Evidence map›Paper›PMID 42268571›Full record

ArticleClinical drug investigation2026

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

Ahmed S Kenawy, James O Baffoe, Chanhyun Park

Abstract read
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Article in Clinical drug investigation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ahmed S KenawyHealth Outcomes Division, College of Pharmacy, The University of Texas at Austin, Austin, TX, 78712, USA.ORCID http://orcid.org/0000-0002-5133-265X
James O BaffoeHealth Outcomes Division, College of Pharmacy, The University of Texas at Austin, Austin, TX, 78712, USA.ORCID http://orcid.org/0000-0003-1236-6264
Chanhyun ParkHealth Outcomes Division, College of Pharmacy, The University of Texas at Austin, Austin, TX, 78712, USA. chanhyun.park@austin.utexas.edu.ORCID http://orcid.org/0000-0002-1081-0950

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer 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.

methodsThis 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.

resultsThe 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.

conclusionPatterns 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.

Indexed as

Diabetes Mellitus, Type 2Drug MonitoringHypoglycemic AgentsProstatic NeoplasmsAdministration, OralAgedAged, 80 and overCohort StudiesHumansMaleRetrospective StudiesHypoglycemic Agents

Identifiers

PMID42268571
PMCPMC13356077

What Socratic holds

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.