2010
Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models
Parisi F, González A, Nadler Y, Camp RL, Rimm DL, Kluger HM, Kluger Y. Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models. Breast Cancer Research 2010, 12: r66. PMID: 20809974, PMCID: PMC3096952, DOI: 10.1186/bcr2633.Peer-Reviewed Original ResearchConceptsNottingham Prognostic IndexClinico-pathological variablesPrognostic indexCox modelPrognostic modelMultivariate Cox regression modelEarly-stage breast cancerBreast cancer patient cohortsAdjuvant chemotherapy decisionsMultivariate Cox modelStage breast cancerCox regression modelCancer patient cohortsTime-dependent areaBreast cancer prognostic modelsCancer prognostic modelsNPI groupOncotype DXPatient cohortChemotherapy decisionsPrognostic markerBackward selection procedureBreast cancerQuantitative immunofluorescence methodImmunofluorescence method
2004
Automated Quantitative Analysis of Tissue Microarrays Reveals an Association between High Bcl-2 Expression and Improved Outcome in Melanoma
DiVito KA, Berger AJ, Camp RL, Dolled-Filhart M, Rimm DL, Kluger HM. Automated Quantitative Analysis of Tissue Microarrays Reveals an Association between High Bcl-2 Expression and Improved Outcome in Melanoma. Cancer Research 2004, 64: 8773-8777. PMID: 15574790, DOI: 10.1158/0008-5472.can-04-1387.Peer-Reviewed Original ResearchConceptsBcl-2 expressionHigh Bcl-2 expressionTissue microarrayMetastatic specimensResponse rateSmall cohortProgression-free survivalImproved response ratesLarge patient cohortMelanoma patientsClark levelEntire cohortBreslow depthClinical variablesPatient cohortMetastatic melanomaContinuous index scoreBetter outcomesIndex scoreMelanoma specimensCohortMelanomaBcl-2PatientsOutcomes