Modeling Breast Cancer Patient, Communication and Treatment Factors in Discontinuation of Daily Adjuvant Treatment Over Time

Introduction. Despite the substantial survival benefit from daily oral endocrine therapy (ET) for estrogen receptor positive breast cancer, 50% of patients discontinue ET before completing 5 years. In order to identify patients at risk for early discontinuation, models are needed that account for the varying effects of factors over time. Methods. A decisional logic model representing possible casual interactions between 19 psychological, demographic, and treatment factors with adherence was assembled based on expert knowledge and tested against data from 83 patients assessed annually for over 3 years. Competing sets of logical rules supporting compliance with observed behaviors as well as regulatory parsimony were identified by solving a Constraint Satisfaction Problem (CSP). Repeated simulations were then conducted to identify risk factors and interventional strategies for early discontinuation of therapy in the presence of biological noise. Results. CSP identified 96 decisional models explaining up to 75% of discontinuation trajectories. These competing models collectively supported 15 stable attractor profiles which are characterized by low perceived risk of cancer recurrence, low level of cancer worry, high level of generalized anxiety, and poor quality of life (QoL) ratings. Answer Set Programming (ASP) applied to each of the 15 non- adherent profiles identified 6 interventional strategies restoring adherence in 13 of these profiles. These involved reducing general anxiety and reinforcing pill-taking strategies, trust in medical system. Neither education, age, nor household income consistently characterized these 13 steady states. Concurrently increasing health literacy in patients with lower education levels, was predicted to improve efficacy of the aforementioned strategies. Conclusions. These analyses suggest that discontinuation trajectories over time can be predicted from behavioral constructs. Improved understanding of mechanisms mediating perceived risk of recurrence and low ratings of QoL specifically could further improve model fidelity. Potential interventional targets include general anxiety, trust in the medical system and strengthened routines.