Monitoring Entry, Retention,

and ART Adherence

Robert Gross, MD MSCEAssociate Professor of

Medicine (ID) and EpidemiologyUniversity of Pennsylvania

Perelman School of Medicine

PennInfectious Diseases

CCEB

Monitoring Overview• Most research on adherence• Entry and retention have

emerged as highly important–Less data available on “how to”–More local logistics come into play

• Overarching message–“Monitoring provides key data on

which patients need interventions”

Entry Monitoring• Entry into care shortly after dx

associated with survival• Monitoring challenge

–Multiple sources of data (e.g., dedicated testing sites, clinics)

–Responsible parties need to be identified and logistics arranged

Retention Monitoring• Retention has multiple benefits

–Decreased morbidity/mortality–Decreased community viral load

• Various metrics used–Visit adherence, gaps in care, visits

per time frame• Logistics easier than for entry

–Use medical records and admin data–May require integration of sources

Adherence Vignette• 45 y.o. HIV infected man

–Philadelphia VAMC–Serial monoRx in 90s, then HAART–Excellent adherence, but multiple

resistance mutations acquired–CD4=0 (0%) x 3 years

• New regimen–DRV/r in combination therapy–HIV-1 RNA <50 c/ml, CD4~300 cells/mm3

Why Monitor?• Follow-up visit

–HIV-1 RNA<50 copies/ml –Queried re: adherence as always–Had stopped meds entirely for 3 wks!–New onset depression–Depression/non-adherence overcome–Resumed adherence and no

subsequent virologic failure

Need for Continued Monitoring• Can detect impending failure

– Irrespective of viral load monitoring (e.g., Bisson G, Gross R et al. PLoS Med 2008)

• Intervention before failure• Same principles likely for

entry and retention in care

False Security of RNA Suppression

• ATH02 study–Observational–EFV-based regimen–HIV-1 RNA<75 copies/ml–Monitored RNA monthly–MEMS for adherence monitoring–Follow until breakthrough or 1 year

Gross R et al, HIV Clinical Trials, 2008

Timing of Adherence and Outcome

time

event or censor date

time shift

Adherence interval without time shift

Adherence interval with time shift

Time Shift Prior to Event Date

VL<1000

n=109

VL>1000

n=7

p value

0 days 96% (83-100%) 38% (12-100%) 0.03

30 days 96% (86-100%) 63% (24-100%) 0.08

60 days 96% (87-100%) 71% (42-96%) 0.04

90 days 95% (86-100%) 57% (51-72%) 0.008

Timing of Non-Adherence

Monitoring Recommendation

s

• Assess adherence each visit–Self-report–Pharmacy refill data (MPR)–Do not recommend microelectronic

monitors at this time–Do not recommend drug

concentrations at this time–Do not recommend routine pill

counts

Self-Reports• Must use non-judgmental tone

–Preamble admitting perfect adherence unrealistic, but desired

–Allow for honesty• Specify time period of recall• Multiple potential tools

–Choice of tool site specific

Self-Report Examples• ACTG questionnaire

–How many doses missed yesterday, 1, 2, and 3 days before

–How many doses missed over w/e?–When last dose missed?

• Visual Analog Scale–Ask ~how many doses taken over

past month–Place X on graduated line

Use of Pharmacy Refill Data• Specify period of interest

–Past 1, 2, 3 months for example–Cannot be shorter than length of

days supply–Too long may be irrelevant data

• Ensure full data capture– If centralized pharmacy: simple– If multiple commercial pharmacies:

logistically challenging, but feasible

Medication Possession Ratio

Fourth fill} } }

First fill Second fill

Third fill

First interval Second interval

Third interval

Adherence metric: (Σ interval days supply)/(4th fill date-1st fill

date)

Time

Grossberg R et al, J Clin Epi 2004

Drug

Concentrations

• Variable association with outcome–Some drugs strongly associated–Different pts on different drugs–Variability across drugs limits

programmatic utility• Logistical limitations

–Need for specimens (blood, hair)–Need for sophisticated lab–Turnaround time–Cost

Pill Counts• Weak association with outcome

–Yet commonly used–Demanding of staff time

• Other value–Limits dispensing expensive drug if

supply not used–Can add information to pharmacy refill

data

Microelectronic monitors• Strongly associated with outcome

–Can provide objective feedback–Useful in intervention–Granular view of dose timing and daily

taking• Logistical limitations

–Cumbersome– Inconvenient (cannot pocket doses)–Cost

Conclusions• Monitor entry in care

–Collate sources of data–Establish responsibilities for linkage

• Monitor retention–Track clinic administrative records

• Monitor adherence–Self-report or refill records–Other techniques need refinement or

replacement