Time-Dependent Prognostic Scoring System for Predicting Survival and Leukemic Evolution in Myelodysplastic Syndromes

Department of Hematology, University of Pavia, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Matteo, 27100 Pavia, Italy.
Journal of Clinical Oncology (Impact Factor: 18.43). 08/2007; 25(23):3503-10. DOI: 10.1200/JCO.2006.08.5696
Source: PubMed


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.
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.
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.
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.

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    • "Patients' performance status and fibrosis were graded by the Eastern Cooperative Oncology Group (ECOG) and European Myelofibrosis Network (EUMNET) [29] scores, respectively. Transfusion dependency was defined according to the WPSS [13] definition. "
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    ABSTRACT: Myelodysplastic syndromes (MDS) comprise bone marrow failure diseases with a diverse clinical outcome. For improved risk stratification, the International Prognostic Scoring System (IPSS) has recently been revised (IPSS-R). This single-centre study aimed to validate the IPSS-R and to evaluate prior prognostic scoring systems for MDS. We retrospectively analysed 363 patients diagnosed with MDS according to the FAB criteria between 2000 and 2012. The IPSS, MD Anderson Risk Model Score (MDAS), World Health Organisation (WHO)-classification based Prognostic Scoring System (WPSS), refined WPSS (WPSS-R), IPSS-R and MDS-Comorbidity Index (MDS-CI) were applied to 222 patients considered with primary MDS following the WHO criteria and their prognostic power was investigated. According to the IPSS-R, 18 (8%), 81 (37%), 50 (23%), 43 (19%) and 30 (13%) patients were classified as very low, low, intermediate, high and very high risk with, respectively, a median overall survival of 96 (95% Confidence interval (CI) not reached), 49 (95% CI 34-64), 22 (95% CI 0-49), 19 (95% CI 11-27) and 10 (95% CI 6-13) months (p<.000). The IPSS-R showed improved prognostic power as compared to the IPSS, MDAS, WPSS and WPSS-R. Furthermore, the MDS-CI refined the risk stratification of MDS patients stratified according to the IPSS-R. In conclusion, accounting for the disease status by means of the IPSS-R and comorbidity through the MDS-CI considerably improves the prognostic assessment in MDS patients. Copyright © 2014 Elsevier Ltd. All rights reserved.
    European journal of cancer (Oxford, England: 1990) 12/2014; 50(18):3198-205. DOI:10.1016/j.ejca.2014.09.016 · 5.42 Impact Factor
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    • "Recently, the revised IPSS (IPSS-R) [4] for MDS incorporates a new classification of cytogenetic abnormalities [5], severity of peripheral cytopenias and different cut-off percentages for BM blasts, allowing identification of five, instead of the former four risk categories. In addition, transfusion dependence (TD; defined as having at least one red blood cell transfusion every 8 weeks over a period of 4 months) and degree of anemia were incorporated by the WHO-based Prognosis Scoring System (WPSS) providing risk stratification at any time during the course of the disease [6] [7]. However, the concept of LR-MDS, defined as low and intermediate- 1 risk categories by the IPSS has several limitations. "
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    ABSTRACT: Scoring systems for lower-risk myelodysplastic syndrome (LR-MDS) recognize patients with a poorer than expected outcome. This study retrospectively analyzes the role of azacitidine in LR-MDS with adverse risk score and compared to an historical cohort treated with best supportive care or erythropoiesis-stimulating agents. Overall response to AZA was 40%. One and 2-year probabilities of survival were 62% and 45% for AZA vs. 25% and 11% (P=10(-4)). In a multivariable time-dependent analysis, response to AZA (CR/PR/HI) was associated with an improved survival (HR=0.234, 95% CI, 0.063-0.0863; P=0.029). Thrombocytopenia (<50×10(9)L(-1)) is confirmed as an adverse parameter in LR-MDS (HR=1.649, 95% CI, 1.012-2.687; P=0.045). Copyright © 2014 Elsevier Ltd. All rights reserved.
    Leukemia Research 10/2014; 39(1). DOI:10.1016/j.leukres.2014.10.004 · 2.35 Impact Factor
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    • "Current prognostic scoring systems for patients with MDS are mainly based on karyotypic abnormalities and certain clinical features that are used to stratify risk. Although existing systems such as the IPSS [4], Revised-IPSS [5] and WHO-classification-based Prognostic Scoring System (WPSS) [6] help to estimate patient outcomes and guide treatment decisions, there remains significant variability in prognosis. Hence, novel molecular markers may offer more precise cancer phenotypes and more accurate estimation of prognosis for MDS patients. "
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    ABSTRACT: Background Recent genomic sequencing efforts have identified a number of recurrent mutations in myelodysplastic syndromes (MDS) that may contribute to disease progression and overall survival, including mutations in isocitrate dehydrogenases 1 and 2 (IDH1 and IDH2). Methods Pretreatment bone marrow (BM) samples were acquired from mononuclear cells in 146 adult patients with de novo MDS from January 2006 to June 2013. Polymerase chain reaction (PCR) and direct sequencing were performed on exon 4 of IDH1/2 genes and mutation status was correlated with overall survival (OS) and leukemia-free survival (LFS). We then performed a meta-analysis combining previously published and current studies to explore the effect of IDH mutations on OS and LFS in MDS. Results In our study, somatic mutations of either IDH gene were discovered in 11 MDS patients (7.53%) and were significantly correlated with poorer OS (P = 0.007). IDH mutations were specifically associated with a poorer OS in the intermediate-1 risk group by the International Prognostic Scoring System (IPSS) (P = 0.039). In addition, we discovered decitabine achieved a better therapeutic effect compared to other treatments in IDH mutation-positive patients (P = 0.023). We identified six previous studies of IDH mutations in MDS. A meta-analysis of these studies included 111 MDS patients IDH mutations and 1671 MDS patients with wild-type IDH1/2. The hazard ratios (HRs) of OS and LFS for patients with IDH mutations were 1.62 (95% CI, 1.27–2.09) and 2.21 (95% CI, 1.48–3.30), respectively. Conclusion The results from our study and the meta-analysis provide firm evidence that IDH mutations are significantly associated with poorer clinical outcomes in MDS. Identification of IDH mutations may be pivotal for better risk stratification in MDS patients and improving IPSS score. Additionally, hypomethylating agents may be an effective treatment option for MDS patients with IDH mutations.
    PLoS ONE 06/2014; 9(6):e100206. DOI:10.1371/journal.pone.0100206 · 3.23 Impact Factor
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