ArticleBMC cancer2020
Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case -control study.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.
- Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe.BMC cancer · 2023Pooled it
- Alcohol consumption and breast lesions: targets for risk-based screening in high-risk Italian women.Breast cancer (Tokyo, Japan) · 2025Article
- Analysis of the chemotherapy effect of albumin-bound paclitaxel combined with pirarubicin and cyclophosphamide on breast cancer and the effects of PCR, ORR, and CBR.Pakistan journal of medical sciences · 2025Article
- Clinical validation of an integrated risk assessment test incorporating genomic and non-genomic data for sporadic breast cancer in Colombia.Frontiers in genetics · 2025Article
- Article
- Circadian PERformance in breast cancer: a germline and somatic genetic study of PER3NPJ breast cancer · 2021Article
Corrections and comments
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Authors and funding
25 authors at 6 institutions in 1 country.
Funding
Abstract
backgroundIn recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluation of individual risk of developing breast cancer.
methodsThis is a case control study based on a population-based cohort. We describe and evaluate a multivariable model that incorporates 92 Single-nucleotide polymorphisms (SNPs) (Supplementary Table S1) and five different phenotypic variables and which was employed in a Spanish population of 642 healthy women and 455 breast cancer patients.
resultsOur model allowed us to stratify two groups: high and low risk of developing breast cancer. The 9th decile included 1% of controls vs 9% of cases, with an odds ratio (OR) of 12.9 and a p-value of 3.43E-07. The first decile presented an inverse proportion: 1% of cases and 9% of controls, with an OR of 0.097 and a p-value of 1.86E-08.
conclusionsThese results indicate the capacity of our multivariable model to stratify women according to their risk of developing breast cancer. The major limitation of our analysis is the small cohort size. However, despite the limitations, the results of our analysis provide proof of concept in a poorly studied population, and opens up the possibility of using this method in the routine screening of the Spanish population.
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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 OpenQuestion graph.