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Updated: Jul 13, 2026
Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up
Published on: March 26, 2018
Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes
Luca Malcovati1, Ulrich Germing, Andrea Kuendgen
1Department of Hematology, University of Pavia, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Matteo, 27100 Pavia, Italy.
Purpose:
The aims of this study were to identify the most significant prognostic factors in myelodysplastic syndromes (MDS) taking into account both their values at clinical onset and their changes in time and to develop a dynamic model for predicting survival and leukemic evolution that can be applied at any time during the course of the disease.
Patients And Methods:
We studied a learning cohort of 426 MDS patients diagnosed at the Department of Hematology, San Matteo Hospital, Pavia, Italy, between 1992 and 2004, and a validation cohort of 739 patients diagnosed at the Heinrich-Heine-University Hospital, Düsseldorf, Germany, between 1982 and 2003. All patients were reclassified according to WHO criteria. Univariable and multivariable analyses were performed using Cox models with time-dependent covariates.
Results:
The most important variables for the prognostic model were WHO subgroups, karyotype, and transfusion requirement. We defined a WHO classification-based prognostic scoring system (WPSS) that was able to classify patients into five risk groups showing different survivals (median survival from 12 to 103 months) and probabilities of leukemic evolution (P < .001). WPSS was shown to predict survival and leukemia progression at any time during follow-up (P < .001), and its prognostic value was confirmed in the validation cohort.
Conclusion:
WPSS is a dynamic prognostic scoring system that provides an accurate prediction of survival and risk of leukemic evolution in MDS patients at any time during the course of their disease. This time-dependent system seems particularly useful in lower risk patients and may be used for implementing risk-adapted treatment strategies.
