Temporal effect of imatinib adherence on time to remission in chronic myeloid leukemia patients

Abstract

Introduction Adherence to imatinib in chronic myeloid leukemia (CML) patients is estimated to be as low as 70% despite its clinical benefit, and our understanding of the impact of nonadherence in this population is limited. This study presents a novel application of the Alternating Conditional Estimation (ACE) algorithm in newly diagnosed CML patients to map the full dose–response curve (DRC) and determine how the strength of this curve varies over time. Methods We applied the ACE algorithm alongside a backward elimination procedure to detect the presence of time dependence and nonlinearity in the relationship between imatinib adherence and time-to-remission. An extended Cox model allowing for the flexible modeling of identified effects via unpenalized B-splines was subsequently fit and assessed. Results The substantial improvement in model fit associated with the extended Cox approach suggests that traditional Cox proportional hazards model assumptions do not hold in this setting. Results indicate that the DRC for imatinib is non-linearly increasing, with an attenuated effect above a 74% adherence rate. The strength of this effect on remission varied over time and was strongest in the initial months of treatment, reaching a peak around 90 days post-initiation (log hazard ratio: 2.12, 95% confidence interval: 1.47 to 2.66). Conclusion Most patients that achieved remission did so by 4 months (120 days) with consistently high adherence, suggesting that this could be a critical time and duration for realizing treatment benefit and patient monitoring. Findings regarding the relationship between adherence and remission can additionally help guide the design of future studies.