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Relative Risk01:12

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Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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Related Experiment Video

Updated: Jul 27, 2025

An R-Based Landscape Validation of a Competing Risk Model
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Polygenic Risk Score Predicts Modified Risk in

Egija Berga-Švītiņa1,2, Jeļena Maksimenko2,3, Edvīns Miklaševičs2,4

  • 1Bioinformatics Lab, Rīga Stradiņš University, Dzirciema Street 16, LV-1007 Riga, Latvia.

Cancers
|June 10, 2023
PubMed
Summary
This summary is machine-generated.

Polygenic risk scores (PRS) can predict breast cancer (BC) risk in BRCA1 variant carriers. However, PRS did not effectively predict ovarian cancer (OC) risk in this study.

Keywords:
BRCA1 pathogenic variant carriersbreast cancerovarian cancerpolygenic risk score (PRS)

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Area of Science:

  • Genetics and Genomics
  • Oncology
  • Cancer Risk Assessment

Background:

  • Germline pathogenic variants (PVs) in BRCA1 increase the risk of breast cancer (BC) and ovarian cancer (OC).
  • Additional genetic factors may influence cancer development in BRCA1 PV carriers.
  • Polygenic risk scores (PRS) are emerging tools for estimating genetic predisposition.

Purpose of the Study:

  • To evaluate the predictive power of PRS for BC and OC development in women with specific BRCA1 PVs (c.4035del or c.5266dup).
  • To assess if PRS can identify individuals at higher risk beyond the BRCA1 mutation itself.

Main Methods:

  • Application of two PRS models (BayesW and BayesRR-RC) derived from genome-wide association studies (GWAS).
  • Analysis included 406 BRCA1 PV carriers (c.4035del or c.5266dup) with BC or OC, compared to unaffected individuals.
  • Binomial logistic regression was used to assess the association between PRS and cancer risk.

Main Results:

  • The BayesW PRS model demonstrated significant predictive power for BC risk (OR = 1.37, AUC = 0.759, p = 0.02905).
  • None of the evaluated PRS models were effective predictors of OC risk in this cohort.
  • The findings highlight the potential utility of PRS for refining BC risk assessment in BRCA1 PV carriers.

Conclusions:

  • The BayesW PRS model can aid in assessing BC risk for carriers of BRCA1 c.4035del or c.5266dup variants.
  • PRS may improve patient stratification for BC, potentially enhancing treatment and prevention strategies.
  • Further research is needed to develop effective PRS models for predicting OC risk in this population.