ALL TAKING SOME OR SOME TAKING NONE? ASSESSING WHETHER DIFFERENT APPROACHES FOR MODELING DRUG COMPLIANCE AFFECT THE OPTIMAL DECISION FOR STATIN TREATMENT INITIATION

ALL TAKING SOME OR SOME TAKING NONE? ASSESSING WHETHER DIFFERENT APPROACHES FOR MODELING DRUG COMPLIANCE AFFECT THE OPTIMAL DECISION FOR STATIN TREATMENT INITIATION

Purpose: When medication compliance is reported as a single value without additional context, it is unclear how this parameter should be modeled in cost-effectiveness analyses. We sought to evaluate whether modeling compliance using two extreme assumptions affected the optimal decision for initiating statin treatment for primary atherosclerotic cardiovascular disease (ASCVD) prevention in the U.S.

Methods: We used a previously developed and validated ASCVD micro-simulation model for a representative adult population in the U.S. (ages 40-75 years). In the model, hypothetical individuals received statin treatment, experienced ASCVD events, and died from ASCVD-related or non-ASCVD-related causes based on ASCVD natural history and statin treatment parameters. All model parameters were estimated from published sources. Statin compliance rates after initiating treatment were 67%, 53%, and 50% in years 1, 2, and 3+, respectively. We used this model to identify and compare optimal ASCVD treatment thresholds under two statin compliance assumptions: 1) proportional reductions in drug effectiveness/risks/costs for all users; and 2) some proportion of patients that are fully compliant with all others completely noncompliant. We evaluated various 10-year ASCVD risk thresholds between >2.0-15.0% (including >7.5%, the current policy recommendation in the U.S.) as well as a treat none strategy in our cost-effectiveness analyses. We used a societal perspective, 3% discount rate for costs and health outcomes, and $50,000-$150,000 per quality-adjusted life year (QALY) cost-effectiveness threshold range.

Results: For any given ASCVD treatment threshold strategy, lifetime discounted costs and QALYs were lower using compliance approach 1 (proportional reductions) compared to compliance approach 2 (individuals either fully compliant or noncompliant). The differences between compliance approaches were more pronounced for strategies that resulted in more individuals taking statins (i.e., for more lenient treatment thresholds). Optimal ASCVD treatment thresholds were >7.5%, >4.0%, and >3.0% using cost-effectiveness thresholds of $50,000/QALY, $100,000/QALY, and $150,000/QALY respectively for both compliance approaches (Table).  

Conclusions: While the choice of modeling statin compliance affected total cost and QALY results, we found that the optimal decisions regarding statin treatment thresholds in the U.S. did not differ by compliance approach. The true effect of medication noncompliance likely lies somewhere between the two extreme approaches we evaluated.