Multiple diseases in carrier probability estimation: Accounting for surviving all cancers other than breast and ovary in BRCAPRO

No abstract is available for this paper.

• Publication year

  2008

• Venue

  Statistics in Medicine

• Publication date

  2008-09-30

• Fields of study

  Mathematics, Medicine

• Identifiers
  DOI 10.1002/sim.3302PMID 18407567PMCID PMC2562929
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Statistical Applications in Genetics and Molecular Biology BayesMendel : an R Environment for Mendelian Risk Prediction

  2011cited by this paper
• Prediction of Germline Mutations and Cancer Risk in the Lynch Syndrome

  2008cited by this paper
• Validity of Models for Predicting BRCA1 and BRCA2 Mutations

  2007cited by this paper
• Prostate cancer progression and survival in BRCA2 mutation carriers.

  2007cited by this paper
• Optimal selection of individuals for BRCA mutation testing: a comparison of available methods.

  2006cited by this paper
• Effect of Misreported Family History on Mendelian Mutation Prediction Models

  2006cited by this paper
• Characterization of BRCA1 and BRCA2 mutations in a large United States sample.

  2006cited by this paper
• The risk of ovarian cancer after breast cancer in BRCA1 and BRCA2 carriers.

  2005cited by this paper
• Good medicine is efficient medicine.

  2005cited by this paper
• Accuracy of MSI testing in predicting germline mutations of MSH2 and MLH1: a case study in Bayesian meta-analysis of diagnostic tests without a gold standard.

  2005cited by this paper
• As genetic tests move into the mainstream, challenges await for doctors and patients.

  2005cited by this paper
• BRCA1 and BRCA2 pathways and the risk of cancers other than breast or ovarian.

  2005cited by this paper
• The BOADICEA model of genetic susceptibility to breast and ovarian cancer

  2004cited by this paper
• Contralateral breast cancer in BRCA1 and BRCA2 mutation carriers.

  2004cited by this paper
• A breast cancer prediction model incorporating familial and personal risk factors

  2004cited by this paper
• Adjustment for competing risk in kin‐cohort estimation

  2003cited by this paper
• Application of breast cancer risk prediction models in clinical practice.

  2003cited by this paper
• Improved survival in women with BRCA‐associated ovarian carcinoma

  2003cited by this paper
• Lifetime risk for diabetes mellitus in the United States.

  2003cited by this paper
• The Statistical Analysis of Failure Time Data: Kalbfleisch/The Statistical

  2002cited by this paper
• Cancer Incidence in BRCA1 mutation carriers.

  2002cited by this paper
• Effects of violations of assumptions on likelihood methods for estimating the penetrance of an autosomal dominant mutation from kin-cohort studies

  2001cited by this paper
• Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

  2001cited by this paper
• Analysis of Multivariate Survival Data

  2001cited by this paper
• On semi-competing risks data

  2001cited by this paper
• Modeling Risk of Breast Cancer and Decisions about Genetic Testing

  1999cited by this paper
• Cancer risks in BRCA2 mutation carriers.

  1999cited by this paper
• Risk communication in genetic testing for cancer susceptibility.

  1999cited by this paper
• Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2.

  1998influential reference
• Probability of carrying a mutation of breast-ovarian cancer gene BRCA1 based on family history.

  1997cited by this paper
• Breast and ovarian cancer incidence in BRCA1-mutation carriers. Breast Cancer Linkage Consortium.

  1995cited by this paper
• Evaluating the yield of medical tests.

  1982cited by this paper
• The Statistical Analysis of Failure Time Data

  1980cited by this paper
• The Application of Bayesian Methods in Genetic Counselling

  1969cited by this paper
• Bmc Medical Genetics Incorporating Medical Interventions into Carrier Probability Estimation for Genetic Counseling

  year unknowncited by this paper

• Statistical methods for Mendelian models with multiple genes and cancers

  2021cites this paper
• Identification and characterization of de novo germline TP53 mutation carriers in families with Li-Fraumeni Syndrome

  2021cites this paper
• PANELPRO: A GENERAL FRAMEWORK FOR MULTI-GENE, MULTI-CANCER MENDELIAN RISK PREDICTION MODELS

  2021cites this paper
• A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome

  2020cites this paper
• A Pragmatic Testing-Eligibility Framework for Population Mutation Screening: The Example of BRCA1/2

  2019cites this paper
• Simpson's paradox in the integrated discrimination improvement

  2017cites this paper
• Modeling of successive cancer risks in Lynch syndrome families in the presence of competing risks using copulas

  2017cites this paper
• Adaptation of the Genetic Risk Prediction Model BRCAPRO for Primary Care Settings

  2017cites this paper
• Estimating TP53 Mutation Carrier Probability in Families with Li–Fraumeni Syndrome Using LFSPRO

  2017cites this paper
• A two-stage approach to genetic risk assessment in primary care

  2016cites this paper
• Additive gamma frailty models with applications to competing risks in related individuals

  2015cites this paper
• Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies

  2014cites this paper
• Reclassification of predictions for uncovering subgroup specific improvement

  2014cites this paper
• Extending Mendelian Risk Prediction Models to Handle Misreported Family History

  2014cites this paper
• Piecewise cause-specific association analyses of multivariate untied or tied competing risks data.

  2014cites this paper
• Piecewise Cause-Specific Association Analyses of Multivariate Untied or Tied Competing Risks Data

  2014cites this paper
• Providing access to risk prediction tools via the HL7 XML-formatted risk web service

  2013cites this paper
• Calibrated predictions for multivariate competing risks models

  2013cites this paper
• Simplifying clinical use of the genetic risk prediction model BRCAPRO

  2013cites this paper
• Assessing the added value of breast tumor markers in genetic risk prediction model BRCAPRO

  2012cites this paper
• Frailty‐Based Competing Risks Model for Multivariate Survival Data

  2011influential citation