller for the intervention group than for the

usual care group (P = 0.027). For the domain of social functioning, the scores improved by 24

months for the intervention group but not for the usual care group (P = 0.022). Subscales of

role limitations due to physical health, emotional problems, energy/fatigue, emotional well-

being, pain, and general health were similar between groups.

Prostate-Specific HRQoL

In Table 11, we present the results of analysis for prostate-specific HRQoL. For each

domain of the EPIC, we compared the proportion of participants “returning to baseline”

between intervention status and over time. We considered a participant as returning to his

baseline values if the score on that item/domain at follow-up was equal to or greater than the

baseline score. For the urinary irritation domain at 3-month follow-up, a higher proportion of

the usual care group had returned to baseline compared with the intervention group (56% vs

46%, respectively; P = 0.0328). However, by 24 months, 60% of participants in both groups had

returned to baseline values for this domain. For the bowel bother domain at 6 months, a higher

proportion of intervention group participants had returned to baseline compared with the

usual care group (76% vs 68%, respectively; P = 0.044). However, these proportions were

comparable at 24 months. For the urinary function domain at 24 months, a higher proportion

of intervention group participants had returned to baseline compared with the usual care group

(59% vs 50%, respectively), but the difference was not statistically significant (P = 0.071). For

the urinary incontinence domain at 24 months, a higher proportion of intervention group

participants had returned to baseline compared with the usual care group (56% vs 46%,

61

respectively; P = 0.041). The domains of urinary function and bother, bowel score and function,

sexual function and bother, and hormonal function and bother were similar between groups.

62

Table 10. Comparison of Generic HRQoL Scores Across Intervention and Usual Care Groups

Generic HRQoL (SF-36) Item

Intervention group Usual care group Test of difference between groups, P

value

Observed mean (SD)

Model estimate change from baseline, mean (SE)

Test of difference

over time, P value

Observed mean (SD)

Model estimate change from baseline, mean (SE)

Test of difference

over time, P value

Baseline (n = 274)

3 mo (n = 255)

6 mo (n = 261)

12 mo (n = 251)

24 mo (n = 249)

Baseline (n = 277)

3 mo (n = 254)

6 mo (n = 261)

12 mo (n = 253)

24 mo (n = 237)

Physical functioning 85.5 (20.2) –3.9 (1.4)

–4.4 (1.4)

–3.5 (1.3)

–0.13 (1.4)

0.0007 86.9 (20.4) –6.3 (1.3)

–1.9 (1.4)

–2.3 (1.3)

–2.9 (1.3)

0.0003 0.0279

Role limitations due to physical health

81.4 (33.3) –20.3 (3.1)

–4.6 (2.4)

–3.2 (2.2)

–4.7 (2.6)

<0.0001 82.9 (32.7) –24.2 (3.1)

–8.2 (2.4)

–6.2 (2.2)

–5.4 (2.5)

<0.0001 0.7768

Role limitations due to emotional problems

85.1 (30.2) –4.8 (2.6)

–1.1 (2.3)

–0.92 (2.3)

–0.92 (2.5)

0.4267 80.2 (35.0) –3.6 (2.5)

4.8 (2.3)

4.5 (2.3) 5.6 (2.4) 0.0009 0.2048

Energy/fatigue 64.0 (20.1) –3.8 (1.1)

–1.1 (0.98)

–0.52 (1.0)

–1.0 (1.1)

0.0065 65.3 (19.1) –3.8 (1.1)

–0.28 (0.9)

–1.1 (1.0)

–0.79 (1.1)

0.0047 0.8822

Emotional well-being 76.6 (17.3) 1.2 (0.9)

2.7 (0.8)

3.7 (0.9)

2.4 (0.9)

0.0002 77.1 (16.9) 1.3 (0.8)

1.7 (0.8)

1.8 (0.8) 2.3 (0.9) 0.1113 0.2610

Social functioning 84.2 (22.1) –7.2 (1.6)

0.58 (1.3)

1.1 (1.4)

6.5 (1.6)

<0.0001 85.5 (20.9) –8.5 (1.5)

0.58 (1.3)

1.1 (1.4) 0.51 (1.5)

<0.0001 0.0220

Pain 83.1 (20.4) –8.4 (1.6)

–2.2 (1.3)

–2.4 (1.3)

–5.7 (1.5)

<0.0001 82.6 (23.0) –7.5 (1.6)

–2.9 (1.3)

–2.8 (1.3)

–3.7 (1.4)

0.0002 0.6599

General health 70.1 (17.8) –0.53 (0.8)

–0.58 (0.8)

–1.3 (0.9)

–3.2 (0.9)

0.0145 71.9 (18.6) –0.95 (0.7)

–2.5 (0.8)

–2.0 (0.9)

–3.1 (0.9)

0.0065 0.4356

Physical health summary

79.9 (17.4) –8.0 (1.3)

–2.8 (1.0)

–2.4 (1.0)

–3.6 (1.2)

<0.0001 80.9 (19.7) –9.6 (1.3)

–3.7 (1.0)

–3.4 (0.99)

–3.9 (1.2)

<0.0001 0.9046

Mental health summary

77.4 (18.4) –3.5 (1.1)

–0.45 (1.0)

1.0 (1.1)

1.8 (1.2)

0.0001 77.1 (18.9) –3.6 (1.1)

1.4 (1.0)

0.81 (1.0)

1.5 (1.1) <0.0001 0.8937

Abbreviations: HRQoL, health-related quality of life; SF-36, Medical Outcome Study Short Form 36.

63

Table 11. Proportion Returning to Baseline Scores at 3, 6, 12, and 24 Months for Prostate-Specific HRQoL

Prostate-specific HRQoL (EPIC) individual Item

Proportion returning to baseline score, No. (%)

3 mo 6 mo 12 mo 24 mo

Intervention group

(n = 255)

Usual care

group (n = 254)

P value

Intervention group

(n = 261)

Usual care

group (n = 261)

P value

Intervention group

(n = 251)

Usual care

group (n = 253)

P value

Intervention group

(n = 249)

Usual care

group (n = 240)

P value

Urinary score 31.1 38.7 0.089 40.3 41.8 0.737 48.1 46.9 0.788 45.8 40.8 0.322

Urinary function 37.9 43.8 0.204 50.9 51.1 0.964 55.9 57.3 0.783 59.4 50.0 0.071

Urinary bother 40.6 45.7 0.284 50.4 50.0 0.924 53.7 55.4 0.726 48.2 46.2 0.691

Urinary incontinence

40.8 43.6 0.552 49.6 45.4 0.377 53.1 53.4 0.943 56.2 45.9 0.042

Urinary irritation 46.3 56.3 0.033 59.4 68.1 0.052 61.3 63.0 0.717 60.3 60.9 0.894

Bowel score 53.4 52.6 0.863 62.9 61.1 0.694 62.5 64.6 0.651 64.7 60.8 0.413

Bowel function 53.2 59.9 0.149 66.4 65.8 0.898 66.7 68.2 0.738 64.7 67.9 0.498

Bowel bother 64.4 61.3 0.499 76.3 68.1 0.044 69.8 76.5 0.114 70.9 69.4 0.772

Sexual sum 26.5 25.2 0.759 23.9 25.8 0.645 21.9 27.0 0.209 20.7 19.4 0.742

Sexual function 27.4 24.8 0.528 24.8 25.8 0.810 24.7 26.6 0.644 25.0 22.3 0.533

Sexual bother 55.4 51.8 0.451 45.9 44.4 0.732 33.7 36.5 0.531 29.1 28.9 0.968

Hormonal sum 54.4 54.8 0.917 50.2 51.4 0.779 58.9 57.9 0.832 62.0 57.2 0.334

Hormonal function 57.4 57.1 0.944 55.6 54.2 0.762 69.2 64.2 0.274 69.4 66.0 0.481

Hormonal bother 67.4 62.2 0.252 62.9 60.2 0.554 64.8 60.7 0.375 63.6 62.2 0.776

Abbreviations: EPIC, Expanded Prostate Cancer Index; HRQoL, health-related quality of life.

64

AUA-SI

In Table 12, we present the results of the analysis for AUA-SI. At baseline, a higher

proportion of intervention group participants reported severe urologic symptoms compared

with usual care group participants. However, by 24 months, the proportion of those with severe

urinary symptoms was lower in the intervention group than in the usual care group. The

comparison of AUA symptom categories across time and intervention status groups was

statistically significant (P < .0001).

Depression

A CES-D score of 0-14 is considered low depression, 15-21 moderate depression, and

>21 high depression. The proportion of participants with high depression was lower at baseline

for the intervention group than for the usual care group. As presented in Table 13, at 3- and 12-

month follow-up, both groups were comparable in terms of the proportions of participants with

high depression. However, at 6 months and 24 months, a lower proportion of intervention

group participants had high depression than did usual care participants. The overall comparison

of depression category across time and intervention status groups was statistically significant

(P < .0001).

65

Table 12. Comparison of 3 Categories of Urologic Symptoms at Baseline and at 3, 6, 12, and 24 Months Across Intervention and

Usual Care Groups Using AUA-SI

AUA symptom categorya

No. (%) P value

Baseline 3 mo 6 mo 12 mo 24 mo

Intervention

group (n = 274)

Usual care

group (n = 277)

Intervention

group (n = 255)

Usual care

group (n = 254)

Intervention

group (n = 261)

Usual care

group (n = 261)

Intervention

group (n = 251)

Usual care

group (n = 253)

Intervention

group (n = 249)

Usual care

group (n = 240)

Mild 149 (56.9)

144 (54.1)

102 (41.0)

107 (43.7)

149 (59.1)

128 (52.2)

136 (57.9)

136 (65.0)

157 (63.1)

150 (62.8)

<0.0001

Moderate 83 (31.7) 100 (37.6)

118 (47.8)

120 8.9) 90 (35.7) 101 (41.2)

91 (38.7) 75 (31.3) 82 (32.8) 76 (31.7)

Severe 30 (11.5) 22 (8.3) 27 (10.9) 18 (7.4) 13 (5.2) 16 (6.5) 8 (3.4) 9 (3.8) 10 (4.1) 13 (5.5)

Abbreviations: AUA, American Urological Association; AUA-SI, AUA Symptom Index. aAUA-SI scores are 1-7, mild; 8-19, moderate; and 20-35, severe.

66

Table 13. Comparison of 3 Categories of Depression at Baseline and at 3, 6, 12, and 24 Months Across Intervention and Usual Care

Groups Using CES-D

Depression categorya

No. (%)

P value

Baseline 3 mo 6 mo 12 mo 24 mo

Intervention group (n = 274)

Usual care group (n = 277)

Intervention group (n = 255)

Usual care group (n = 254)

Intervention group (n = 261)

Usual care group (n = 261)

Intervention group (n = 251)

Usual care group (n = 253)

Intervention group (n = 249)

Usual care group (n = 240)

Low 207 (75.8)

212 (77.4)

184 (73.0)

188 (74.6)

172 (66.7)

169 (66.3)

128 (51.2)

124 (49.4)

124 (49.8)

112 (47.0)

<0.0001 Moderate 42 (15.4) 36 (13.1) 43 (17.1) 40 (15.9) 66 (25.6) 54 (20.9) 86 (34.4) 91 (36.3) 92 (38.4) 91 (38.0)

High 24 (8.8) 26 (9.5) 25 (9.9) 24 (9.5) 20 (7.8) 36 (13.9) 36 (14.4) 36 (14.3) 28 (11.9) 36 (14.9)

Abbreviation: CES-D, Center for Epidemiologic Studies Depression Scale. aCES-D scores are 0-14, low; 15-21, moderate; and >21, high.

67

Utility Levels (Value Markers), Concordance, and Outcomes

In Table 6, we present the treatment attributes and average importance of the utilities

for the intervention group. As shown in Table 14, latent profile analysis of individual utilities

indicated 2 classes. For patient preference concordance, we analyzed 3 separate logistic

regression models. The dependent variable is the treatment, and the independent variables are

the utilities. Table 15 presents the results of logistic regression to study the association

between attributes and treatment type after adjusting for sociodemographic variables. We

observed that the attributes of survival (odds ratio [OR] = 1.20; 95% CI, 1.06-1.50) and change

in bowel function (OR = 1.18; 95% CI, 1.03-1.51) were associated with higher odds of radiation

treatment, whereas adverse effects were associated with lower odds of radiation treatment

(OR = 0.71; 95% CI, 0.54-0.95). The attributes of survival (OR = 1.11; 95% CI, 1.06-1.28), and

cancer control (OR = 1.16; 95% CI, 1.00-1.34) were associated with higher odds of surgery

treatment. On the other hand, attributes of change in sexual function (OR = 0.93; 95% CI, 0.80-

0.99), psychological distress (OR = 0.90; 95% CI, 0.78-0.99), and needs for cutting (OR = 0.88;

95% CI, 0.77-0.99) were associated with lower odds of surgery treatment. Among low-risk

prostate cancer patients, attributes of sexual function (OR = 1.46; 95% CI, 1.04-2.06), need for

cutting (OR = 1.54; 95% CI, 1.06-2.24), and recovery time (OR = 1.43; 95% CI, 1.02-1.99) were

associated with being on active surveillance. On the other hand, the attribute of survival

(OR = 0.67; 95% CI, 0.48-0.94) was associated with lower odds of being on active surveillance.

The attributes of cancer recurrence, change in urinary function, treatment duration, radiation,

out-of-pocket cost, and caregiver burden did not exhibit an association with treatment type.

68

Table 14. Latent Profile Analysis of Individual Utilities for the Intervention Group (n = 312)

Attribute Mean utility Class 1 (52.2%) estimate (SE)

Class 2 (47.8%) estimate (SE)

Survival

Many (85%) –53.76923

Most (95%) 3.11486 0.043 (0.017) 0.006 (0.021)

Almost all (98%) 50.65437 0.393 (0.019) 0.402 (0.018)

Recurrence

10% 63.41151

20% –0.50867 0 (0.013) –0.004 (0.015)

30% –62.90284 –0.505 (0.018) –0.471 (0.017)

Urinary problems

20%/10% 58.35360

30%/20% 0.66223 –0.039 (0.023) 0.058 (0.02)

60%/40% –59.01583 –0.378 (0.039) –0.547 (0.023)

Sexual problems

20%/10% 50.77480

30%/20% 3.46070 0.013 (0.011) 0.046 (0.012)

60%/40% –54.23550 –0.377 (0.026) –0.469 (0.021)

Bowel problems

10%/5% 61.42767

30%/15% 0.84279 0.004 (0.01) 0.013 (0.011)

50%/30% –62.27046 –0.438 (0.03) –0.533 (0.018)

Psychological distress

10% 44.86592

20% –0.02403 0.002 (0.011) 0.001 (0.012)

30% –44.84189 –0.344 (0.018) –0.354 (0.022)

Adverse effects

10%/10% 54.29945

69

Attribute Mean utility Class 1 (52.2%) estimate (SE)

Class 2 (47.8%) estimate (SE)

20%/30% –2.79476 –0.03 (0.013) –0.009 (0.019)

30%/40% –51.50469 –0.341 (0.015) –0.464 (0.038)

Treatment length

2 d 39.66939

4 d 1.88438 0.013 (0.014) 0.021 (0.015)

6 mo –41.55376 –0.347 (0.018) –0.297 (0.026)

Surgery

None 43.00122

Minimal 3.89751 0.036 (0.013) 0.028 (0.013)

Significant –46.89873 –0.396 (0.021) –0.33 (0.021)

Radiation

None 48.14221

Moderate –0.47731 –0.01 (0.014) 0.007 (0.016)

Extensive –47.66490 –0.368 (0.02) –0.372 (0.019)

Recovery

3 mo 48.67195

6 mo 1.48437 0.013 (0.017) 0.013 (0.017)

24 mo –50.15633 –0.399 (0.021) –0.38 (0.022)

Control

Monitoring –45.16591

Complete 45.16591 0.371 (0.021) 0.337 (0.017)

Expense

$50 37.71223

$500 3.02089 0.041 (0.015) 0.007 (0.018)

$5000 –40.73312 –0.384 (0.025) –0.242(0.043)

Caregiver burden

1 h 40.20699

70

Attribute Mean utility Class 1 (52.2%) estimate (SE)

Class 2 (47.8%) estimate (SE)

2 h 2.84679 0.004 (0.014) 0.045 (0.015)

4 h –43.05378 –0.341 (0.016) –0.327 (0.018)

Level of difficulty

Not difficult 47.80225

Somewhat difficult –1.01426 –0.012 (0.011) 0.001 (0.01)

Very difficult –46.78799 –0.383 (0.017) –0.342 (0.019)

Table 15. Association between treatments received and attributes of the PreProCare Tool for

intervention group, after adjusting for sociodemographic and clinical characteristics (n = 312)

Attribute Treatment type, OR (95% CI)

Radiation Surgery Active surveillance

Survival 1.20 (1.06-1.50) 1.11 (1.06-1.28) 0.67 (0.48-0.94)

Cancer recurrence or progression

0.90 (0.70-1.16) 0.99 (0.86-1.15) 1.02 (0.75-1.38)

Change in urinary function 1.07 (0.85-1.36) 0.98 (0.85-1.15) 1.11 (0.77-1.60)

Change in bowel function 1.18 (1.03-1.51) 0.95 (0.82-1.11) 1.09 (0.75-1.58)

Change in sexual function 0.95 (0.75-1.19) 0.93 (0.80-0.99) 1.46 (1.04-2.06)

Psychological distress 1.22 (1.09-1.56) 0.90 (0.78-0.99) 0.88 (0.63-1.23)

Adverse effects 0.71 (0.54-0.95) 0.99 (0.85-1.16) 0.99 (0.67-1.47)

Treatment duration 0.87 (0.66-1.16) 0.98 (0.83-1.15) 1.11 (0.78-1.58)

Need for cutting 1.05 (0.84-1.31) 0.88 (0.77-0.99) 1.54 (1.06-2.24)

Radiation or seed implants 0.86 (0.67-1.10) 1.01 (0.88-1.17) 1.10 (0.80-1.51)

Recovery time 0.98 (0.76-1.27) 0.98 (0.85-1.15) 1.43 (1.02-1.99)

Cancer control 0.90 (0.71-1.14) 1.16 (1.00-1.34) 1.10 (0.81-1.51)

Out-of-pocket expenses during treatment year

1.12 (0.89-1.38) 0.98 (0.86-1.13) 1.03 (0.77-1.37)

Caregiver burden 0.84 (0.64-1.11) 1.03 (0.88-1.21) 1.09 (0.77-1.55)

Abbreviations: OR, odds ratio.

71

DISCUSSION

Context for the Study Results

In this first-of-its-kind, large multicenter RCT, the intervention of PreProCare was

associated with improved long-term (24-month) satisfaction with care, satisfaction with

decision, reduced regrets, improved alignment of treatment choice with prostate cancer risk

category, lowered depression and severe urinary symptoms, and improved domains of generic

and prostate-specific HRQoL among men with localized prostate cancer. Patient satisfaction

with care has emerged as an important quality-of-care measure associated with process of care

and outcomes.180 Consistent with our hypothesis, we observed improved satisfaction with care

in the intervention group. Treatment of localized prostate cancer causes adverse effects that

can affect a patient’s satisfaction with care and treatment choice regret. Thus, as part of

patient-centered care, it is important for a patient to understand his own preferences while

evaluating treatment modalities.181,182 Our study is notable for the association of preference

assessment intervention with treatment choice, whereas most previous trials have not shown

this effect.183 Our study is rigorous in its measurements along the spectrum of patient-reported

outcomes. Additionally, we were able to achieve a good retention rate of 75% at 24 months.

Higher satisfaction with treatment decision has been associated with improved

posttreatment HRQoL.184 This finding emphasizes the importance of the decision-making

process for patients and providers. We observed significant improvement in satisfaction with

decision in our intervention group at the 24-month follow-up compared with the usual care

group. Additionally, a higher proportion of the PreProCare tool intervention group reported

reduced decision regret by 24 months. Patients often find it confusing to sort out the wealth of

information regarding treatment options, which can lead to difficulties in decision-making and

affect the patient centeredness of care.36,57,181,182 A recent study observed that in prostate

cancer patients, preference assessment intervention reduced decision conflict immediately

after cancer consultation.185

Shared decision-making is a collaborative process that allows patients and providers to

make health care decisions together, taking into account the best scientific evidence available

72

and the patients’ values and preferences.186-188 The significance of patients’ preferences for

decision-making is highlighted by the definition of a “high-quality decision” as one that is

consistent with a patient’s underlying values and preferences.10,186,189 Patients with localized

prostate cancer have health-related preferences that go beyond cancer cure. Thus, patient

involvement, as reflected in patient-centered decision-making, is highly relevant to localized

prostate cancer care. Although clinicians believe that they consider patient preferences, they

may often be indifferent about these preferences.190 Physician recommendations for

treatments are strong predictors of treatment choice, so it is important to understand how well

physicians’ views of preferences actually reflect patients’ preferences.188,191-193 The goal of our

web-based preference assessment tool, PreProCare, was to help patients with localized

prostate cancer understand their preferences and thus facilitate an informed treatment

decision.

Our study is also novel in its approach to the development of the PreProCare tool for

preference assessment. We used a comprehensive approach consisting of extensive systematic

literature review, one-on-one patient interviews, and provider focus groups to identify the

attributes that are important for decision-making. Our patient-centered approach also engaged

key stakeholders in the development of our PreProCare tool.

Generalizability of the Findings

Our study cohort consisted of patients with localized prostate cancer in academic-based

clinical settings. However, we feel that it is possible to develop preference assessments and

interventions based on preference assessments similar to ours for other preference-sensitive

cancers in various settings and subpopulations.

Implementation of the Study Results

Unlike other prostate cancer treatment decision aids that discuss the alternatives, risks,

and benefits of different treatments, our preference assessment PreProCare tool is unique in

that it assists a patient in identifying attributes that are important to him. We believe that this

tool was effective because it might have helped facilitate patient-centered treatment decision

73

discussions with providers that focused on patients’ specific preferences. Improving the quality

of discussion between a patient and provider is important because for a majority of prostate

cancer patients, their physician’s recommendation was the most important factor in their

treatment choice.181,182,194,195 This is appropriate if the physician is an efficient agent for the

patient, that is, they make the decision the patient would if the patient had the physician’s

medical knowledge. The physician agency model presupposes that the physician understands

the patient’s preferences and values. However, patient and physician beliefs differ regarding

conceptualization of the illness and assessment of treatments.36,57,181,182 Despite making sincere

efforts toward shared decision-making, physicians may face difficulties in communicating

appropriate information to patients, overlook the issue of emotions that affect a patient’s

participation in decision-making, and overburden patients with extraneous information.196

Thus, the PreProCare tool has the potential to address this challenge and facilitate a dialogue

with the physician to enhance shared decision-making. There are several potential ways to

implement our PreProCare tool in a clinical setting. The implementation of PreProCare into the

workflow will be greatly facilitated by attention to the following: training of physicians and

office staff, time and mode of delivery of the tool, and sharing and interpretation of results.

Both the physicians and practice staff can undergo training to familiarize themselves with the

tool. Next, the tool can be made available to the patient before or during the visit. For example,

the tool can be made available via a patient portal, and the patient can be directed to complete

it before their visit. Alternatively, the patient can complete the assessment in the waiting room.

The results can be shared either by printing them or by integrating the assessment with the

patient’s electronic medical record. Finally, with minimum training, physicians should be able to

understand and interpret the findings of the PreProCare tool and advance patient-centered

treatment decision-making.

Research indicates that decision aid intervention for localized prostate cancer can

reduce decision conflict and improve elements of shared decision-making, patient knowledge,

and satisfaction with decision.197-202 At the same time, a systematic review and meta-analysis of

RCTs for localized prostate cancer decision aids highlight some of the challenges of these

studies.202 Incorporating a patient-centered clinical decision-making process in a real-world

74

clinical setting is a daunting task; it requires the decision tools to quantify the degree of patient

centeredness based on decision-specific knowledge and the extent to which a patient’s values

and preferences are integrated. Thus, the PreProCare tool offers an opportunity to quantify

treatment preferences of patients with localized prostate cancer in a clinical setting.

Subpopulation Considerations

Among our study participants with low-risk prostate cancer, those in the intervention

group were more likely to be on active surveillance. This finding is important for several

reasons. For low-risk prostate cancer patients, active surveillance demonstrated similar survival

rates compared with definitive therapy 203,204 and had better quality-adjusted life expectancy.205

Active surveillance is associated with lower rates of adverse effects than active therapy206 and is

increasingly incorporated into clinical practice as a clinically acceptable option for the

management of low-risk prostate cancer.207,208 Before making a decision to proceed with active

surveillance, a careful discussion of the risks and benefits of active treatment, as well as the

risks of untreated cancer and any necessary follow-up, must take place. In our study it is

possible that after undergoing the preference elucidation process, patients were more

prepared to discuss their concerns about treatment-related adverse effects with their

physicians, which might have ultimately led them to pursue active surveillance.

Study Limitations

We would like to note some limitations to our study. The PreProCare tool–based values

clarification exercise is limited by the attributes selected. Determining the most appropriate

way to integrate decision aids into the fast-paced nature of clinical decision-making is an area in

need of further research. For the intervention group participants, we did not measure the

quality and quantity of patient-physician interactions postintervention; such interactions are a

direct measure of adherence to intervention that can help us understand the dynamics of

patient-physician interaction leading to decision-making. Additionally, the physicians did not

receive formal training to incorporate the results of the preference assessment in treatment

discussions. Formal training may improve the quality of physician-patient interaction and

further enhance the outcomes. All of our study sites are urban academic institutions. We did

75

not control for the additional time and attention to preferences in care between the

intervention and usual care groups. Also, we did not obtain information about the standard

workflow or practices, details of physician-level information, and shared decision-making

practice at our study sites. Most of the participants in our RCT were married and were college

graduates, and almost two-thirds had an annual household income of $75 000 or higher. The

study attrition rate was 24%. Thus, to enhance the generalizability of the findings, we need

future studies in diverse groups of patients and clinical settings with additional training on how

to interpret the results of the preference assessment.

Future Research

Despite these limitations, our study has several strengths. This study is the first large-

scale multicenter RCT of preference assessment intervention among patients with localized

prostate cancer using a comprehensive intervention tool, PreProCare, with long-term outcome

assessment. To facilitate patient-centered care, future research should focus on multilevel

intervention to train providers and patients for effective implementation of preference

assessment intervention in real-world clinical settings, either primary care or urologic.

76

CONCLUSIONS

Preference assessment is the cornerstone of patient-centered care and has been

universally accepted as a method to improve the quality of patient care.209 However, evidence

that preference assessment itself improves patient-centered outcomes and treatment choice is

lacking.209,210 In our novel patient-centered RCT of more than 700 patients with localized

prostate cancer, we observed that our preference assessment intervention, the PreProCare

tool, was associated with improved satisfaction with care, increased decision satisfaction, lower

regrets, improved alignment of treatment choice with prostate cancer risk, clearly stated

values/preferences for the outcomes that might be experienced, lowered depression and

severe urinary symptoms, and improvement in some domains of generic and prostate-specific

HRQoL. Our study is the first to analyze the association between conjoint analysis-value

assessment intervention and outcomes and determined (1) the comparative effectiveness of

preference assessment intervention on treatment choice outcomes vs usual care; (2) the

importance of an assessment of value markers in patient-centered care; and (3) the effects of

concordance between value markers and treatment choice on outcomes. Our study

demonstrated that in localized prostate cancer, helping patients identify their own preferences

using a structured, standardized computer-based preference assessment tool might be a

mechanism for enhancing patient-centered decision-making and outcomes.

77

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191. Ramsey SD, Zeliadt SB, Fedorenko CR, et al. Patient preferences and urologist recommendations among local-stage prostate cancer patients who present for initial consultation and second opinions. World J Urol. 2011;29:3-9.

192. van Tol-Geerdink JJ, Leer JW, Weijerman PC. Choice between prostatectomy and radiotherapy when men are eligible for both: a randomized controlled trial of usual care vs decision aid. BJUI. 2012;111:564-573.

193. Aning JJ, Wassersug RJ, Goldenberg SL. Patient preference and the impact of decision-making aids on prostate cancer treatment choices and post-intervention regret. Curr Oncol 2012;19:S37-44.

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Jayadevappa R, Cook R, Chhatre S. Minimal important difference to infer changes in health-related quality of life-a systematic review. J Clin Epidemiol. 2017;89:188-198.

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ACKNOWLEDGMENTS

We thank the patient and provider members of the study advisory group. We also thank

all study participants.

The Patient-Centered Outcomes Research Institute played no role in the design and

conduct of the study; collection, management, analysis, and interpretation of the data; or in the

preparation, review, approval, or publications.

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APPENDIX

Treatment Preference and Patient Centered Prostate Cancer Care

Focus Group/Interview Guide

This interview is about your experiences with prostate cancer and its treatment. We are especially interested in learning about how men make decisions about which treatment they will use. We are interested in learning which aspects (or attributes) of prostate cancer treatment you feel are most important and want to share them with other men making decisions about treatment. Since you have actually been in this position, you are an expert and we would like to know what you think.

1) First, I’d like to ask you about how things have unfolded with your prostate cancer since you were first diagnosed. Would you please tell me about the events that led up to your diagnosis and treatment including recurrences?

a. What treatment did you receive for your prostate cancer and when did you receive this treatment (month and year).

2) When you were first diagnosed with prostate cancer, how did you learn about the different treatment options?

a. What are the different treatments you heard about? Who told you about them? b. What do you remember about what your doctor said about the treatment

choices you had?

3) What things did you consider when making your decision? a. How did the potential physical side-effects of each treatment influence your

decision? b. Where did you learn about the side-effects of the different treatments?

4) Who did you talk to about your options?

a. When you talked with others about your options, what kinds of things did you talk about?

b. Why did you turn to that person for help? c. How did you feel about the advice you received? d. How did talking with someone about your choices affect the decision you made?

5) What other types of resources did you use to learn about prostate cancer and its

treatment? a. What do you think about these sources of information?

6) What do you know now about prostate cancer, its treatment, and treatment side-effects that you wish you knew before you made your decision?

a. With any treatment, things may come up that you don’t expect. Looking back,

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how well do you think you understood the treatment you received before you started treatment? What didn’t you understand about it, that you now know?

7) What would you want to tell someone who is trying to choose a treatment?

8) Can you please list the advantages of the treatment that you received?

1

2

3

4

5

9) Can you please list the disadvantages of the treatment that you received?

1

2

3

4

5

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Survey I This survey is about how and where you obtained information about options for prostate cancer treatment and decision making. 1. After being diagnosed with prostate cancer, how important were the following resources for you to learn about prostate cancer treatment?

1

Most

important

2 3 4 5

Least

important

Television

Internet

Pamphlet from doctor's office

Website such as National Cancer Institute,

American Cancer Society, and American

Urologic Association

Other patients

Friends with prostate cancer

Discussions with my spouse/partner

Other (Please list)

2. After being diagnosed with prostate cancer, how helpful were the following resource(s) to you in making a decision about treatment? 1

Most

helpful

2 3 4 5

Least

helpful

Television

Internet

Pamphlet from doctor's office

Website such as National Cancer

Institute, American Cancer Society,

and American Urologic

Association

Other patients

Friends with prostate cancer

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Discussions with my

spouse/partner

Other (Please list)

3) Who was most helpful in communicating with you about your treatment options? 1

Most

helpful

2 3 4 5

Least

helpful

Urologist

Urologist oncologist

Radiation/Radiation oncologist

Oncologist

Primary physician/family

physician/Geriatrician

Other (Please list)

4) Who was most helpful to you in making a decision? 1

Most

helpful

2 3 4 5

Least

helpful

Urologist

Urologist oncologist

Radiation/Radiation oncologist

Oncologist

Primary physician/family

physician/Geriatrician

Other (Please list)

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5) With any treatment, things may come up that you don’t expect. Looking back, how well do you think you understood the treatment you received before you started treatment? (circle the best answer)

▪ I understood it very well ▪ Pretty well ▪ Not so well ▪ I did not understand some of it ▪ I did not understand it at all

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Survey II Below are some of the aspects of treatment that other patients have found to be important in making a treatment decision for prostate cancer. Please rank each that was most important (1) to not at all important to you (5) in choosing your treatment.

1

Most

important

2 3 4 5

Not at all

important

The likelihood of developing impotence

The likelihood of developing incontinence

The likelihood of developing impaired bowel

function

The likelihood of recurrence of the cancer

What other men like me choose for treatment

What my doctor recommends for treatment

The number of treatment sessions I had to have

The complications of the treatment (e.g.

bleeding for surgery)

Length of recovery period

Time off from work

Insurance coverage

Out of pocket expenses

Travel

Burden on spouse/caregivers

Other (Please List)

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Urologist/ Radiation Oncologist/ Oncologist Focus Group Interview guide Preamble: Thank you for joining us today. We appreciate your taking time out of your busy schedules to talk with us today. The aim of this focus group is to understand your perspectives as physicians caring for men with newly diagnosed, early and localized prostate cancer. We are in the process of developing a treatment decision making tool that could be used by patients and discussed with their physicians. Specifically, we are interested in finding out what you think is important for men to know about the risks and benefits of different treatment options. We’d like to start with asking you about the kind of conversations you have with patients and their families when they first come to see you.

1. What do you think the goal of the first visit with a patient and his family should be? 2. What have you found most helpful in talking with patients about their options? Prompt:

do you use handouts? Do you recommend websites? Do patients typically come in with questions of their own?

3. How do you usually discuss treatment options with patients? 4. What kind of questions are patients most focused on? 5. In your opinion, where do most patients get their information about prostate cancer

and it’s treatment? 6. Who do patients most often involve in making choices about treatments? 7. How do you involve your patients’ spouses or partners in discussions about prostate

cancer treatment options. 8. When do patients want you to make the decision? 9. When do you tell patients about all the different treatment options available 10. When do you tell patient only about some of the treatment options? 11. How do you decide which treatment options to discuss?

i. Prompt: e.g. is it based on the patient’s symptoms? ii. Prompt: e.g. is it based on the patient’s preferences or values?

12. What is the most important thing you think your patients ought to know before coming to see you?

Now I’d like to you focus on the specific treatment options you may discuss with your patients

13. How do you talk to your patients about what to expect with surgical interventions? a. How do you discuss the risks and benefits of surgery?

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b. In your opinion, what do patients typically know the least about? Know the most about?

c. In your opinion, what do patients need the most help understanding about surgical options

14. What about radiation treatment? How do you discuss the risks and benefits of radiation treatments?

a. In your opinion, what do patients typically know the least about? Know the most about?

b. In your opinion, what do patients need the most help understanding about surgical options

15. Now I’d like you to think about medical or hormonal treatment. How do you discuss the risks and benefits of medical treamtent?

a. In your opinion, what do patients typically know the least about? Know the most about?

b. In your opinion, what do patients need the most help understanding about surgical options

16. And finally, what about active surveillance and watchful waiting?

Finally, I’d like to ask your opinion about research related to patients emotional and relational needs with respect to prostate cancer.

a. How do you talk to patients about issues such as self-esteem and relationships? Are there any other things we haven’t covered that you’d like to add about early localized prostate cancer, decision making or treatment options?

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Copyright © 2020. University of Pennsylvania. All Rights Reserved.

Disclaimer:

The [views, statements, opinions] presented in this report are solely the

responsibility of the author(s) and do not necessarily represent the views of the

Patient-Centered Outcomes Research Institute® (PCORI®), its Board of Governors

or Methodology Committee.

Acknowledgment:

Research reported in this report was funded through a Patient-Centered Outcomes

Research Institute® (PCORI®) Award (#CE-12-11-4973). Further information

available at: https://www.pcori.org/research-results/2013/helping-men-prostate-

cancer-determine-their-preferences-treatment