Change in Adherence to Oral Antidiabetic Medications Before and After Prostate Cancer Diagnosis: A Group-Based Trajectory Modeling Approach

Cancer diagnoses impact adherence to antidiabetic medications, but limited research has focused on patients with prostate cancer and type 2 diabetes (T2DM). We investigated adherence trajectories to oral antidiabetic medications one year before and after a prostate cancer diagnosis and identified risk factors.

This retrospective cohort study used the 2011–2021 MarketScan Commercial and Medicare Supplemental databases. We included newly diagnosed prostate cancer patients with T2DM with continuous insurance enrollment. We applied group-based trajectory modeling with a beta distribution to evaluate adherence patterns before and after prostate cancer diagnosis. Model covariates included age, total number of medications, number of antidiabetic medications, the Charlson Comorbidity Index (CCI), cost, insurance type, and complicated diabetes from the year before diagnosis. Metastasis and cancer treatments were included in the model after diagnosis.

The study included 7864 patients (mean age = 74.5 ± 7.1). Three adherence trajectories were identified before diagnosis: consistently high adherence, steady decliners, and consistently low adherence. After diagnosis, a fourth trajectory revealing a moderate decline emerged. Over half (61.2%) changed adherence patterns after diagnosis. Among those with consistently high adherence before diagnosis, 57.8% transitioned to a lower adherence trajectory. In contrast, 58.5% of steady decliners and 57.6% of consistently low adherents transitioned to a higher adherence trajectory after diagnosis. Predictors of high adherence included older age, fewer antidiabetic medications, lower CCI, and complicated diabetes before diagnosis. After diagnosis, fewer antidiabetic medications and complicated diabetes remained predictive of high adherence.

Patterns of adherence to oral antidiabetic medications undergo substantial changes after a prostate cancer diagnosis. Targeted interventions are needed to support and facilitate effective diabetes management in this population.