Intervention research

Contents

• Definition of intervention research• Characteristics of intervention research• Analyses• Exercise• Reporting• Summary

Intervention research

Quantitative measurement of effects of therapy or preventive measures

Experimental: investigator determines who is treated, not the treating physician

Example: Sehat®

Sehat®: new blood pressure drug

1st experiment Ny. Ani with high blood pressure

Intervention: 6 weeks sehat®

Outcome: blood pressure

Weekly measured systolic blood pressure of Ny. Ani using Sehat®

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Learn from single observation or ‘experience’

“For certain patients the blood pressure will decrease after using the drug”

What reasons can you think of that explain Ny. Ani’s decrease in blood pressure?

Learn from single observation or ‘experience’

Explanations for the observed effect:

- Regression to the mean

- Natural course / prognosis of disease

- External effects

- Measurement error

- True effect drug

Regression to the mean

Quartiles systolic blood pressure

1st measurement

2nd measurement

• Centripetal movement of data in successive measurements

• Effect of variability

• “the Doctor’s friend”

Solutions:

• measure more often

• control group

Natural course / prognosis of disease

Independent of treatment, blood pressure can change over time and this change can differ between people

External effects

Only interest: effect of Sehat®

Effects of other factors can influence the measurement of the effect of Sehat® in two ways:

-“placebo” effects

- induced effects

Induced external effects

Behavioral changes as effect of treatment of high blood pressure with Sehat®, e.g. eating and drinking pattern, physical activity, etc.

Observation errors (“information bias”)

Observer effects

• Patients, treating physicians, manufacturer can have expectations for the effect of Sehat®

• These expectations can influence, for example the reporting of patients or the measurements made by treating physicians

Result: measurement error

Learn from single observation or ‘experience’

Quantitative measurement of the effect of Sehat® can be distorted (confounded) because of :

• Natural course / regression to the mean (NC)• External effects (EE)• Observation errors (Information Bias) (IB)

Weekly measured systolic blood pressure of Ny. Ani using Sehat®

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140

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170

Observed effect

Components of the observed effect

• Observed effect (OE) =

Drug effect (Rx) +

Natural course (NC) +

External effects (EE) +

Observation errors (Information Bias) (IB)

General: only interest in Rx

How do we distinguish RX effects from confounding effects?

We ‘control’ the experiment

Comparison:

Ny. Ani (green) with Sehat®,

Ny. Sri (pink) without Sehat®

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RX?

Controlled study

Index (drug treatment):

OEi = Rx + NCi + EEi + IBi

Reference group (no treatment):

OEr = NCr + EEr + IBr

Therapeutic drug effect

• OEi - OEr =

Rx + (NCi - NCr) + (EEi - EEr) + (IBi - IBr)

• So, OEi - OEr = Rx

• If, NCi = NCr and EEi = EEr and IBi = IBr

Validity

Essence: validity in experimental research is assessed through comparability of groups

The basis of an experiment’s design is the prevention of non-comparibility

Comparability of natural course

= comparability populations = comparability prognosis

What could we do to assure comparability of the natural course?

Sleepy?

How about some coffee?

Clinical trial:

“The effect of coffee to daytime drowsiness”

Now open your envelope!

coffee no coffee

male 25 19

Live with parents 21 17

First child 16 19

High school in Jakarta 22 19

Comparability of natural course

Options:

- Selection or matching

- Measure prognostic variables at baseline and control for these during analysis

- Randomisation - paradigm for comparative research since 1948

Aim of randomization

To ensure that the groups to be compared have the same average baseline probability of change in blood pressure (prognosis, natural course)

To make the index and reference groups comparable for all known and unknown factors that may influence blood pressure

Randomized trial Table 1. Baseline characteristics at randomization

Sehat®

YES

Ny. Ani

NO

Ny. Sri

Age (years) 41 57

BMI (kg/m2) 24,6 32,3

SBP (mmHg) 160 160

Randomized trial:

Ny. Ani (green) with Sehat®,

Ny. Sri (pink) without Sehat®

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RX?

Randomized trial Table 1. Baseline characteristics at randomization

Sehat®

YES

N = 5,000

NO

N = 5,000

Age (years) 52,3 52,4

BMI (kg/m2) 25,7 25,6

SBP (mmHg) 160 160

Randomized trial:

5000 women (green) with Sehat®,

5000 women (pink) without Sehat®

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RX?

Comparability of external effects (EEi=EEr)

What could we do to assure comparability of external effects?

Comparability of external effects (EEi=EEr)

Options:

- Randomize

- Placebo or simulated treatment in the reference group

- Blinding

Comparability of observations (IBi = IBr)

What could we do to assure comparability for the observations (=no observation errors)?

Comparability observation (IBi = IBr)

Options:- Use protocols, systematics- Placebo

- Blinding (single, double, triple)

Comparability observation (IBi = IBr)

Need to blind depends on the interpretability of the studied endpoint:

- death- myocardial infarction- angina pectoris- blood glucose- quality of life

Measurement Bias -minimizing differential error

• Blinding – Who?– Participants?– Investigators?– Outcome assessors?– Analysts?

• Most important to use "blinded" outcome assessors when outcome is not objective!

• Papers should report WHO was blinded and HOW it was done

•Schulz and Grimes. Lancet, 2002

Placebo effectTrial in patients with chronic severe itching

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Itching score•Cyproheptadine• HCL

•Trimeprazine• tartrate

•No treatment

•Treatment vs no treatment for itching

Placebo effectTrial in patients with chronic severe itching

0

10

20

30

40

50

60

Itching score•Cyproheptadine• HCL

•Trimeprazine• tartrate

•Placebo

•No treatment

•Treatment vs no treatment vs placebo for itching•Placebo effect - attributable to the expectation that

•the treatment will have an effect

Randomized triple blind placebo controlled trial Table 1. Baseline characteristics at randomization

Sehat®

BUGAR®

N = 5,000

PLACEBO

N = 5,000

Age (years) 52,3 52,4

BMI (kg/m2) 25,7 25,6

SBP (mmHg) 160 160

Randomized triple blind placebo controlled trial: 5000 women (green) Sehat BUGAR®,

5000 women (pink) Sehat PLACEBO®

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RX?

Need of comparability

Natural course/prognosis: always

External effects: depends on aim research: “explanatory” vs. pragmatic

Observation errors: depends on endpoint

Randomize Blind Placebo NC + EE + + (patient) + IB + (investigator) +

Randomized double blind controlled trial

Intervention: and then

• Different aims: explanatory vs pragmatic• Analysis• Loss-to follow-up• Choice of study endpoints• Disadvantages• Alternatives for experimental research• Size of trials• Reporting

Aims of intervention

Explanatory

Interest in a single aspect of high blood pressure treatment, by Sehat®

Pragmatic

Interest in strategy (procedure with all that belongs to it) of high blood pressure treatment, e.g. combination of drugs with living rules and weight loss, including induced effects

Analysis randomized research

Randomisation is a powerful way to solve the problem of differences in the natural course:

This principle should not be undone in the analysis!

“Intention to treat” analysis

Once a member of the cohort, always a member of the cohort

contrary to

Analysis of only those patients who really received the treatment (‘per treatment’ or ‘per protocol’ analysis).

Problem: loss to follow-up

Loss to follow-up: what is the problem?

People stop treatment for a reason– Treatment does work or does not– People are ill or are not

Reasons can be related to the occurrence relation: drug and outcome

Problem: we do not know why people stop

Result: bias?

Outcomes and endpoints

• Intuitive preference for “hard” clinical measures, but:Growing realization of importance of patient preference in assessment of choices

• Often unclear choice of endpoints• Often unclear validity of chosen endpoints

Exercise intervention(open your exercise book!)

Question 1

Do children of mothers from high risk-families (patient/domain) have a lower 2-year risk of atopic diseases (outcome) if they are exposed, before and after the pregnancy, to probiotics (intervention/determinant) than to placebo (comparison)?

Question 2

Somewhat more atopy and smoking in placebo families, a somewhat more higher incidence of pets and detectable IgE in Lactobacillus, but as a whole reasonably comparable

Question 3 and 4

2-year risk of atopy in Lactobacillus group

15 / 64 = 23%

2-year risk of atopy in placebo group

31 / 68 = 46%

Question 5

RR = = 0.5115 / 64

31 / 68

Question 6

Eln0.51 ± 1.96√[49/15*64 + 37/31*68]

95% CI = 0.31 to 0.85

Question 7

Confidence interval tells something about the precision of the effect estimate

Question 8

Fairly strong protective effect of Lactobacillus treatment against developing atopy

Complete explanation of effect by baseline differences or differential loss to follow-up very unlikely

Question 9

Pre- and postnatal use of Lactobacillus in high risk children seems to prevent the development of early atopy

Disadvantages of trials

Limits to generalisability

Selection of the study population

Budget

RCT is expensive

Takes long

RCT is prospective

Number of patients

Ethical dilemma’s (a.o. equipoise)

Alternative: comparative non-experimental research

• Cohort studies / Case control studies• Not inherently less valid, but much more difficult

to design and conduct and therefore much more sensitive to bias

• In comparative non-experimental research exists a large probability of non-comparibility of especially those three components that are solved so well in an RCT

Confounding by indication

The prognosis influences the probability to be assigned a certain intervention

E.g. -observational studies on the effectivity of vaccinations

- observational study on the effect ofantihypertensives

Confounding by indication

Confounding by indication: research on the effect of anti-hypertensives among 793 Dutch hypertensive women, who were followed for over 10 years

Crude and adjusted rate ratios for fatal cardiovascular diseases in treated women compared with non-treated women

Confounding by indication

RR cardio-vascular mortality 95% CI

Crude 1.0 0.6 TO 1.5

Adjusted* 0.6 0.3 TO 0.9

* For age, Quetelet index, hart frequency, smoking habits, serum cholesterol, diabetes, previous myocardial infarction or stroke

Reporting randomized trials

• Table 1: prognostic factors in index and reference group (see exercise)– Show whether randomization succeeded

• Table 2: shows intervention effects– Difference in group averages, difference in

group proportions– Relative risk (reduction), risk difference,

NNT

Reporting: flow-chart

Conclusions

• To evaluate the effects of therapy a comparison is necessary

• In trials, very effective methods have been developed to enhance the comparability of the natural course, external effects and information

randomisation, blinding and placebo• The concepts and principles of a trial are a model

for non-experimental research

Thank you