Dataset Information

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.

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.

SUBMITTER: Cleries R

PROVIDER: S-EPMC8950380 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Publications

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.

Clèries Ramon R Buxó Maria M Vilardell Mireia M Ameijide Alberto A Martínez José Miguel JM Font Rebeca R Marcos-Gragera Rafael R Puigdemont Montse M Viñas Gemma G Carulla Marià M Espinàs Josep Alfons JA Galceran Jaume J Izquierdo Ángel Á Borràs Josep Maria JM

International journal of environmental research and public health 20220318 6

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 ...[more]

PMID: 35329292

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Project description:BACKGROUND: As the use of next-generation sequencing technologies is becoming more widespread, the need for robust software to help with the analysis is growing as well. A key challenge when analyzing sequencing data is the prediction of genotypes from the reads, i.e. correct inference of the underlying DNA sequences that gave rise to the sequenced fragments. For diploid organisms, the genotyper should be able to predict both alleles in the individual. Variations between the individual and the population can then be analyzed by looking for SNPs (single nucleotide polymorphisms) in order to investigate diseases or phenotypic features. To perform robust and high confidence genotyping and SNP calling, methods are needed that take the technology specific limitations into account and can model different sources of error. As an example, ancient DNA poses special challenges as the data is often shallow and subject to errors induced by post mortem damage. FINDINGS: We present a novel approach to the genotyping problem where a probabilistic framework describing the process from sampling to sequencing is implemented as a graphical model. This makes it possible to model technology specific errors and other sources of variation that can affect the result. The inferred genotype is given a posterior probability to signify the confidence in the result. SNPest has already been used to genotype large scale projects such as the first ancient human genome published in 2010. CONCLUSIONS: We compare the performance of SNPest to a number of other widely used genotypers on both real and simulated data, covering both haploid and diploid genomes. We investigate the effects of read depth, of removing adapters before mapping and genotyping, of using different mapping tools, and of using the correct model in the genotyping process. We show that the performance of SNPest is comparable to existing methods, and we also illustrate cases where SNPest has an advantage over other methods, e.g. when dealing with simulated ancient DNA.

Dataset Information

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.

Publications

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.

Similar Datasets

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