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ARV Pharmacy Refill Adherence. Robert Grossberg, MD Montefiore Medical Center Albert Einstein College of Medicine. Objectives. Understand the importance of antiretroviral adherence in HIV Evaluate various adherence measurement methods
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ARV Pharmacy Refill Adherence • Robert Grossberg, MD • Montefiore Medical Center • Albert Einstein College of Medicine
Objectives • Understand the importance of antiretroviral adherence in HIV • Evaluate various adherence measurement methods • Review the use of pharmacy refill adherence methodology in HIV
Virologic Control falls sharply with diminished adherence N = 504 pts on HAART % Achieving <500 copies/mL Adherence, by prescription refill 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, % Protease Inhibitor adherence, % (electronic bottle caps) Paterson, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago, IL. Abstract 92.
Adherence O 90–100% O50–89% O 0–49% Adherence and AIDS-Free Survival 10% Adherence difference = 21% reduction in risk of AIDS 1.00 0.75 Proportion AIDS-Free 0.50 0.25 P = .0012 0.00 0 5 10 15 20 25 30 Months from entry Bangsberg D, et al. AIDS. 2001:15:1181
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 1. Vanhove G, et al. JAMA. 1996;276:1955-1956. 2. Montaner JS, et al. JAMA. 1998;279:930-937.
Adherence, Antiviral Activity & Risk of Resistance Mutations High Risk of Resistance: Drug Pressure Sustains Replication of Poorly Fit Virus Low Risk of Resistance: Complete Viral Suppression Low Risk of Resistance: Inadequate Drug Exposure Increasing probability of selecting mutation Increasing Adherence
How do we Measure Adherence? • Provider Estimates • Patient self-report • Diaries • Pill Count • Laboratory Markers • Electronic Devices • Prescription refill data
Measuring Adherence: Patient Self-Report • 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. 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.
QuickRead software, for use with MEMScaps system http://www.aardex.ch/QRChronology.htm
Advantages more difficult for patients to exaggerate their adherence reveals patterns of non-adherence (i.e., what time of day pills are taken) studies using these devices have documented relationship between adherence & dosing Disadvantages too expensive for routine use outside of research studies cannot be used for patients who use pillboxes Measuring Adherence: Electronic Bottle Caps
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
Sources of Refill Data Automated database Medicaid VA System Pharmacies Pharmacy Benefit Managers Ad hoc data collection Call pharmacies HIPAA barriers?
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
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
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
Low-Beer et al. JAIDS 2000 n= 232 37 51 64 502
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
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
Time to 4 refills (3 months) First fill Second fill Third fill } } } First interval Second interval Third interval Fourth fill Adherence metric: Σ intervals/(4th fill date-1st fill date)
VA Pharmacy Refill Study Specific aim To compare validity of self-reported measure and pharmacy refill measure of adherence to antiretroviral therapy in HIV
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)
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
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)
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)
Time to 4 refills (90 days) First fill Second fill Third fill } } } First interval Second interval Third interval 90d 60d 60d 30d Fourth fill
Correlation of shorter interval adherence measures and change in viral load First fill Second fill Third fill } } } First interval Second interval Third interval 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) Fourth fill
Correlation of shorter interval adherence measures and change in viral load First fill Second fill Third fill } } } First interval Second interval Third interval 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) Fourth fill
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.
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.