BACKGROUND: Recent improvements in the treatment of Myelodysplastic Syndromes have fostered further interest in the development of prognostic scores. Prognostic indices such as the IPSS were developed and later validated assuming their predictive values to be unchanged over time. A systematic analysis of the possible variability of predictive power over time in different scores is still lacking and was the aim of this study. DESIGN AND METHODS: For 243 primary MDS patients from a single institution treated with supportive care, 19 established or modified scoring systems based on different prognostic factors (clinical, cytogenetical and/or comorbidity) were analysed for their variability over time by statistical methods that quantify time variations in the risk relations (specifically the risk ratios of Cox models) between prognostic subgroups. RESULTS: Established scores based mainly on clinical parameters showed strong to moderate loss of predictive power over time whereas cytogenetic scores maintained their predictive power. Scores including comorbidity data showed gain of predictive power over time. CONCLUSIONS: The development and comparison of prognostic systems have to take into account their stability versus the possibility or need for re-evaluation. Possibly not only re-evaluation after time is of importance, but also different weighting of items constituting scores.
BACKGROUND: Recent improvements in the treatment of Myelodysplastic Syndromes have fostered further interest in the development of prognostic scores. Prognostic indices such as the IPSS were developed and later validated assuming their predictive values to be unchanged over time. A systematic analysis of the possible variability of predictive power over time in different scores is still lacking and was the aim of this study. DESIGN AND METHODS: For 243 primary MDSpatients from a single institution treated with supportive care, 19 established or modified scoring systems based on different prognostic factors (clinical, cytogenetical and/or comorbidity) were analysed for their variability over time by statistical methods that quantify time variations in the risk relations (specifically the risk ratios of Cox models) between prognostic subgroups. RESULTS: Established scores based mainly on clinical parameters showed strong to moderate loss of predictive power over time whereas cytogenetic scores maintained their predictive power. Scores including comorbidity data showed gain of predictive power over time. CONCLUSIONS: The development and comparison of prognostic systems have to take into account their stability versus the possibility or need for re-evaluation. Possibly not only re-evaluation after time is of importance, but also different weighting of items constituting scores.
Authors: Peter L Greenberg; Heinz Tuechler; Julie Schanz; Guillermo Sanz; Guillermo Garcia-Manero; Francesc Solé; John M Bennett; David Bowen; Pierre Fenaux; Francois Dreyfus; Hagop Kantarjian; Andrea Kuendgen; Alessandro Levis; Luca Malcovati; Mario Cazzola; Jaroslav Cermak; Christa Fonatsch; Michelle M Le Beau; Marilyn L Slovak; Otto Krieger; Michael Luebbert; Jaroslaw Maciejewski; Silvia M M Magalhaes; Yasushi Miyazaki; Michael Pfeilstöcker; Mikkael Sekeres; Wolfgang R Sperr; Reinhard Stauder; Sudhir Tauro; Peter Valent; Teresa Vallespi; Arjan A van de Loosdrecht; Ulrich Germing; Detlef Haase Journal: Blood Date: 2012-06-27 Impact factor: 22.113
Authors: Michael Pfeilstöcker; Heinz Tuechler; Guillermo Sanz; Julie Schanz; Guillermo Garcia-Manero; Francesc Solé; John M Bennett; David Bowen; Pierre Fenaux; Francois Dreyfus; Hagop Kantarjian; Andrea Kuendgen; Luca Malcovati; Mario Cazzola; Jaroslav Cermak; Christa Fonatsch; Michelle M Le Beau; Marilyn L Slovak; Alessandro Levis; Michael Luebbert; Jaroslaw Maciejewski; Sigrid Machherndl-Spandl; Silvia M M Magalhaes; Yasushi Miyazaki; Mikkael A Sekeres; Wolfgang R Sperr; Reinhard Stauder; Sudhir Tauro; Peter Valent; Teresa Vallespi; Arjan A van de Loosdrecht; Ulrich Germing; Detlef Haase; Peter L Greenberg Journal: Blood Date: 2016-06-22 Impact factor: 22.113