2022
2MO First-line (1L) nivolumab (NIVO) + ipilimumab (IPI) in metastatic non-small cell lung cancer (mNSCLC): Clinical outcomes and biomarker analyses from CheckMate 592
Gettinger S, Schenker M, De Langen J, Fischer J, Morgensztern D, Ciuleanu T, Beck T, De Castro Carpeno J, Schumann C, Yang X, Telivala B, Deschepper K, Nadal E, Schalper K, Spires T, Balli D, Nassar A, Karam S, Bhingare A, Spigel D. 2MO First-line (1L) nivolumab (NIVO) + ipilimumab (IPI) in metastatic non-small cell lung cancer (mNSCLC): Clinical outcomes and biomarker analyses from CheckMate 592. Immuno-Oncology Technology 2022, 16: 100107. DOI: 10.1016/j.iotech.2022.100107.Peer-Reviewed Original Research
2020
Biomarkers Associated with Beneficial PD-1 Checkpoint Blockade in Non–Small Cell Lung Cancer (NSCLC) Identified Using High-Plex Digital Spatial Profiling
Zugazagoitia J, Gupta S, Liu Y, Fuhrman K, Gettinger S, Herbst RS, Schalper KA, Rimm DL. Biomarkers Associated with Beneficial PD-1 Checkpoint Blockade in Non–Small Cell Lung Cancer (NSCLC) Identified Using High-Plex Digital Spatial Profiling. Clinical Cancer Research 2020, 26: 4360-4368. PMID: 32253229, PMCID: PMC7442721, DOI: 10.1158/1078-0432.ccr-20-0175.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerPD-1 checkpoint blockadeCell lung cancerCheckpoint blockadeLung cancerAdvanced non-small cell lung cancerUnivariate unadjusted analysisProgression-free survivalImmune cell countsMinority of patientsRobust predictive biomarkersBiomarkers of responseLarge independent cohortsSpatial profiling technologyDigital spatial profilingDigital spatial profiling (DSP) technologyOverall survivalClinical outcomesImmune predictorsHigher CD56NSCLC casesPredictive biomarkersUnadjusted analysesImmune parametersTissue microarray
2018
EGFR-Mutant Adenocarcinomas That Transform to Small-Cell Lung Cancer and Other Neuroendocrine Carcinomas: Clinical Outcomes
Marcoux N, Gettinger SN, O’Kane G, Arbour KC, Neal JW, Husain H, Evans TL, Brahmer JR, Muzikansky A, Bonomi PD, del Prete S, Wurtz A, Farago AF, Dias-Santagata D, Mino-Kenudson M, Reckamp KL, Yu HA, Wakelee HA, Shepherd FA, Piotrowska Z, Sequist LV. EGFR-Mutant Adenocarcinomas That Transform to Small-Cell Lung Cancer and Other Neuroendocrine Carcinomas: Clinical Outcomes. Journal Of Clinical Oncology 2018, 37: 278-285. PMID: 30550363, PMCID: PMC7001776, DOI: 10.1200/jco.18.01585.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma of LungAdultAgedAged, 80 and overAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorCarcinoma, Non-Small-Cell LungClass I Phosphatidylinositol 3-KinasesErbB ReceptorsFemaleGenetic Predisposition to DiseaseHumansLung NeoplasmsMaleMiddle AgedMutationNeoplasm GradingNorth AmericaPhenotypeRetinoblastoma Binding ProteinsRetrospective StudiesSmall Cell Lung CarcinomaTime FactorsTreatment OutcomeTumor Suppressor Protein p53Ubiquitin-Protein LigasesConceptsNon-small cell lung cancerSmall cell lung cancerEGFR-mutant non-small cell lung cancerSCLC transformationLung cancerNeuroendocrine carcinomaEGFR mutationsDe novo small cell lung cancersInitial lung cancer diagnosisHigh-grade neuroendocrine carcinomaEGFR tyrosine kinase inhibitorsT790M positivityMedian overall survivalCell lung cancerTyrosine kinase inhibitorsHigh response rateEGFR-mutant adenocarcinomaLung cancer diagnosisCNS metastasesCheckpoint inhibitorsMedian survivalOverall survivalClinical courseMixed histologyClinical outcomes
2017
1531PD Clinical outcomes for EGFR-mutant adenocarcinomas (AC) that transform to small cell lung cancer (SCLC)
Marcoux N, Piotrowska Z, Farago A, Hata A, Mooradian M, Drapkin B, Muzikansky A, Gettinger S, Mino-Kenudson M, Sequist L. 1531PD Clinical outcomes for EGFR-mutant adenocarcinomas (AC) that transform to small cell lung cancer (SCLC). Annals Of Oncology 2017, 28: v540-v541. DOI: 10.1093/annonc/mdx386.005.Peer-Reviewed Original Research
2015
An Advanced Practice Nurse Coordinated Multidisciplinary Intervention for Patients with Late-Stage Cancer: A Cluster Randomized Trial
McCorkle R, Jeon S, Ercolano E, Lazenby M, Reid A, Davies M, Viveiros D, Gettinger S. An Advanced Practice Nurse Coordinated Multidisciplinary Intervention for Patients with Late-Stage Cancer: A Cluster Randomized Trial. Journal Of Palliative Medicine 2015, 18: 962-969. PMID: 26305992, PMCID: PMC4638201, DOI: 10.1089/jpm.2015.0113.Peer-Reviewed Original ResearchConceptsLate-stage cancerSelf-reported clinical outcomesSecondary outcomesPalliative carePatient outcomesMonths postbaselinePrimary patient-reported outcomesEarly palliative careComprehensive cancer carePatient-reported outcomesAdvanced practice nursesWhole patient careLinear mixed model analysisUsual carePrimary outcomeClinical outcomesMultidisciplinary clinicPractice nursesCancer careClinic levelMultidisciplinary interventionTrial designMixed model analysisGeneral linear mixed model analysisTranslational studies
2013
A Clinical Model for Identifying Radiosensitive Tumor Genotypes in Non–Small Cell Lung Cancer
Johung KL, Yao X, Li F, Yu JB, Gettinger SN, Goldberg S, Decker RH, Hess JA, Chiang VL, Contessa JN. A Clinical Model for Identifying Radiosensitive Tumor Genotypes in Non–Small Cell Lung Cancer. Clinical Cancer Research 2013, 19: 5523-5532. PMID: 23897899, DOI: 10.1158/1078-0432.ccr-13-0836.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAnaplastic Lymphoma KinaseAntineoplastic AgentsBrain NeoplasmsCarcinoma, Non-Small-Cell LungErbB ReceptorsFemaleGenotypeHumansLung NeoplasmsMaleMiddle AgedMutationProtein Kinase InhibitorsRadiation ToleranceReceptor Protein-Tyrosine KinasesRecurrenceTranslocation, GeneticTumor BurdenConceptsNon-small cell lung cancerCell lung cancerEML4-ALK translocationGamma knife treatmentLocal controlTumor genotypeLung cancerEGFR mutationsCox proportional hazards modelDistant brain controlDistant brain recurrenceGamma knife radiotherapyEGFR kinase domain mutationsSuperior local controlField local controlKRAS mutation statusProportional hazards modelKinase domain mutationsEGF receptorMetastasis sizeBrain recurrenceBrain metastasesField recurrenceClinical outcomesIndependent predictors