2018
Subset-Based Analysis Using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes
Yu Y, Xia L, Lee S, Zhou X, Stringham H, Boehnke M, Mukherjee B. Subset-Based Analysis Using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes. Human Heredity 2018, 83: 283-314. PMID: 31132756, PMCID: PMC7034441, DOI: 10.1159/000496867.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesCholesterolCohort StudiesComputer SimulationC-Reactive ProteinFinlandGene FrequencyGene-Environment InteractionGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLipoproteins, LDLMeta-Analysis as TopicModels, GeneticPhenotypePolymorphism, Single NucleotideConceptsPresence of G-E interactionsGenetic associationHeterogeneity of genetic effectsDiscovery of genetic associationsGene-environment (G-EMarginal genetic effectsG-E interactionsGenome-wide association studiesGene-environment interactionsGenetic effectsData examplesSimulation studySingle nucleotide polymorphismsGene-environmentAssociation studiesAssociation analysisScreening toolMarginal associationNucleotide polymorphismsPresence of heterogeneityAssociationEnvironmental factorsIncreased powerMultiple studiesG-E
2014
The impact of exposure-biased sampling designs on detection of gene–environment interactions in case–control studies with potential exposure misclassification
Stenzel S, Ahn J, Boonstra P, Gruber S, Mukherjee B. The impact of exposure-biased sampling designs on detection of gene–environment interactions in case–control studies with potential exposure misclassification. European Journal Of Epidemiology 2014, 30: 413-423. PMID: 24894824, PMCID: PMC4256150, DOI: 10.1007/s10654-014-9908-1.Peer-Reviewed Original ResearchConceptsG-E interactionsExposure informationDetection of gene-environment interactionsPrevalence of exposureGene-environment interactionsSampling designCase-control studyRandom selection of subjectsPerformance of sampling designsCase-onlyExposure prevalenceJoint testExposure misclassificationCase-controlRare exposuresMarginal associationSelection of subjectsType I errorEmpirical simulation studyIdeal sampling schemesJoint effectsPrevalenceRandom selectionG-EMisclassification
2013
Incidence of Upgrading and Upstaging in Patients with Low-Volume Gleason Score 3+4 Prostate Cancers at Biopsy: Finding a New Group Eligible for Active Surveillance
Park H, Ha Y, Park S, Kim Y, Lee T, Kim J, Lee D, Kim W, Kim I. Incidence of Upgrading and Upstaging in Patients with Low-Volume Gleason Score 3+4 Prostate Cancers at Biopsy: Finding a New Group Eligible for Active Surveillance. Urologia Internationalis 2013, 90: 301-305. PMID: 23391718, DOI: 10.1159/000345292.Peer-Reviewed Original ResearchConceptsGleason score 3Prostate cancerRadical prostatectomyActive surveillanceScore 3Positive coresIncidence of upstagingPrediction of upgradingPSA cutoff levelPreoperative PSA levelUpstaging ratePSA levelsCancer involvementClinical stageNeedle biopsyUpstagingPatientsCutoff levelBiopsyMarginal associationIncidenceOverall rateCancerSurveillanceProstatectomy
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