ArticleOncotarget2018
Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- A systematic review of prediction models for risk of breast cancer.BMC cancer · 2025Pooled it
- Role of Polygenic Risk Score in Cancer Precision Medicine of Non-European Populations: A Systematic Review.Current oncology (Toronto, Ont.) · 2022Pooled it
- Evaluation of Multiple Breast Cancer Polygenic Risk Score Panels in Women of Latin American Heritage.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Article
- Breast cancer risk assessment based on susceptibility genes and polygenic risk score in Vietnamese women.BJC reports · 2024Article
- Article
- Development of a Breast Cancer Risk Prediction Model Incorporating Polygenic Risk Scores and Nongenetic Risk Factors for Korean Women.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Development and validation of polygenic risk scores for prediction of breast cancer and breast cancer subtypes in Chinese women.BMC cancer · 2022Article
- BREAst screening Tailored for HEr (BREATHE)-A study protocol on personalised risk-based breast cancer screening programme.PloS one · 2022Article
- Cost effectiveness analysis of a polygenic risk tailored breast cancer screening programme in Singapore.BMC health services research · 2021Article
- Deep neural network improves the estimation of polygenic risk scores for breast cancer.Journal of human genetics · 2021Article
- Breast Cancer Risk Prediction in Korean Women: Review and Perspectives on Personalized Breast Cancer Screening.Journal of breast cancer · 2020Review
- Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field.Breast cancer research : BCR · 2020Review
- Genetic Testing to Guide Risk-Stratified Screens for Breast Cancer.Journal of personalized medicine · 2019Review
- Polygenic Determinants for Subsequent Breast Cancer Risk in Survivors of Childhood Cancer: The St Jude Lifetime Cohort Study (SJLIFE).Clinical cancer research : an official journal of the American Association for Cancer Research · 2018Article
- ZNF423: A New Player in Estrogen Receptor-Positive Breast Cancer.Frontiers in endocrinology · 2018Review
Corrections and comments
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Authors and funding
20 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157-3.100), 2.013 (95% CI = 1.227-3.302) and 1.751 (95% CI = 1.073-2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.
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