Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes.
Aziz NazhaRami S KomrokjiManja MeggendorferXuefei JiaNathan RadakovichJacob ShreveC Beau HiltonYasunubo NagataBetty K HamiltonSudipto MukherjeeNajla Al AliWencke WalterStephan HutterEric PadronDavid A SallmanTeodora KuzmanovicCassandra KerrVera AdemaDavid P SteensmaAmy DezernGail J RobozGuillermo Garcia ManeroHarry P ErbaClaudia HaferlachJaroslaw P MaciejewskiTorsten HaferlachMikkael A SekeresPublished in: Journal of clinical oncology : official journal of the American Society of Clinical Oncology (2021)
A personalized prediction model on the basis of clinical and genomic data outperformed established prognostic models in MDS. The new model was dynamic, predicting survival and leukemia transformation probabilities at different time points that are unique for a given patient, and can upstage and downstage patients into more appropriate risk categories.