2024
Artificial Intelligence-Powered Digital Pathology to Improve Diagnosis and Personalized Prognostic Assessment in Patient with Myeloid Neoplasms
Asti G, Curti N, Maggioni G, Carlini G, Lanino L, Campagna A, D'Amico S, Sauta E, Delleani M, Bonometti A, Lancellotti C, Rahal D, Ubezio M, Todisco G, Tentori C, Russo A, Crespi A, Figini G, Buizza A, Riva E, Zampini M, Brindisi M, Ficara F, Crisafulli L, Ventura D, Pinocchio N, Zazzetti E, Bicchieri M, Grondelli M, Forcina Barrero A, Savevski V, Santoro A, Santini V, Sole F, Platzbecker U, Fenaux P, Diez-Campelo M, Komrokji R, Haferlach T, Kordasti S, Di Tommaso L, Zeidan A, Loghavi S, Garcia-Manero G, Castellani G, Della Porta M. Artificial Intelligence-Powered Digital Pathology to Improve Diagnosis and Personalized Prognostic Assessment in Patient with Myeloid Neoplasms. Blood 2024, 144: 3598-3598. DOI: 10.1182/blood-2024-206248.Peer-Reviewed Original ResearchLeukemia-free survivalMyeloid neoplasmsOverall survivalConcordance indexGenomic informationBone marrowPredictive of overall survivalMD Anderson Cancer CenterCell typesProportion of patientsHarrell's concordance indexSomatic gene mutationsMorphological featuresHumanitas Research HospitalGenomic dataMGG smearsPersonalized risk assessmentRUNX1 mutationsBM aspiratesClinically relevant informationClinical entityBiopsy dataMN patientsPrognostic assessmentWhole slide images
2023
Data-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
2016
Hypomethylating Agent Therapy and Survival Among Older Patients with Chronic Myelomonocytic Leukemia in the United States: A Large Population-Based Study
Zeidan A, Hu X, Long J, Wang R, Huntington S, Podoltsev N, Gore S, Ma X, Davidoff A. Hypomethylating Agent Therapy and Survival Among Older Patients with Chronic Myelomonocytic Leukemia in the United States: A Large Population-Based Study. Blood 2016, 128: 394. DOI: 10.1182/blood.v128.22.394.394.Peer-Reviewed Original ResearchChronic myelomonocytic leukemiaMyelodysplastic syndromeSurvival benefitHigh-risk myelodysplastic syndromeDemonstrated survival benefitRetrospective cohort studyRisk myelodysplastic syndromesUse of HMAsAgent azacitidineLack of evidenceCohort studyClinical entityMyelomonocytic leukemiaBiologic evidenceOlder adultsAzacitidineUnited StatesHMAsEnd resultPatientsSyndromeLeukemiaDecitabineEpidemiology