ArticleJAMA oncology2016
Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States.
Article in JAMA oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 212 papers, 13 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
212 citing papers in PubMed, 13 syntheses or guidelines pooled it, 401 citations in OpenAlex.
- Artificial intelligence in the radiologic assessment of ductal carcinomaFrontiers in oncology · 2026Pooled it
- Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- A systematic review of prediction models for risk of breast cancer.BMC cancer · 2025Pooled it
- Dietary Glycemic Index, Glycemic Load, Sugar, and Fiber Intake in Association With Breast Cancer Risk: An Updated Meta-analysis.Nutrition reviews · 2025Pooled it
- Genome-wide association study of idiopathic epilepsy in the Italian Spinone dog breed.PloS one · 2025Pooled it
- Dietary factors associated with breast cancer among women in Ethiopia: a systematic review and meta-analysis of case-control studies.Frontiers in nutrition · 2025Pooled it
- Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe.BMC cancer · 2023Pooled it
- Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population.Nature communications · 2023Pooled it
- The Promise of Polygenic Risk Prediction in Smoking Cessation: Evidence From Two Treatment Trials.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2022Pooled it
- Integrative genomic analysis implicates ERCC6 and its interaction with ERCC8 in susceptibility to breast cancer.Scientific reports · 2020Pooled it
- Identification of risk loci and a polygenic risk score for lung cancer: a large-scale prospective cohort study in Chinese populations.The Lancet. Respiratory medicine · 2019Pooled it
- Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large-scale analysis of 14 published GWAS datasets in the DRIVE study.International journal of cancer · 2019Pooled it
- A systematic review and quality assessment of individualised breast cancer risk prediction models.British journal of cancer · 2019Pooled it
- Genetic Variant in CHRNA5 and Response to Varenicline and Combination Nicotine Replacement in a Randomized Placebo-Controlled Trial.Clinical pharmacology and therapeutics · 2020Trial
- Trial
- Individuals who deviate from polygenic expectation are enriched for damaging variants in genes linked to rare disease.American journal of human genetics · 2026Article
- Breast cancer polygenic risk score performance varies by socioeconomic status.medRxiv : the preprint server for health sciences · 2026Article
- Contextualizing the Utility of Polygenic Risk Scores using Absolute Risk Models in Diverse Ancestry Populations.medRxiv : the preprint server for health sciences · 2026Article
- Estimation of direct and indirect polygenic effects and gene-environment interactions using polygenic scores in case-parent trio studies.Nature genetics · 2026Article
- Article
152 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Erratum issuedErrata2016
Authors and funding
45 authors at 20 institutions in 8 countries.
Funding
Abstract
importanceAn improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention.
objectiveTo evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors. DESIGN, SETTING, AND
participantsUsing a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality. EXPOSURES: Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors. MAIN OUTCOMES AND MEASURES: Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking).
resultsThe average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population. CONCLUSIONS AND RELEVANCE: This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.
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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.