2020
Missing data in breast cancer: Relationship with survival in national databases.
Plichta J, Rushing C, Lewis H, Blazer D, Hyslop T, Greenup R. Missing data in breast cancer: Relationship with survival in national databases. Journal Of Clinical Oncology 2020, 38: e19114-e19114. DOI: 10.1200/jco.2020.38.15_suppl.e19114.Peer-Reviewed Original ResearchOverall survivalNational Cancer RegistryTumor variablesCancer RegistryBreast cancerLarge national cancer registryCox proportional hazards modelInvasive breast cancerPatterns of careInclusion/exclusion criteriaTreatment variablesProportional hazards modelRate of deathWorse OSOncology outcomesN stageOS differenceExclusion criteriaOutcome studiesHazards modelPatientsNCDBSurgery dataGreater riskNational database
2018
The Clinical Significance of Breast-only and Node-only Pathologic Complete Response (pCR) After Neoadjuvant Chemotherapy (NACT)
Fayanju O, Ren Y, Thomas S, Greenup R, Plichta J, Rosenberger L, Tamirisa N, Force J, Boughey J, Hyslop T, Hwang E. The Clinical Significance of Breast-only and Node-only Pathologic Complete Response (pCR) After Neoadjuvant Chemotherapy (NACT). Annals Of Surgery 2018, 268: 591-601. PMID: 30048319, PMCID: PMC6496955, DOI: 10.1097/sla.0000000000002953.Peer-Reviewed Original ResearchConceptsPathologic complete responseImproved overall survivalNeoadjuvant chemotherapyOverall survivalComplete responseBreast cancerHuman epidermal growth factor receptor 2 (HER2) statusEpidermal growth factor receptor 2 statusCox proportional hazards modelHormone receptorsNode-positive patientsTriple-negative diseaseKaplan-Meier curvesBreast cancer patientsMultivariate logistic regressionProportional hazards modelAnatomic extentCancer patientsReceptor subtypesClinical significanceHazards modelTumor subtypesPatientsBreastLogistic regressionAxillary Nodal Evaluation in Elderly Breast Cancer Patients: Potential Effects on Treatment Decisions and Survival
Tamirisa N, Thomas S, Fayanju O, Greenup R, Rosenberger L, Hyslop T, Hwang E, Plichta J. Axillary Nodal Evaluation in Elderly Breast Cancer Patients: Potential Effects on Treatment Decisions and Survival. Annals Of Surgical Oncology 2018, 25: 2890-2898. PMID: 29968029, PMCID: PMC6404232, DOI: 10.1245/s10434-018-6595-2.Peer-Reviewed Original ResearchConceptsBreast cancer patientsElderly breast cancer patientsCN0 breast cancerOverall survivalNodal surgeryCancer patientsAxillary surgeryElderly patientsTreatment decisionsBreast cancerCharlson-Deyo comorbidity scoreCN0 breast cancer patientsSurgical lymph node evaluationCox proportional hazards modelAdjuvant therapy decisionsAdjuvant therapy receiptAxillary nodal evaluationLymph node evaluationNational Cancer DatabaseYear of diagnosisWorse overall survivalEstrogen receptor statusLong-term outcomesSubsequent treatment decisionsProportional hazards modelThe Effect of Hospital Volume on Breast Cancer Mortality
Greenup R, Obeng-Gyasi S, Thomas S, Houck K, Lane W, Blitzblau R, Hyslop T, Hwang E. The Effect of Hospital Volume on Breast Cancer Mortality. Annals Of Surgery 2018, 267: 375-381. PMID: 27893532, PMCID: PMC5994238, DOI: 10.1097/sla.0000000000002095.Peer-Reviewed Original ResearchConceptsHigh-volume centersNational Cancer Data BaseHospital volumeVolume centersBreast cancerHazard ratioImproved survivalStage 0Case volumeMultivariable Cox proportional hazards modelsMultidisciplinary breast cancer treatmentMultivariable Cox proportional hazardsSurgeons National Cancer Data BaseCox proportional hazards modelAnnual hospital volumeLess common cancersUnilateral breast cancerBreast cancer mortalityBreast cancer patientsCubic spline analysisLog-rank testBreast cancer treatmentCox proportional hazardsProportional hazards modelHigher case volume
2017
A population-based analysis of treatment and outcomes in 2,500 metaplastic breast cancer patients.
Ong C, Thomas S, Campbell B, Greenup R, Plichta J, Rosenberger L, Force J, Hyslop T, Hwang E, Fayanju O. A population-based analysis of treatment and outcomes in 2,500 metaplastic breast cancer patients. Journal Of Clinical Oncology 2017, 35: 532-532. DOI: 10.1200/jco.2017.35.15_suppl.532.Peer-Reviewed Original ResearchMetaplastic breast cancerMBC patientsOverall survivalWorse OSHigher clinical T stageMetaplastic breast cancer patientsCox proportional hazards modelNational Cancer DatabaseClinical T stageBreast cancer patientsPopulation-based analysisProportional hazards modelAxillary dissectionTN patientsReceptor statusTN subtypeAggressive variantHigher proportionLuminal subtypeT stageTreatment patternsEntire cohortKaplan-MeierCancer patientsSubgroup analysisImpact of insurance status on treatment for stage 0-IV breast cancer.
Greenup R, Thomas S, Fayanju O, Hyslop T, Hwang E. Impact of insurance status on treatment for stage 0-IV breast cancer. Journal Of Clinical Oncology 2017, 35: 6532-6532. DOI: 10.1200/jco.2017.35.15_suppl.6532.Peer-Reviewed Original ResearchRisk of deathInsurance statusBreast cancerStage 0Private insuranceMultivariate Cox proportional hazards modelStage 1 breast cancerUninsured breast cancer patientsNational Cancer Data BaseCox proportional hazards modelUnilateral stage 0Receipt of chemotherapyReceipt of surgeryStage 4 diseaseReceipt of treatmentBreast cancer patientsProportional hazards modelBinary logistic regressionNeoadjuvant chemotherapyOncologic outcomesOverall survivalBilateral mastectomyMedian ageUninsured womenTreatment patterns