2025
Validation and refinement of Society of Immunotherapy of Cancer (SITC) definitions for PD-(L)1 resistance: An analysis of more than 1,300 participants from SWOG.
Othus M, Kurzrock R, Patel S, Chae Y, Patel S, Sosman J, Snyder Charen A, Rizvi N, LaVallee T, Felquate D, Burton E, Futreal P, Sullivan R, Kluger H, Tawbi H. Validation and refinement of Society of Immunotherapy of Cancer (SITC) definitions for PD-(L)1 resistance: An analysis of more than 1,300 participants from SWOG. Journal Of Clinical Oncology 2025, 43: 2656-2656. DOI: 10.1200/jco.2025.43.16_suppl.2656.Peer-Reviewed Original ResearchOverall survivalMartingale residual plotsAdjuvant settingPD-(L)1Shorter OSNo significant differencePrimary resistanceAssociated with significantly shorter OSHazard ratioHigh-risk resected stagePD-(L)1 inhibitorsImmunotherapy of cancerSignificant differenceConfidence intervalsCox regression modelsClinical trial interpretationAdjuvant cohortAdjuvant pembrolizumabImmunotherapy resistanceLate recurrenceResected stageEarly recurrenceSWOG trialsIO agentsPatient cohort
2018
A Serum Protein Signature Associated with Outcome after Anti–PD-1 Therapy in Metastatic Melanoma
Weber JS, Sznol M, Sullivan RJ, Blackmon S, Boland G, Kluger HM, Halaban R, Bacchiocchi A, Ascierto PA, Capone M, Oliveira C, Meyer K, Grigorieva J, Asmellash SG, Roder J, Roder H. A Serum Protein Signature Associated with Outcome after Anti–PD-1 Therapy in Metastatic Melanoma. Cancer Immunology Research 2018, 6: 79-86. PMID: 29208646, DOI: 10.1158/2326-6066.cir-17-0412.Peer-Reviewed Original ResearchConceptsAcute phase reactantsCheckpoint inhibitorsOverall survivalPhase reactantsIpilimumab-treated patientsPD-1 blockadeTrials of nivolumabBetter overall survivalIndependent patient cohortsPretreatment serumPD-1Melanoma patientsValidation cohortMetastatic melanomaMultipeptide vaccinePatient cohortPooled analysisWorse outcomesClinical dataPatientsMultivariate analysisComplement cascadeMass spectrometry analysisNivolumabCohort
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
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