2022
Examination of Low ERBB2 Protein Expression in Breast Cancer Tissue
Fernandez AI, Liu M, Bellizzi A, Brock J, Fadare O, Hanley K, Harigopal M, Jorns JM, Kuba MG, Ly A, Podoll M, Rabe K, Sanders MA, Singh K, Snir OL, Soong TR, Wei S, Wen H, Wong S, Yoon E, Pusztai L, Reisenbichler E, Rimm DL. Examination of Low ERBB2 Protein Expression in Breast Cancer Tissue. JAMA Oncology 2022, 8: 1-4. PMID: 35113160, PMCID: PMC8814969, DOI: 10.1001/jamaoncol.2021.7239.Peer-Reviewed Original ResearchConceptsBreast cancer biopsiesT-DXdCancer biopsiesLarge randomized clinical trialsRandomized clinical trialsERBB2 protein expressionCentral pathology laboratoryBreast cancer tissuesAmerican Pathologists surveysStudy of concordanceTrastuzumab deruxtecanERBB2 positivityPatient populationClinical trialsScore 0Breast cancerImmunohistochemistry scoreCancer tissuesIHC assaysPatientsPathology laboratoryProtein expressionBiopsyIHCConcordance
2019
Examining the cost-effectiveness of baseline left ventricular function assessment among breast cancer patients undergoing anthracycline-based therapy
Abu-Khalaf MM, Safonov A, Stratton J, Wang S, Hatzis C, Park E, Pusztai L, Gross CP, Russell R. Examining the cost-effectiveness of baseline left ventricular function assessment among breast cancer patients undergoing anthracycline-based therapy. Breast Cancer Research And Treatment 2019, 176: 261-270. PMID: 31020471, DOI: 10.1007/s10549-019-05178-z.Peer-Reviewed Original ResearchConceptsIncremental cost-effectiveness ratioEquilibrium radionuclide angiographyCardiac risk factorsBreast cancer patientsVentricular function assessmentRisk factorsAbnormal LVEFBaseline LVEFCancer patientsBreast cancerFunction assessmentPotential cardiac risk factorsSelf-reported risk factorsAnthracycline-based therapyLeft ventricular function assessmentCoronary artery diseaseCost-effectiveness ratioArtery diseaseTrastuzumab therapyCardiac screeningPatient populationRadionuclide angiographyCardiotoxicity riskPayer perspectiveRetrospective analysis
2018
A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT)
Mateo J, Chakravarty D, Dienstmann R, Jezdic S, Gonzalez-Perez A, Lopez-Bigas N, Ng CKY, Bedard PL, Tortora G, Douillard J, Van Allen EM, Schultz N, Swanton C, André F, Pusztai L. A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT). Annals Of Oncology 2018, 29: 1895-1902. PMID: 30137196, PMCID: PMC6158764, DOI: 10.1093/annonc/mdy263.Peer-Reviewed Original ResearchConceptsESMO ScaleMolecular targetsClinical actionabilityPrecision Medicine Working GroupGenomic alterationsPrecision medicineRoutine clinical decisionEvidence-based criteriaMedicine Working GroupLack of evidencePreclinical evidenceClinical benefitClinical evidencePatient populationClassification systemClinical managementCancer precision medicineInvestigational targetsPatient managementMolecular aberrationsTumor typesClinical decisionClinical targetsAvailable evidenceEuropean SocietyTumor infiltrating lymphocytes and PD-L1 expression in pre- and post-treatment breast cancers in the SWOG S0800 Phase II neoadjuvant chemotherapy trial
Pelekanou V, Barlow WE, Nahleh Z, Wasserman B, Lo YC, von Wahlde MK, Hayes D, Hortobagyi GN, Gralow J, Tripathy D, Porter P, Szekely B, Hatzis C, Rimm DL, Pusztai L. Tumor infiltrating lymphocytes and PD-L1 expression in pre- and post-treatment breast cancers in the SWOG S0800 Phase II neoadjuvant chemotherapy trial. Molecular Cancer Therapeutics 2018, 17: molcanther.1005.2017. PMID: 29588392, PMCID: PMC6548451, DOI: 10.1158/1535-7163.mct-17-1005.Peer-Reviewed Original ResearchConceptsPD-L1 expressionPathologic complete responseTIL countPosttreatment tissuePD-L1Estrogen receptorImmune checkpoint inhibitor therapyPD-L1 positivity rateTumor-infiltrating lymphocyte countsDoxorubicin/cyclophosphamideCheckpoint inhibitor therapyPD-L1 levelsMol Cancer TherNab-paclitaxelLymphocyte countResidual cancerComplete responseER statusImmune changesInhibitor therapyCox regressionPatient populationControl armClinical trialsPositivity rate
2015
Clinical nomogram to predict bone-only metastasis in patients with early breast carcinoma
Delpech Y, Bashour SI, Lousquy R, Rouzier R, Hess K, Coutant C, Barranger E, Esteva FJ, Ueno NT, Pusztai L, Ibrahim NK. Clinical nomogram to predict bone-only metastasis in patients with early breast carcinoma. British Journal Of Cancer 2015, 113: 1003-1009. PMID: 26393887, PMCID: PMC4651124, DOI: 10.1038/bjc.2015.308.Peer-Reviewed Original ResearchConceptsNon-metastatic breast cancerBreast cancerClinical nomogramCox proportional hazards regression modelProportional hazards regression modelsBone-targeted therapiesHormone receptor statusEarly breast cancerLymph node statusLymphovascular space invasionEarly breast carcinomaAnalysis of patientsHazards regression modelsPathologic variablesReceptor statusDistant metastasisTumor characteristicsNode statusSpace invasionT classificationPatient populationMedical recordsBreast carcinomaCommon siteConcordance index
2011
First generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations
Iwamoto T, Lee JS, Bianchini G, Hubbard RE, Young E, Matsuoka J, Kim SB, Symmans WF, Hortobagyi GN, Pusztai L. First generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations. Breast Cancer Research And Treatment 2011, 130: 155. PMID: 21833625, DOI: 10.1007/s10549-011-1706-9.Peer-Reviewed Original ResearchConceptsLong-term survivalPrognostic gene signatureClinical variablesChemotherapy responseGenomic prognostic markersPrognostic markerPredictive valueKaplan-Meir survival curvesSignificant independent predictive valuePathologic complete responseProgression-free survivalLong-term followIndependent predictive valueSame patient cohortReceiver operator characteristic curveOperator characteristic curveOverall survivalPreoperative chemotherapyComplete responseNodal statusIndependent prognosticClinicopathological variablesPatient populationHER2 statusPatient cohort
2010
Nomogram to Predict Subsequent Brain Metastasis in Patients With Metastatic Breast Cancer
Graesslin O, Abdulkarim BS, Coutant C, Huguet F, Gabos Z, Hsu L, Marpeau O, Uzan S, Pusztai L, Strom EA, Hortobagyi GN, Rouzier R, Ibrahim NK. Nomogram to Predict Subsequent Brain Metastasis in Patients With Metastatic Breast Cancer. Journal Of Clinical Oncology 2010, 28: 2032-2037. PMID: 20308667, DOI: 10.1200/jco.2009.24.6314.Peer-Reviewed Original ResearchConceptsSubsequent brain metastasesBrain metastasesMetastatic breast cancerBreast cancerPatient populationMethods Electronic medical recordsStage IV breast cancerHuman epidermal growth factor receptor 2Shorter disease-free survivalEpidermal growth factor receptor 2Multivariate logistic regression analysisDisease-free survivalGrowth factor receptor 2Logistic regression analysisDesign of trialsFactor receptor 2Cross Cancer InstituteElectronic medical recordsInstitutional review boardMetastatic diseaseMetastatic sitesPrevention trialsPrognostic featuresClinical nomogramMedical records
2007
Pharmacogenomic Predictor Discovery in Phase II Clinical Trials for Breast Cancer
Pusztai L, Anderson K, Hess KR. Pharmacogenomic Predictor Discovery in Phase II Clinical Trials for Breast Cancer. Clinical Cancer Research 2007, 13: 6080-6086. PMID: 17947471, DOI: 10.1158/1078-0432.ccr-07-0809.Peer-Reviewed Original ResearchMeSH KeywordsAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsClinical Trials, Phase II as TopicGene Expression ProfilingGene Expression Regulation, NeoplasticHumansIn Situ Hybridization, FluorescenceOligonucleotide Array Sequence AnalysisPharmacogeneticsProbabilityRNA, MessengerTissue DistributionTrastuzumabConceptsPhase II studyPhase II trialII trialII studyBreast cancerTwo-stage phase II trialPhase II clinical trialPhase II trial designPredictors of responseMarker-positive patientsPhase II designUnselected patientsPatient populationClinical trialsTrastuzumab responseInsufficient responseTrial designResponse markersSame drugResponse rateMarker testingPotential predictorsMarker assessmentTrialsPatients