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
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