2022
Factors associated with the quality of end-of-life care for patients with metastatic renal cell carcinoma.
Dzimitrowicz H, Wilson L, Jackson B, Spees L, Baggett C, Greiner M, Kaye D, Zhang T, George D, Scales C, Pritchard J, Leapman M, Gross C, Dinan M, Wheeler S. Factors associated with the quality of end-of-life care for patients with metastatic renal cell carcinoma. Journal Of Clinical Oncology 2022, 40: 300-300. DOI: 10.1200/jco.2022.40.6_suppl.300.Peer-Reviewed Original ResearchMetastatic renal cell carcinomaOral anti-cancer agentsRenal cell carcinomaSEER-MedicareDays of lifeSystemic therapyICU admissionCell carcinomaOdds ratioLife careSEER-Medicare cohortSystemic therapy useMultivariable logistic regressionUse of hospiceQuality of endHigh-quality endMRCC diagnosisAnti-cancer agentsMost patientsOlder patientsHospital admissionMedian ageTherapy useImmunotherapy treatmentRetrospective study
2019
Shared-patient physician networks and their impact on the uptake of genomic testing in breast cancer
Rotter J, Wilson L, Greiner MA, Pollack CE, Dinan M. Shared-patient physician networks and their impact on the uptake of genomic testing in breast cancer. Breast Cancer Research And Treatment 2019, 176: 445-451. PMID: 31028607, PMCID: PMC6556129, DOI: 10.1007/s10549-019-05248-2.Peer-Reviewed Original ResearchConceptsPatient-level analysisOncotype DXBreast cancerMedical oncologistsEarly-stage breast cancerGenomic testingPhysician networksODX testingMore patientsRetrospective studySEER-MedicareStudy criteriaSuboptimal treatmentCancer patientsMedian numberModifiable driversModifiable meansPatientsOncologistsLogistic mixed modelsEarly adoption periodWomenCancerPhysiciansGenomic assays
2018
Advanced imaging and hospice use in end-of-life cancer care
Dinan MA, Curtis LH, Setoguchi S, Cheung WY. Advanced imaging and hospice use in end-of-life cancer care. Supportive Care In Cancer 2018, 26: 3619-3625. PMID: 29728843, DOI: 10.1007/s00520-018-4223-0.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overBlack or African AmericanBreast NeoplasmsColorectal NeoplasmsComorbidityDiagnostic ImagingFemaleHospice CareHospicesHumansLung NeoplasmsMaleMedicareMiddle AgedNeoplasmsOutcome Assessment, Health CareProstatic NeoplasmsReferral and ConsultationRetrospective StudiesSEER ProgramTerminal CareUnited StatesConceptsHospital referral regionsHospice enrollmentComputerized tomographyHospice useLife careReferral regionsAdvanced imagingPopulation-based retrospective studyHigh rateLate hospice enrollmentLife cancer careMultivariable logistic regressionSEER-Medicare dataMagnetic resonance imagingPositron emission tomographyEnd of lifeGreater comorbidityReal-world practiceAggressive endBlack patientsMultivariable analysisRetrospective studyResultsA totalStudy criteriaCancer care
2017
Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset
Harowicz MR, Robinson TJ, Dinan MA, Saha A, Marks JR, Marcom PK, Mazurowski MA. Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset. Breast Cancer Research And Treatment 2017, 162: 1-10. PMID: 28064383, PMCID: PMC5909985, DOI: 10.1007/s10549-016-4093-4.Peer-Reviewed Original ResearchConceptsIntermediate-risk diseaseOncotype DX recurrence scoreHigh-risk diseaseDX recurrence scoreODX RSReceptor statusRecurrence scoreSurrogate markerProgesterone receptor statusInvasive breast cancerEstrogen receptor statusHigh-risk groupOngoing clinical trialsMagee EquationsPresence of patientsAdjuvant chemotherapyClinicopathologic dataRetrospective studyTumor sizeHER2 statusHistopathologic variablesClinical trialsBreast cancerPatient managementAdditional independent validation