ArticleAmerican journal of human genetics2008
Using the optimal receiver operating characteristic curve to design a predictive genetic test, exemplified with type 2 diabetes.
Article in American journal of human genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed.
- Using changes in binding globulins to assess oral contraceptive compliance.Contraception · 2013Trial
- A multi-locus predictiveness curve and its summary assessment for genetic risk prediction.Statistical methods in medical research · 2020Article
- Future Preventive Gene Therapy of Polygenic Diseases from a Population Genetics Perspective.International journal of molecular sciences · 2019Article
- Assessing the performance of genome-wide association studies for predicting disease risk.PloS one · 2019Article
- Using Breast Cancer Risk Associated Polymorphisms to Identify Women for Breast Cancer Chemoprevention.PloS one · 2017Article
- Breast cancer risk prediction using a clinical risk model and polygenic risk score.Breast cancer research and treatment · 2016Article
- A Three-Way Interaction among Maternal and Fetal Variants Contributing to Congenital Heart Defects.Annals of human genetics · 2016Article
- Constructing Hypothetical Risk Data from the Area under the ROC Curve: Modelling Distributions of Polygenic Risk.PloS one · 2016Article
- GWGGI: software for genome-wide gene-gene interaction analysis.BMC genetics · 2014Article
- Estimating the predictive ability of genetic risk models in simulated data based on published results from genome-wide association studies.Frontiers in genetics · 2014Article
- Bridge: a GUI package for genetic risk prediction.BMC genetics · 2013Article
- Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.PLoS genetics · 2013Article
- Analytical and simulation methods for estimating the potential predictive ability of genetic profiling: a comparison of methods and results.European journal of human genetics : EJHG · 2012Article
- A likelihood ratio-based Mann-Whitney approach finds novel replicable joint gene action for type 2 diabetes.Genetic epidemiology · 2012Article
- Gene × environment interactions in type 2 diabetes.Current diabetes reports · 2011Review
- Collapsing ROC approach for risk prediction research on both common and rare variants.BMC proceedings · 2011Article
- Annotating individual human genomes.Genomics · 2011Review
- Detecting genetic interactions for quantitative traits with U-statistics.Genetic epidemiology · 2011Article
- Improved risk prediction for Crohn's disease with a multi-locus approach.Human molecular genetics · 2011Article
- Psoriasis prediction from genome-wide SNP profiles.BMC dermatology · 2011Article
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2 authors.
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Abstract
Current extensive genetic research into common complex diseases, especially with the completion of genome-wide association studies, is bringing to light many novel genetic risk loci. These new discoveries, along with previously known genetic risk variants, offer an important opportunity for researchers to improve health care. We describe a method of quick evaluation of these new findings for potential clinical practice by designing a new predictive genetic test, estimating its classification accuracy, and determining the sample size required for the verification of this accuracy. The proposed predictive test is asymptotically more powerful than tests built on any other existing method and can be extended to scenarios where loci are linked or interact. We illustrate the approach for the case of type 2 diabetes. We incorporate recently discovered risk factors into the proposed test and find a potentially better predictive genetic test. The area under the receiver operating characteristic (ROC) curve (AUC) of the proposed test is estimated to be higher (AUC = 0.671) than for the existing test (AUC = 0.580).
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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.