No Excess Mortality up to 10 Years in Early Stages of Breast Cancer in Women Adherent to Oral Endocrine Therapy: A Probabilistic Graphical Modeling Approach

• Published in: International journal of environmental research and public health Vol. 19; no. 6; p. 3605
• Main Authors: Clèries, Ramon, Buxó, Maria, Vilardell, Mireia, Ameijide, Alberto, Martínez, José Miguel, Font, Rebeca, Marcos-Gragera, Rafael, Puigdemont, Montse, Viñas, Gemma, Carulla, Marià, Espinàs, Josep Alfons, Galceran, Jaume, Izquierdo, Ángel, Borràs, Josep Maria
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18.03.2022; MDPI
• Subjects: Age; Antineoplastic Agents, Hormonal - therapeutic use; Bayes Theorem; Bayesian analysis; Breast cancer; Breast Neoplasms - diagnosis; Cohort Studies; Datasets; Endocrine therapy; Estrogens; Female; Humans; Indicators; Medical prognosis; Modelling; Models, Statistical; Mortality; Patients; Population; Simulation; Survival; Variables; Womens health; excess mortality; breast cancer; adherence; graphical modeling; synthetic dataset; endocrine therapy
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph19063605

Breast cancer (BC) is globally the most frequent cancer in women. Adherence to endocrine therapy (ET) in hormone-receptor-positive BC patients is active and voluntary for the first five years after diagnosis. This study examines the impact of adherence to ET on 10-year excess mortality (EM) in patients diagnosed with Stages I to III BC (N = 2297). Since sample size is an issue for estimating age- and stage-specific survival indicators, we developed a method, ComSynSurData, for generating a large synthetic dataset (SynD) through probabilistic graphical modeling of the original cohort. We derived population-based survival indicators using a Bayesian relative survival model fitted to the SynD. Our modeling showed that hormone-receptor-positive BC patients diagnosed beyond 49 years of age at Stage I or beyond 59 years at Stage II do not have 10-year EM if they follow the prescribed ET regimen. This result calls for developing interventions to promote adherence to ET in patients with hormone receptor-positive BC and in turn improving cancer survival. The presented methodology here demonstrates the potential use of probabilistic graphical modeling for generating reliable synthetic datasets for validating population-based survival indicators when sample size is an issue.