ArticleStatistics in medicine2011
Personalized estimates of breast cancer risk in clinical practice and public health.
Article in Statistics in medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
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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.
The trial behind it
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
46 citing papers in PubMed, 80 citations in OpenAlex.
- Article
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- Graphical displays and related statistical measures of health disparities between groups in complex sample surveys.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- Data-integration with pseudoweights and survey-calibration: application to developing US-representative lung cancer risk models for use in screening.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- Mammography Screening Preferences Among Screening-Eligible Women in Their 40s : A National U.S. Survey.Annals of internal medicine · 2024Observational
- Polygenic Risk Score, Environmental Tobacco Smoke, and Risk of Lung Adenocarcinoma in Never-Smoking Women in Taiwan.JAMA network open · 2023Article
- Deep Learning Analysis of Mammography for Breast Cancer Risk Prediction in Asian Women.Diagnostics (Basel, Switzerland) · 2023Article
- Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?Cancers · 2023Article
- Recalibrating Risk Prediction Models by Synthesizing Data Sources: Adapting the Lung Cancer PLCO Model for Taiwan.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022Article
- Curcumin inhibits the growth of triple-negative breast cancer cells by silencing EZH2 and restoring DLC1 expression.Journal of cellular and molecular medicine · 2020Article
- Article
- Design and sample size considerations for Alzheimer's disease prevention trials using multistate models.Clinical trials (London, England) · 2019Article
- Risk prediction for breast Cancer in Han Chinese women based on a cause-specific Hazard model.BMC cancer · 2019Article
- Use of detailed family history data to improve risk prediction,with application to breast cancer screening.PloS one · 2019Article
- Estimating Risk of Breast Cancer Occurrences at Different Ages: Application of Survival TechniquesAsian Pacific journal of cancer prevention : APJCP · 2018Article
- Estimation of lifetime risks of Alzheimer's disease dementia using biomarkers for preclinical disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2018Article
- Evaluating the Impact of Uncertainty on Risk Prediction: Towards More Robust Prediction Models.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Measuring differential treatment benefit across marker specific subgroups: The choice of outcome scale.Contemporary clinical trials · 2017Article
- Statistical interactions and Bayes estimation of log odds in case-control studies.Statistical methods in medical research · 2017Article
- Bayesian joint ordinal and survival modeling for breast cancer risk assessment.Statistics in medicine · 2016Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
This paper defines absolute risk and some of its properties, and presents applications in breast cancer counseling and prevention. For counseling, estimates of absolute risk give useful perspective and can be used in management decisions that require weighing risks and benefits, such as whether or not to take tamoxifen to prevent breast cancer. Absolute risk models are also useful in designing intervention trials to prevent breast cancer and in assessing the potential reductions in absolute risk of disease that might result from reducing exposures that are associated with breast cancer. In these applications, it is important that the risk model be well calibrated, namely that it accurately predicts the numbers of women who will develop breast cancer in various subsets of the population. Absolute risk models are also needed to implement a 'high risk' prevention strategy that identifies a high-risk subset of the population and focuses intervention efforts on that subset. The limitations of the high-risk strategy are discussed, including the need for risk models with high discriminatory accuracy, and the need for less toxic interventions that can reduce the threshold of risk above which the intervention provides a net benefit. I also discuss the potential use of risk models in allocating prevention resources under cost constraints. High discriminatory accuracy of the risk model, in addition to good calibration, is desirable in this application, and the risk assessment should not be expensive in comparison with the intervention.
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Registered trials
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.