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

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 patie...

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Bibliographic Details
Authors: Clèries Soler, Ramon, Buxó, Maria, Vilardell, Mireia, Ameijide, Alberto, Martínez, José Miguel, Font, Rebeca, Marcos Gragera, Rafael, Puigdemont, Montserrat, Viñas, Gemma, Carulla, Marià, Espinàs Piñol, Josep Alfons, Galceran, Jaume, Izquierdo i Font, Àngel Xavier, Borràs, Josep Maria
Format: article
Status:Published version
Publication Date:2022
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/185037
Online Access:https://hdl.handle.net/2445/185037
Access Level:Open access
Keyword:Càncer de mama
Endocrinologia
Breast cancer
Endocrinology
Description
Summary: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.

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