2021
Expected Medium- and Long-Term Impact of the COVID-19 Outbreak in Oncology
Onesti CE, Tagliamento M, Curigliano G, Harbeck N, Bartsch R, Wildiers H, Tjan-Heijnen V, Martin M, Rottey S, Generali D, Campone M, Cristofanilli M, Pusztai L, Peeters M, Berchem G, Cortes J, Ruhstaller T, Ciruelos E, Rugo HS, Jerusalem G. Expected Medium- and Long-Term Impact of the COVID-19 Outbreak in Oncology. JCO Global Oncology 2021, 7: go.20.00589. PMID: 33529077, PMCID: PMC8081548, DOI: 10.1200/go.20.00589.Peer-Reviewed Original ResearchConceptsMedical oncologistsCOVID-19 positive patientsCOVID-19 outbreakUse of telemedicineClinical trial activityAffected modalityPalliative treatmentOncology unitLong-term impactNational registryPostacute phaseClinical activityMultidisciplinary meetingOncologic activityLocal registryHealthcare staffTreatment adaptationPatientsEarly cessationTrial activityHealthcare systemCOVID-19 pandemicOncologistsRegistrySignificant reduction
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 Society
2011
Multifactorial Approach to Predicting Resistance to Anthracyclines
Desmedt C, Di Leo A, de Azambuja E, Larsimont D, Haibe-Kains B, Selleslags J, Delaloge S, Duhem C, Kains JP, Carly B, Maerevoet M, Vindevoghel A, Rouas G, Lallemand F, Durbecq V, Cardoso F, Salgado R, Rovere R, Bontempi G, Michiels S, Buyse M, Nogaret JM, Qi Y, Symmans F, Pusztai L, D'Hondt V, Piccart-Gebhart M, Sotiriou C. Multifactorial Approach to Predicting Resistance to Anthracyclines. Journal Of Clinical Oncology 2011, 29: 1578-1586. PMID: 21422418, DOI: 10.1200/jco.2010.31.2231.Peer-Reviewed Original ResearchMeSH KeywordsAntibiotics, AntineoplasticAntigens, NeoplasmBiomarkers, TumorBiopsyBreast NeoplasmsChemotherapy, AdjuvantDNA Topoisomerases, Type IIDNA-Binding ProteinsDrug Resistance, NeoplasmEpirubicinEuropeFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedNeoadjuvant TherapyOdds RatioPatient SelectionPoly-ADP-Ribose Binding ProteinsPredictive Value of TestsProspective StudiesReceptor, ErbB-2Receptors, EstrogenReproducibility of ResultsRisk AssessmentRisk FactorsTexasTreatment FailureConceptsPathologic complete responseHuman epidermal growth factor receptor 2Neoadjuvant trialsTOP trialPredictive valueEstrogen receptor-negative tumorsEpidermal growth factor receptor 2High negative predictive valuePrimary end pointGrowth factor receptor 2Receptor-negative tumorsResponse/resistanceFactor receptor 2Negative predictive valueUseful clinical toolER-negative samplesA scoresAnthracycline monotherapyEvaluable patientsGene expression signaturesComplete responseBreast cancerImmune responseReceptor 2Patients