A Comparison Study of Multiple Measures of Adherence to HIV Protease Inhibitors

Nonadherence to medication is a major obstacle to successful medical treatment. Despite the efforts of providers, pharmaceutical manufacturers, and health systems to encourage adherence, irregular and incomplete drug dosing is common. Even interventions aimed at optimizing medication-taking often fail (1, 2). The economic burden of medication nonadherence, combining direct and indirect costs, is estimated to be as high as $100 billion annually (3). In HIV treatment, the effectiveness of highly active antiretroviral therapy is compromised by patients' difficulty in adhering to increasingly complicated regimens (4-7). Failure to adhere to prescribed HIV therapy may result in treatment failure as drug-resistant strains produce elevated viral loads and disease progression. Despite the importance of adherence in clinical care and research, rigorous study of measurement techniques is uncommon. This is in part because measurement of adherence to long-term medical therapy is complex and requires longitudinal assessment. Because of the intensity required in measuring adherence, more than one method of assessment is rarely used. Moreover, since there is no gold standard for adherence, evaluation of adherence measures usually requires assessing construct validity (8). Previous studies have shown that available adherence measures have limitations, raising questions about how best to measure drug-taking behavior (9). Although drug levels are an objective measure of drug exposure, they provide only a snapshot of behavior and are affected by factors other than adherence. Pill count is also commonly used to measure medication adherence in research, but it is too time-consuming and computationally complex for most clinical purposes. Several studies emphasized the shortcomings of pill count in overestimating adherence (10-13), often due to medication dumping (9). Although pharmacy and administrative records are a convenient source of adherence information, they are limited in many ways, including misinterpretation of usage when dosages change (14-16). Patient self-report has been used extensively to assess medication-taking, but this method tends to overestimate adherence (17, 18). Finally, the Medication Event Monitoring System (MEMS) (19-21), a relatively recent method, provides an objective measure of pill bottle opening, but it is not effective when pill storage devices are used or for liquid medications. The validity of studies designed to investigate critical aspects of adherence to antiretroviral therapy rests on researchers' ability to obtain valid measurements of medication-taking behavior. Despite the difficulties encountered in measuring medication adherence, methods of adherence measurement have rarely been directly and systematically compared in a longitudinal fashion. Using HIV viral load as a clinical criterion, we compared methods of measuring adherence to antiretroviral therapy among HIV-infected patients, developed a composite adherence score (CAS), analyzed the associations between each adherence measure and viral load, and explored the implications of missing adherence information. Methods We collected adherence data in an observational evaluation of antiretroviral medication use in a public HIV clinic. Several measures of medication adherence were collected to understand patients' adherence behavior and its relationship to HIV viral load suppression. Patient Sample From January 1998 through February 1999, patients who received care at a county hospitalassociated HIV clinic were enrolled in the Adherence and Efficacy of Protease Inhibitor Therapy (ADEPT) study. Enrolled patients spoke English or Spanish, were naive to protease inhibitors or had started protease inhibitor or non-nucleoside reverse transcriptase inhibitor (NNRTI) therapy in the past 3 months, and were able to provide informed consent for participation. Sixty percent of eligible patients enrolled in the trial. Data Collection Medication adherence and HIV viral load were assessed approximately every 4 weeks for 48 weeks. A face-to-face interview was administered at study entry to collect the patient's demographic information and clinical HIV history. At 8, 24, and 48 weeks after baseline, interviews were conducted to assess medication adherence by asking the following questions: Many people don't take their medication perfectly all the time. Over the past 7 days, how many times did you miss a dose of [this medication]? When was the last time that you missed any of [this medication]? In addition, patients were asked whether they used a pillbox. Objective information on medication adherence was collected by using MEMS and pill counts. The former is a pill bottle cap containing a microchip that records each instance of bottle opening. At study entry, a MEMS cap (Aprex Corp., Union City, California [22]) was placed on the bottle containing the patient's newly started protease inhibitor or NNRTI medication. Pill count was also computed at each 4-week period. The study nurse counted the number of pills remaining in the patient's bottle or bottles. For liquid medication, the height of the medication in the upright bottle was measured and converted into a number of doses missed. Definition of Adherence Measures We defined adherence as the percentage of prescribed doses taken during each 4-week period. For interview, adherence referred to the week before the interview took place. Scores for adherence measures ranged between 0 and 1, with 0 indicating complete nonadherence and 1 indicating perfect adherence. If more than the expected number of pills was taken, full adherence was assigned to that 4-week period. MEMS At each study visit, data from the MEMS cap were downloaded into the patient's drug-specific data file. Recorded dates and times of bottle opening were analyzed within 4-week blocks by using a software system created in SAS (SAS Institute, Inc., Cary, North Carolina). If a patient was taking more than one protease inhibitor or NNRTI, adherence for each drug was calculated first and mean adherence was then obtained by averaging drug-specific adherence values. Adherence measured by MEMS was computed by dividing the number of bottle openings by the number of expected doses over the time period. Pill Count Study participants brought their pill bottles to the clinic so that the study nurse could count the pills remaining in the bottle. The number of missed doses was computed from the difference between the actual and expected number of pills remaining in the bottle. Interview Responses to questions about number of doses missed during the past 7 days were translated into adherence over that period. Composite Adherence Score The CAS was created by combining the values for MEMS, pill count, and interview. Because MEMS caps record each bottle opening, this measure is most closely related to medication dosing and was used as the foundation of CAS. Inaccuracies in MEMS were identified by 1) medication changes within 4-week blocks, 2) use of a pillbox, 3) use of liquid medicine, 4) medications distributed by other people, 5) medication sharing, and 6) lost or damaged bottles and caps. In a hierarchical fashion, when MEMS values were missing or were considered inaccurate, CAS values were obtained from calibrated estimates of pill count adherence. If the pill count information was also missing, the CAS was obtained from calibrated values for interview adherence. The Appendix Figure illustrates the algorithm of CAS computation. If the patient was not prescribed antiretroviral medications during the period, the CAS is missing. Before use in the CAS computation, pill count and interview adherence values were calibrated to MEMS values. Calibration was performed because when MEMS, pill count, and interview values were available for the same period, pill count and interview values were regularly higher than MEMS values, and the literature suggests that pill count and interview overestimate adherence (11-13, 17, 18). Repeated-measures longitudinal models showed that mean calibration coefficients (SD) for pill count and interview were 0.75 0.045 and 0.89 0.18, respectively. The equations used to compute MEMS, pill count, and interview adherence and the calibration model are shown in the Appendix. Viral Load Determinations We measured HIV viral load in copies/mL approximately every 4 weeks. An undetectable viral load was defined as an HIV RNA level less than 400 copies/mL. Serum was processed, stored at 70 C, and subsequently assayed for HIV RNA by using the Amplicor assay (Roche Diagnostics Systems, Branchburg, New Jersey). Statistical Analysis Univariate statistics for each adherence measure and bivariate associations between the three adherence measures were calculated. Only interview values from 8 and 24 weeks were used in this analysis because of the small number of patients with data at 48 weeks. The mean of adherence summarized over time for each patient and then averaged over patients was compared across measures. The time trend of adherence measures was evaluated by using repeated-measures models. At each 4-week block, paired analyses compared mean adherence between measures. We evaluated mean antiretroviral adherence between persons with undetectable and detectable levels of viral load. At weeks 8 and 24, CAS, MEMS, pill count, and interview predictions of undetectable viremia were evaluated as the area under the receiver-operating characteristic (ROC) curve. The longitudinal power of each adherence measure to predict HIV virologic response across all 4-week blocks was evaluated by using repeated-measures logistic regression models. When measured adherence from MEMS, pill count, or interview was missing, we examined the distribution of adherence measured by CAS, including mean adherence and the percentage of patients with a CAS lower than the clinically important cutoffs of 85% and 95% (7). Statistical analyses were performed by using SAS statistical softw