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. 2022 Mar 18;19(6):3605.
doi: 10.3390/ijerph19063605.

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

Ramon Clèries  1   2   3 , Maria Buxó  4 , Mireia Vilardell  5 , Alberto Ameijide  6 , José Miguel Martínez  7   8 , Rebeca Font  1   2 , Rafael Marcos-Gragera  4   9   10   11   12 , Montse Puigdemont  9   10 , Gemma Viñas  13 , Marià Carulla  6 , Josep Alfons Espinàs  1   2 , Jaume Galceran  6 , Ángel Izquierdo  9   10   13 , Josep Maria Borràs  1   2   3
Affiliations

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

Ramon Clèries et al. Int J Environ Res Public Health. .

Abstract

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.

Keywords: adherence; breast cancer; endocrine therapy; excess mortality; graphical modeling; synthetic dataset.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Scheme of procedure for generating combined cohort by using best synthetic cohort for each of the considered L age-stratum groups. Synthetic cohorts generated according to ModGraProDep.
Figure 2
Figure 2
Undirected acyclic graphs generated from fitting the best graphical models to observed data (N = 1243) using different criterions: (a) GMK1 model: k-penalty factor of penalized log-likelihood set to 1; (b) GMTEST: testing for statistical significance of arches; (c) GMAIC: Akaike information criterion (BIC) and GMBIC: Bayesian information criterion (BIC).
Figure 3
Figure 3
Comparison of 95% credible interval of observed survival derived from original cohort (black) and median survival (red) of combined cohort across stages at diagnosis and stratified by age group.
Figure 4
Figure 4
Comparison of 5-year conditional excess mortality (in percentage) between original cohort (black) and combined cohort (red) across stage at diagnosis and stratifying by adherence to endocrine therapy: (a,d) Stage I; (b,e) Stage II; (c,f) Stage III.
Figure 5
Figure 5
Graphical comparison of main population-based survival indicators between adherent and nonadherent BC patients across age groups: (a–c) EM(5); (d–f) PCa(10); (g–i) OS(10). EM(5): 5-year conditional excess mortality (EM) at T = 5 years after cancer diagnosis; PCa(10): crude probability of death due to cancer at T = 10 years; OS(10): observed survival at 10 years after cancer diagnosis.
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