2022
Acceptance of Simulated Adult Patients With Medicaid Insurance Seeking Care in a Cancer Hospital for a New Cancer Diagnosis
Marks VA, Hsiang WR, Nie J, Demkowicz P, Umer W, Haleem A, Galal B, Pak I, Kim D, Salazar MC, Berger ER, Boffa DJ, Leapman MS. Acceptance of Simulated Adult Patients With Medicaid Insurance Seeking Care in a Cancer Hospital for a New Cancer Diagnosis. JAMA Network Open 2022, 5: e2222214. PMID: 35838668, PMCID: PMC9287756, DOI: 10.1001/jamanetworkopen.2022.22214.Peer-Reviewed Original ResearchConceptsNew cancer diagnosesMedicaid insuranceCancer careAdult patientsSkin cancerComprehensive community cancer programsMultivariable logistic regression modelMedicaid acceptanceCancer-accredited facilitiesCancer diagnosisCommunity cancer programsBreast cancer carePopulation of patientsState Medicaid expansion statusCancer care servicesFacility-level factorsAbility of patientsAmerican Hospital Association Annual SurveyMedicaid expansion statusHigh-quality careLogistic regression modelsCancer HospitalCommon cancerFindings highlight gapsCancer programs
2019
Benefit of combining local treatment and systemic therapy for stage IV NSCLC: Results from the National Cancer Database.
Dendy Case M, Uhlig J, Blasberg J, Boffa D, Chiang A, Gettinger S, Kim H. Benefit of combining local treatment and systemic therapy for stage IV NSCLC: Results from the National Cancer Database. Journal Of Clinical Oncology 2019, 37: 8545-8545. DOI: 10.1200/jco.2019.37.15_suppl.8545.Peer-Reviewed Original ResearchNon-small cell lung cancerNational Cancer DatabaseStage IV non-small cell lung cancerStage IV NSCLC patientsSystemic therapyOverall survivalSurgical resectionPatient demographicsNSCLC patientsCancer DatabaseMultivariable Cox proportional hazards modelsSquamous cell carcinoma patientsPropensity scoreMultivariable logistic regression modelCox proportional hazards modelSuperior overall survivalCell carcinoma patientsCell lung cancerLung cancer treatmentProportional hazards modelLogistic regression modelsLimited nodalTA patientsMetastatic diseaseMultivariable adjustment