ArticleBiostatistics (Oxford, England)2015
Testing calibration of risk models at extremes of disease risk.
Article in Biostatistics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Genomic Risk Score for Melanoma in a Prospective Study of Older Individuals.Journal of the National Cancer Institute · 2021Pooled it
- Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma.Human molecular genetics · 2018Pooled it
- A constrained maximum likelihood approach to developing well-calibrated models for predicting binary outcomes.Lifetime data analysis · 2024Article
- Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?Cancers · 2023Article
- Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention.Medical review (2021) · 2021Review
- Article
- Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.Journal of the National Cancer Institute · 2021Article
- Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks.American journal of human genetics · 2020Article
- Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk.Molecular oncology · 2020Article
- Future Preventive Gene Therapy of Polygenic Diseases from a Population Genetics Perspective.International journal of molecular sciences · 2019Article
- Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases.Journal of personalized medicine · 2019Article
- Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk.Breast cancer research : BCR · 2019Article
- Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.American journal of human genetics · 2019Article
- Age-related late-onset disease heritability patterns and implications for genome-wide association studies.PeerJ · 2019Article
- Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium.International journal of epidemiology · 2018Article
- Testing Calibration of Cox Survival Models at Extremes of Event Risk.Frontiers in genetics · 2018Article
- Update on the State of the Science for Analytical Methods for Gene-Environment Interactions.American journal of epidemiology · 2017Article
- Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States.JAMA oncology · 2016Article
- Developing and evaluating polygenic risk prediction models for stratified disease prevention.Nature reviews. Genetics · 2016Review
- Multigene testing of moderate-risk genes: be mindful of the missense.Journal of medical genetics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Risk-prediction models need careful calibration to ensure they produce unbiased estimates of risk for subjects in the underlying population given their risk-factor profiles. As subjects with extreme high or low risk may be the most affected by knowledge of their risk estimates, checking the adequacy of risk models at the extremes of risk is very important for clinical applications. We propose a new approach to test model calibration targeted toward extremes of disease risk distribution where standard goodness-of-fit tests may lack power due to sparseness of data. We construct a test statistic based on model residuals summed over only those individuals who pass high and/or low risk thresholds and then maximize the test statistic over different risk thresholds. We derive an asymptotic distribution for the max-test statistic based on analytic derivation of the variance-covariance function of the underlying Gaussian process. The method is applied to a large case-control study of breast cancer to examine joint effects of common single nucleotide polymorphisms (SNPs) discovered through recent genome-wide association studies. The analysis clearly indicates a non-additive effect of the SNPs on the scale of absolute risk, but an excellent fit for the linear-logistic model even at the extremes of risks.
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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.