2021
Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma
Moore MR, Friesner ID, Rizk EM, Fullerton BT, Mondal M, Trager MH, Mendelson K, Chikeka I, Kurc T, Gupta R, Rohr BR, Robinson EJ, Acs B, Chang R, Kluger H, Taback B, Geskin LJ, Horst B, Gardner K, Niedt G, Celebi JT, Gartrell-Corrado RD, Messina J, Ferringer T, Rimm DL, Saltz J, Wang J, Vanguri R, Saenger YM. Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma. Scientific Reports 2021, 11: 2809. PMID: 33531581, PMCID: PMC7854647, DOI: 10.1038/s41598-021-82305-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiopsyChemotherapy, AdjuvantClinical Decision-MakingDeep LearningFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedNeoplasm StagingPatient SelectionPrognosisRetrospective StudiesRisk AssessmentROC CurveSkinSkin NeoplasmsYoung AdultConceptsTumor-infiltrating lymphocytesDisease-specific survivalEarly-stage melanomaOpen-source deep learningCutoff valueMultivariable Cox proportional hazards analysisCox proportional hazards analysisDeep learningLow-risk patientsProportional hazards analysisKaplan-Meier analysisAccurate prognostic biomarkersEosin imagesAccuracy of predictionAdjuvant therapyRisk patientsSpecific survivalPrognostic valueValidation cohortReceiver operating curvesTraining cohortTIL analysisClinical trialsPrimary melanomaPrognostic biomarker
2019
Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes and Immunotherapy Outcome in Metastatic Melanoma
Wong PF, Wei W, Smithy JW, Acs B, Toki MI, Blenman K, Zelterman D, Kluger HM, Rimm DL. Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes and Immunotherapy Outcome in Metastatic Melanoma. Clinical Cancer Research 2019, 25: 2442-2449. PMID: 30617133, PMCID: PMC6467753, DOI: 10.1158/1078-0432.ccr-18-2652.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAntineoplastic Agents, ImmunologicalBiomarkersBiomarkers, TumorFemaleFluorescent Antibody TechniqueHumansImmunohistochemistryImmunotherapyKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedMolecular Targeted TherapyNeoplasm StagingROC CurveT-Lymphocyte SubsetsConceptsCell countTIL activationQuantitative immunofluorescenceLymphocytic infiltrationMelanoma patientsMetastatic melanomaAnti-PD-1 responseAnti-PD-1 therapyCell death 1 (PD-1) inhibitionAbsence of immunotherapyDeath-1 (PD-1) inhibitionDisease control rateProgression-free survivalCD8 cell countsTumor-Infiltrating LymphocytesNew predictive biomarkersWhole tissue sectionsRECIST 1.1Progressive diseaseDurable responsesObjective responsePartial responseImmunotherapy outcomesLymphocyte profilesMultivariable analysis
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