2011
High Risk of Colorectal and Endometrial Cancer in Ashkenazi Families With the MSH2 A636P Founder Mutation
Mukherjee B, Rennert G, Ahn J, Dishon S, Lejbkowicz F, Rennert H, Shiovitz S, Moreno V, Gruber S. High Risk of Colorectal and Endometrial Cancer in Ashkenazi Families With the MSH2 A636P Founder Mutation. Gastroenterology 2011, 140: 1919-1926. PMID: 21419771, PMCID: PMC4835182, DOI: 10.1053/j.gastro.2011.02.071.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAgedAged, 80 and overCase-Control StudiesColorectal Neoplasms, Hereditary NonpolyposisEndometrial NeoplasmsFemaleFounder EffectGene FrequencyGenetic Predisposition to DiseaseGenetic TestingHeredityHumansIsraelJewsLikelihood FunctionsMaleMass ScreeningMiddle AgedMutationMutS Homolog 2 ProteinPedigreePenetrancePhenotypeProportional Hazards ModelsRegistriesRisk AssessmentRisk FactorsSex FactorsYoung AdultConceptsRisk of colorectal cancerHazard ratioColorectal cancerCumulative riskPopulation-basedLifetime risk of colorectal cancerCumulative risk of colorectal cancerEstimates of colorectal cancerAge-specific cumulative riskHigh risk of colorectalCases of colorectal cancerModified segregation analysisRisk of colorectalClinical genetics servicesClinic-based sampleEndometrial cancerRisk of ECCase-control studyGenetic servicesLynch syndromeCancer screeningEC riskLifetime riskAshkenazi familiesEstimated penetrance
2007
Semiparametric Bayesian Analysis of Case–Control Data under Conditional Gene-Environment Independence
Mukherjee B, Zhang L, Ghosh M, Sinha S. Semiparametric Bayesian Analysis of Case–Control Data under Conditional Gene-Environment Independence. Biometrics 2007, 63: 834-844. PMID: 17489972, DOI: 10.1111/j.1541-0420.2007.00750.x.Peer-Reviewed Original ResearchConceptsGene-environment independenceSemiparametric Bayesian approachTraditional logistic regression analysisParametric model assumptionsSemiparametric Bayesian modelCase-control studyPopulation-based case-control studySimulation studyBayesian approachRobust alternativeLogistic regression analysisUnderlying populationEfficient estimation techniqueBayesian modelEnvironmental exposuresModel assumptionsScientific evidenceRegression analysisAssociated with diseaseEstimation techniquesOvarian cancerControl populationPopulationIndependenceCovariates