Transcript Grossberg - Pharmacy Pickup Adherence

ARV Pharmacy Refill Adherence
• Robert Grossberg, MD
• Montefiore Medical Center
• Albert Einstein College of Medicine
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Objectives
• Understand the importance of antiretroviral
adherence in HIV
• Evaluate various adherence measurement
methods
• Review the use of pharmacy refill
adherence methodology in HIV
2
% Achieving <500 copies/mL
Virologic Control falls sharply
with diminished adherence
90
80
70
N = 504 pts on HAART
60
50
40
30
20
10
0
95-100%
90-95%
80-90%
70-80%
< 70%
Adherence, by prescription refill
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Montessori, V, et al. XII International Conference on AIDS, Durban, South Africa, 2000. Abstract MoPpD1056.
Virologic Control falls sharply
with diminished adherence
Patients with HIV RNA
<400 copies/mL, %
100
80
60
40
20
0
>95
90-95
80–90
70-80
Protease Inhibitor adherence, %
(electronic bottle caps)
<70
4 Paterson, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago, IL. Abstract 92.
Adherence and AIDS-Free Survival
10% Adherence difference = 21% reduction in risk of AIDS
Proportion AIDS-Free
1.00
0.75
0.50
0.25
P = .0012
0.00
0
5
10
15
20
Months from entry
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Bangsberg D, et al. AIDS. 2001:15:1181
25
30
Adherence
O 90–100%
O 50–89%
O 0–49%
Sub-Optimal Adherence Predisposes to Resistance
• Sub-optimal adherence ==> sub-therapeutic drug
levels ==> incomplete viral suppression ==>
generation of resistant HIV strains by selection for
mutant viruses
• Association between poor adherence and
antiretroviral resistance is well-documented1,2
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1. Vanhove G, et al. JAMA. 1996;276:1955-1956.
2. Montaner JS, et al. JAMA. 1998;279:930-937.
Increasing probability
of selecting mutation
Adherence, Antiviral Activity & Risk
of Resistance Mutations
Low Risk of Resistance:
Inadequate Drug Exposure
Increasing Adherence
High
Risk of
Resistance:
Drug
Pressure
Sustains
Replication
of Poorly
Fit Virus
How do we Measure Adherence?
•
•
•
•
•
•
•
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Provider Estimates
Patient self-report
Diaries
Pill Count
Laboratory Markers
Electronic Devices
Prescription refill data
Measuring Adherence: Patient SelfReport
• patients tend to report what they think the provider wants to hear1
• patients are unlikely to misrepresent low levels of adherence3 - hence,
patient-reported poor adherence is specific but not sensitive
• patient-reported adherence tends to exceed adherence by more
objective measurements (such as pill count or electronic monitoring) 2
• Nevertheless, studies have documented an association between
patient-reported adherence and viral outcome 4-6
• Patient-reported adherence may be a useful tool to evaluate
adherence at a group level but not so much on an individual level
1. DiMatteo MR, DiNicola DD, eds. Achieving Patient Compliance. New York: Pergamon Press; 1982:1-28.
2. Golin C et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago. Abstract 95.
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3. Bond W, Hussar DA, Am J Public Health 1991;81:1978-1988.
4 Bangsberg DR, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago. Abstract 93.
5. Duong M, et al. 39th ICAAC; 1999; San Francisco. Abstract 2069
6. Demasi R, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago. Abstract 94.
Measuring Adherence: Electronic Bottle
Caps
MEMScaps, Aardex Corp.
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QuickRead software, for use with MEMScaps system
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http://www.aardex.ch/QRChronology.htm
Measuring Adherence: Electronic Bottle Caps
• Advantages
– more difficult for patients
to exaggerate their
adherence
– reveals patterns of nonadherence (i.e., what
time of day pills are
taken)
– studies using these
devices have
documented relationship
between adherence &
dosing
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• Disadvantages
– too expensive for
routine use outside of
research studies
– cannot be used for
patients who use
pillboxes
Pharmacy Refill Data
• Advantages
– only choice for retrospective studies
– can assess short or long-term behavior
• Disadvantages
– less intra-interval variability
– further removed from actual drug taking
– may not capture (legitimate) prescriptions from
other sources
– if automatic refills, data are useless
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Sources of Refill Data
• Automated database
–Medicaid
–VA System Pharmacies
–Pharmacy Benefit Managers
• Ad hoc data collection
–Call pharmacies
–HIPAA barriers?
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Examples of Refill Data
• Antihypertensives
–Taken chronically
• Disease process over years/decades
• Drugs infrequently changed
–Metric: number of refills obtained over
year
• Ratio of number of refills/12
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Examples of Refill Data
• Antiretrovirals
–Taken chronically
• Disease process over months/years
• Drugs frequently changed
–Metric: number of days to obtain 4 refills
(3 months)
• Ratio of 90 days supply/# of days to obtain
supply
• Time to event approach
• Allows for more variability over shorter
interval
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Prior Work using Refills in HIV
• Low-Beer et al. (Vancouver)
– 886 subjects
– Median cd4 count 290 cells/cm3 (IQR 130-440)
– Median viral load 130K (47K-310K)
– Follow up-median 19 mo (IQR 13-24mo)
– Adherence defined as
• # refills obtained/# months on therapy over 1 year
– Outcome-viral load <500 c/ml
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Proportion Undetectable (VL<500 c/ml)
Low-Beer et al. JAIDS 2000
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90%
84%
80%
70%
64%
60%
47%
50%
40%
30%
20%
24%
12%
10%
0%
n=
<70%
70-<80%
80-<90%
232
37
51
90-<95%
64
>95%
502
Issues with Refill Data
• Variety of other approaches possible
–Assessment of time to refill
–Assessment of duration of gaps
–Others
• Limitations
–Unclear how they will operate on short term
–For example, 3 months of follow-up allows
only for 2, 3, or 4 fills using Low-Beer
method
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Choice of Pharmacy Metric
–Metric: number of days to obtain 4
refills (3 months)
• 90 days supply/# of days to obtain
supply
• Time to event approach
• Allows for more variability over shorter
(clinically relevant) interval
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Time to 4 refills (3 months)
First fill
Second fill
Third fill
Fourth fill
}
}
}
First interval
Second interval
Third interval
Adherence metric: Σ intervals/(4th fill date-1st fill date)
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VA Pharmacy Refill Study
• Specific aim
–To compare validity of self-reported
measure and pharmacy refill measure of
adherence to antiretroviral therapy in HIV
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VA Refill Study Design
• Observational Study (n=110) conducted in the
Philadelphia VA HIV Clinic
• Outcomes
– Change in HIV viral load from baseline to study date
– HIV viral load undetectable or not (dichotomized)
• Exposures
– Adherence measured via self-report (ACTG
measure)
– Adherence measured using refill data (time to
obtaining 90 days supply)
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Setting/Study Patients
• Subjects on therapy at least 3 months
• Philadelphia VA Medical Center
–Veterans obtain all HIV Rx here
–Electronic pharmacy records
–Mailed medications require telephone call
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Pharmacy-based measure
0
1
2
3
4
5
Self -reported measure
0
20
40
60
80
100
120
140 0
20
40
60
80
100
Percent Adherence
Change in Log Viral Load (c/ml)
Entire
cohort, N=110
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Fitted values
120
140
VA Pharmacy Study Results
• Spearman correlation coefficient (95% CI)
• Adherence and change in viral load
Pharmacy refill = 0.22 (0.01 to 0.40)
Self-report = 0.10 (-0.08 to 0.32)
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VA Pharmacy Study Results
Change in plasma viral load
Rank sum
test
Method
Study group
Adherence >85%
Adherence <85%
Pharmacy
Entire cohort
N=57
2.4 log c/ml
(IQR 1.4 - 3.2)
N=53
1.5 log c/ml
(IQR 0.7 - 2.4)
0.005
N=96
2.1 log c/ml
(IQR 1.1 - 3.0)
N=14
1.4 log c/ml
(IQR 0.4 -1.9)
0.04
N=44
2.4 log c/ml
(IQR 1.4 - 3.4)
N=30
1.5 log c/ml
( IQR 0.8 - 2.4)
0.03
Self-report
Pharmacy
27
Entire cohort
100% by selfreport
p value
Conclusions of Refill Study
• Time to refill is a valid adherence
measure
–may perform better than self-report
• Generalizability outside of VA?
• Unclear function over shorter intervals
(e.g., 1 or 2 months)
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Time to 4 refills (90 days)
90d
60d
60d
30d
First fill
Second fill
Third fill
Fourth fill
}
}
}
First interval
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Second interval
Third interval
Correlation of shorter interval adherence measures
and change in viral load
0.265 (0.078-0.434)
0.184 (-0.007-0.362)
0.229 (0.036-0.405)
0.144 (-0.050-0.327)
0.150 (-0.045-0.334)
0.250 (0.059-0.423)
First fill
Second fill
Third fill
Fourth fill
}
}
}
First interval
30
Second interval
Third interval
Correlation of shorter interval adherence measures
and change in viral load
0.265 (0.078-0.434)
0.184 (-0.007-0.362)
0.229 (0.036-0.405)
0.144 (-0.050-0.327)
0.150 (-0.045-0.334)
0.250 (0.059-0.423)
First fill
Second fill
Third fill
Fourth fill
}
}
}
First interval
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Second interval
Third interval
Conclusions regarding shorter interval
measurements of refill adherence
• Shorter interval measurements of refill
adherence are associated with virologic
outcome.
• The “upstream” interval is the best predictor of
outcome.
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Summary
• Refill adherence is a valid method for measuring
adherence.
• Refill adherence correlates with outcome.
• Short interval measurements of refill adherence
are valid, but only if measured 60-90 days in
advance of the point of interest.
• Clinical use of refill data to inform providers
about medication adherence is evolving.
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