2024
Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes
Komrokji R, Lanino L, Ball S, Bewersdorf J, Marchetti M, Maggioni G, Travaglino E, Al Ali N, Fenaux P, Platzbecker U, Santini V, Diez-Campelo M, Singh A, Jain A, Aguirre L, Tinsley-Vance S, Schwabkey Z, Chan O, Xie Z, Brunner A, Kuykendall A, Bennett J, Buckstein R, Bejar R, Carraway H, DeZern A, Griffiths E, Halene S, Hasserjian R, Lancet J, List A, Loghavi S, Odenike O, Padron E, Patnaik M, Roboz G, Stahl M, Sekeres M, Steensma D, Savona M, Taylor J, Xu M, Sweet K, Sallman D, Nimer S, Hourigan C, Wei A, Sauta E, D’Amico S, Asti G, Castellani G, Delleani M, Campagna A, Borate U, Sanz G, Efficace F, Gore S, Kim T, Daver N, Garcia-Manero G, Rozman M, Orfao A, Wang A, Foucar M, Germing U, Haferlach T, Scheinberg P, Miyazaki Y, Iastrebner M, Kulasekararaj A, Cluzeau T, Kordasti S, van de Loosdrecht A, Ades L, Zeidan A, Della Porta M, Syndromes I. Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes. The Lancet Haematology 2024, 11: e862-e872. PMID: 39393368, DOI: 10.1016/s2352-3026(24)00251-5.Peer-Reviewed Original ResearchGenomic featuresData-driven approachTP53 inactivationGenomic heterogeneityEntity labelsGenetic featuresDel(7q)/-7Myelodysplastic syndromeGenomic profilingData scientistsMutated SF3B1Cluster assignmentComplex karyotypeRUNX1 mutationsModified Delphi consensus processDel(5qIsolated del(5qAcute myeloid leukemiaData-drivenDelphi consensus processMarrow blasts
2023
Impact of Type of Hypomethylating Agent (HMA) Used on Outcomes of Patients (Pts) with Higher-Risk Myelodysplastic Syndromes/Neoplasms (HR-MDS) - a Large, Multicenter, Retrospective Analysis
Bewersdorf J, Kewan T, Blaha O, Stahl M, Al Ali N, DeZern A, Sekeres M, Uy G, Carraway H, Desai P, Griffiths E, Stein E, Brunner A, McMahon C, Zeidner J, Savona M, Stempel J, Chandhok N, Ramaswamy R, Roboz G, Rolles B, Wang E, Harris A, Amaya M, Hawkins H, Grenet J, Gurnari C, Shallis R, Xie Z, Maciejewski J, Sallman D, Della Porta M, Komrokji R, Zeidan A. Impact of Type of Hypomethylating Agent (HMA) Used on Outcomes of Patients (Pts) with Higher-Risk Myelodysplastic Syndromes/Neoplasms (HR-MDS) - a Large, Multicenter, Retrospective Analysis. Blood 2023, 142: 4613. DOI: 10.1182/blood-2023-178728.Peer-Reviewed Original ResearchCox multivariable regression modelOverall survivalHMA initiationHypomethylating agentMultivariable regression modelsTP53 mutationsAllo-HCTComplete remissionComplex karyotypePartner drugsBone marrowSurvival analysisAllogeneic hematopoietic cell transplantMultivariable Cox regression modelsTreatment typeOverall responseAdverse genetic featuresMedian overall survivalOutcomes of patientsHematopoietic cell transplantAdverse overall survivalKaplan-Meier methodCox regression modelLog-rank testPredictors of responseClinical Implications of TP53 Mutations/Allelic State in Patients (Pts) with Myelodysplastic Syndromes/Neoplasms (MDS) Treated with Hypomethylating Agents (HMA)- a Multicenter, Retrospective Analysis from the Validate Database
Kewan T, Bewersdorf J, Blaha O, Stahl M, Al Ali N, DeZern A, Sekeres M, Carraway H, Desai P, Griffiths E, Stein E, Brunner A, Amaya M, Zeidner J, Savona M, Stempel J, Chandhok N, Cochran H, Ramaswamy R, Singh A, Roboz G, Rolles B, Wang E, Harris A, Shallis R, Xie Z, Padron E, Maciejewski J, Della Porta M, Komrokji R, Sallman D, Zeidan A. Clinical Implications of TP53 Mutations/Allelic State in Patients (Pts) with Myelodysplastic Syndromes/Neoplasms (MDS) Treated with Hypomethylating Agents (HMA)- a Multicenter, Retrospective Analysis from the Validate Database. Blood 2023, 142: 1002. DOI: 10.1182/blood-2023-186875.Peer-Reviewed Original ResearchOverall response rateMedian overall survivalOverall survivalComplete responseHMA initiationHMA therapyMultivariable Cox proportional hazards regression modelsCox proportional hazards regression modelHigh-risk disease featuresComplex karyotypeProportional hazards regression modelsWorse overall survivalLog-rank testHazards regression modelsSignificant differencesLogistic regression modelsAllogenic HSCTBM biopsyHMA cyclesMDS-EBTherapy initiationMedian ageRegression modelsCR ratePoor outcomeData-Driven Harmonization of 2022 Who and ICC Classifications of Myelodysplastic Syndromes/Neoplasms (MDS): A Study By the International Consortium for MDS (icMDS)
Lanino L, Ball S, Bewersdorf J, Marchetti M, Maggioni G, Travaglino E, Al Ali N, Fenaux P, Platzbecker U, Santini V, Diez-Campelo M, Singh A, Jain A, Aguirre L, Tinsley-Vance S, Schwabkey Z, Chan O, Xie Z, Brunner A, Kuykendall A, Bennett J, Buckstein R, Bejar R, Carraway H, DeZern A, Griffiths E, Halene S, Hasserjian R, Lancet J, List A, Loghavi S, Odenike O, Padron E, Patnaik M, Roboz G, Stahl M, Sekeres M, Steensma D, Savona M, Taylor J, Xu M, Sweet K, Sallman D, Nimer S, Hourigan C, Wei A, Sauta E, D'Amico S, Asti G, Castellani G, Borate U, Sanz G, Efficace F, Gore S, Kim T, Daver N, Garcia-Manero G, Rozman M, Orfao A, Wang S, Foucar M, Germing U, Haferlach T, Scheinberg P, Miyazaki Y, Iastrebner M, Kulasekararaj A, Cluzeau T, Kordasti S, van de Loosdrecht A, Ades L, Zeidan A, Komrokji R, Della Porta M. Data-Driven Harmonization of 2022 Who and ICC Classifications of Myelodysplastic Syndromes/Neoplasms (MDS): A Study By the International Consortium for MDS (icMDS). Blood 2023, 142: 998. DOI: 10.1182/blood-2023-186580.Peer-Reviewed Original ResearchBlast countMost patientsTP53 mutationsTET2 mutationsChromosomal abnormalitiesMore TP53 mutationsBone marrow blastsGene mutationsSF3B1 mutationsClinical decision-making processHigh-risk mutationsMarrow blastsMultilineage dysplasiaPatient characteristicsAML patientsClinical entityInternational cohortSHAP analysisMDS casesPatientsClinical relevanceCytogenetic abnormalitiesClinical settingComplex karyotypeU2AF1 mutations