Medication adherence assessment in a clinical trial with centralized follow-up and direct-to-patient drug shipments.

BACKGROUND: Assessment of adherence to study medications is a common challenge in clinical research. Counting unused study medication is the predominant method by which adherence is assessed in outpatient clinical trials but it has limitations that include questionable validity and burdens on research personnel. PURPOSE: To compare capsule counts, patient questionnaire responses, and plasma drug levels as methods of determining adherence in a clinical trial that had 2056 participants and used centralized drug distribution and patient follow-up. METHODS: Capsule counts from study medication bottles returned by participants and responses to questions regarding adherence during quarterly telephone interviews were averaged and compared. Both measures were compared to plasma drug levels obtained at the 3-month study visit of patients in the treatment group. Counts and questionnaire responses were converted to adherence rates (doses taken divided by days elapsed) and were categorized by stringent (≥85.7%) and liberal (≥71.4%) definitions. We calculated the prevalence-adjusted bias-adjusted kappa to assess agreement between the two measures. RESULTS: Using a pre-paid mailer, participants returned 76.0% of study medication bottles to the central pharmacy. Both capsule counts and questionnaire responses were available for 65.8% of participants and were used to assess adherence. Capsule counts identified more patients who were under-adherent (18.8% by the stringent definition and 7.5% by the liberal definition) than self-reports did (10.4% by the stringent definition and 2.1% by the liberal definition). The prevalence-adjusted bias-adjusted kappa was 0.58 (stringent) and 0.83 (liberal), indicating fair and very good agreement, respectively. Both measures were also in agreement with plasma drug levels determined at the 3-month visit (capsule counts: p = 0.005 for the stringent and p = 0.003 for the liberal definition; questionnaire: p = 0.002 for both adherence definitions). LIMITATIONS: Inconsistent bottle returns and incomplete notations of medication start and stop dates resulted in missing data but exploratory missing data analyses showed no reason to believe that the missing data resulted in systematic bias. CONCLUSIONS: Depending upon the definition of adherence, there was fair to very good agreement between questionnaire results and capsule counts among returned study bottles, confirmed by plasma drug levels. We conclude that a self-report of medication adherence is potentially comparable to capsule counts as a method of assessing adherence in a clinical trial, if a relatively low adherence threshold is acceptable, but adherence should be confirmed by other measures if a high adherence threshold is required.

Pharmacoeconomic analysis of angiotensin-converting enzyme inhibitors in type 2 diabetes: a Markov model.

BACKGROUND: Prevention of cardiovascular disease (CVD) events by initiating an angiotensin-converting enzyme (ACE) inhibitor on diagnosis of type 2 diabetes may increase survival and decrease costs. OBJECTIVE: To determine the incremental cost-effectiveness ratios of ACE inhibitor initiation in normoalbuminuric, microalbuminuric, and macroalbuminuric patients with newly diagnosed type 2 diabetes. METHODS: A cohort of patients with newly diagnosed type 2 diabetes was followed for 8 years in a Markov model. Clinical outcomes included CVD events, dialysis, all-cause mortality, and the composite endpoints of the 3 events. Probabilities and costs were obtained from the literature. One-way and two-way sensitivity analyses were conducted to test the robustness of the model. RESULTS: Implementation of ACE inhibitor therapy on diagnosis of type 2 diabetes in normoalbuminuric and microalbuminuric patients is a dominant strategy (ie, more effective and less costly) across all outcomes. In macroalbuminuric patients, an additional $4.10 and $4.58 saves one life and avoids one composite endpoint, respectively; however, in these patients, not giving an ACE inhibitor is dominant for prevention of CVD events and dialysis. This is due to a 28.62% higher mortality rate in patients not receiving an ACE inhibitor. Thus, analysis of the composite endpoint shows that not giving an ACE inhibitor does not remain dominant. A limitation of our study is the inability to determine causality. CONCLUSIONS: If every newly diagnosed patient with type 2 diabetes in the US was prescribed an ACE inhibitor, our model shows that 68,314 CVD events would be averted, 46,410 lives would be saved, and 48 people would be prevented from needing dialysis over 8 years. These findings suggest that ACE inhibitors prevent numerous events in patients with type 2 diabetes who are normoalbuminuric at diagnosis, in addition to those already identified as being at risk for CVD events.