Risk stratification based on both disease status and extra-hematologic comorbidities in patients with myelodysplastic syndrome

Porta, Matteo Giovanni Della; Malcovati, Luca; Strupp, Corinna; Ambaglio, Ilaria; Kuendgen, Andrea; Zipperer, Esther; Travaglino, Erica; Invernizzi, Rosangela; Pascutto, Cristiana; Lazzarino, Mario; Germing, Ulrich; Cazzola, Mario

doi:10.3324/haematol.2010.033506

Cited by 213 publications

(113 citation statements)

References 35 publications

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“…39,40 In our cohort, a higher Charlson score increased mortality in univariate analysis only. This is likely because our cohort may have substantially less comorbidity than other populations.…”

Section: Discussionmentioning

confidence: 55%

Non-hematologic predictors of mortality improve the prognostic value of the international prognostic scoring system for MDS in older adults

Fega

Abel

Motyckova

et al. 2015

Journal of Geriatric Oncology

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Objectives-The International Prognostic Scoring System (IPSS) is commonly used to predict survival and assign treatment for the myelodysplastic syndromes (MDS). We explored whether self-reported and readily available non-hematologic predictors of survival add independent prognostic information to the IPSS. Materials and Methods-Retrospective Disclosures and Conflict of Interest StatementThe authors report no circumstance or competing interest that could be construed or perceived as influencing the interpretation of the results. Dr. Richard M Stone has served in a Consultant or Advisory Role for Genzyme © and has received investigator-initiated research funding from Novartis. Dr. Daniel J. DeAngelo has served in a consultant or advisory role for Novartis ©. Author Contributions Sponsor's RoleThe funders of this project had no role in the design, methods, subject recruitment, data collections, analysis and preparation of paper. HHS Public Access Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript extracted clinical-pathologic data from medical records. Kaplan-Meier and Cox proportional hazards models were used to estimate survival.Results-One hundred fourteen patients consented and were available for analysis. Median age was 73 years, and the majority of patients were White, were male, and had a Charlson comorbidity score of <2. Few patients (24%) had an IPSS score consistent with lower-risk disease and the majority received chemotherapy. In addition to IPSS score and history of prior chemotherapy or radiation, significant univariate predictors of survival included low serum albumin, Charlson score, performance status, ability to take a long walk, and interference of physical symptoms in family life. The multivariate model that best predicted mortality included low serum albumin (HR = 2.3; 95% CI: 1.06-5.14), therapy-related MDS (HR = 2.1; 95% CI: 1.16-4.24), IPSS score (HR = 1.7; 95% CI: 1.14-2.49), and ease taking a long walk (HR = 0.44; 95% CI: 0.23-0.90).Conclusions-In this study of older adults with MDS, we found that low serum albumin and physical function added important prognostic information to the IPSS score. Self-reported physical function was more predictive than physician-assigned performance status.

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Section: Discussionmentioning

confidence: 55%

Non-hematologic predictors of mortality improve the prognostic value of the international prognostic scoring system for MDS in older adults

Fega

Abel

Motyckova

et al. 2015

Journal of Geriatric Oncology

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“…Disease stage was already included as part of a risk score defined for CML in 1998 (Gratwohl et al 1998) and also contributes to disease-specific (Shaw et al 2001;la Porta et al 2011;Scott et al 2012;Sorror et al 2007) and non-disease-specific (Gratwohl et al 2009) risk scores in other haematological disorders. In this study, a simple stratification between conventional (untreated MDS, CR1 and CP1) and advanced disease (beyond normal risk) was able to predict OS, EFS and RI (trend) in multivariate analysis, regardless of whether patients were transplanted from antigen-matched or mismatched donors.…”

Section: Discussionmentioning

confidence: 99%

Comparable outcome after single-antigen-mismatched versus matched unrelated donor haematopoietic cell transplantation

Rockstroh

Al-Ali

Lange

et al. 2015

J Cancer Res Clin Oncol

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“…The Charlson comorbidity index (CI) and haematopoietic stem-cell transplantation-specific comorbidity index (HCT-CI) were both prognostic for OS in MDS (30, 71). The MDS comorbidity index (MDS-CI), consisting of cardiac, liver, renal, and pulmonary disease and solid tumours was developed and validated as a time-dependent tool for OS and non-leukemic death prognostication in MDS (72, 73). Subsequent work has shown that the model may be additive to the IPSS, WPSS, and IPSS-R (72, 74, 75).…”

Section: Current Mds Prognostic Scoring Systems and Risk Modelsmentioning

confidence: 99%

“…The MDS comorbidity index (MDS-CI), consisting of cardiac, liver, renal, and pulmonary disease and solid tumours was developed and validated as a time-dependent tool for OS and non-leukemic death prognostication in MDS (72, 73). Subsequent work has shown that the model may be additive to the IPSS, WPSS, and IPSS-R (72, 74, 75). Another model, the Adult Comorbidity Evaluation-27 (ACE-27), was shown to add to the prognostic ability of both the IPSS and IPSS-R, with the most pronounced effect on prognosis in intermediate and higher-risk groups (76, 77).…”

Section: Current Mds Prognostic Scoring Systems and Risk Modelsmentioning

confidence: 99%

MDS prognostic scoring systems – Past, present, and future

Jonas

Greenberg

2015

Best Practice & Research Clinical Haematology

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The myelodysplastic syndromes (MDS) are a heterogeneous group of clonal myeloid haemopathies characterized by defective differentiation of hematopoietic cells and expansion of the abnormal clone. This leads to the bone marrow failure with resulting peripheral blood cytopenias and evolution to or toward acute myeloid leukaemia that characterise MDS clinically. The clinical heterogeneity of MDS has led several groups to analyse patient and clinical characteristics to develop prognostic scoring systems yielding estimates of overall and leukaemia-free survival to guide clinical decision-making. These models have evolved over time as our understanding of the pathogenesis, natural history, and treatment of MDS has improved. Rapid advances in flow cytometric analysis, adjuncts to standard metaphase cytogenetics, and gene mutation analysis are revolutionizing our understanding of MDS pathogenesis and prognosis. Despite the existence of multiple well-validated prognostic scoring systems, further needed refinements of current models with these new sources of prognostic data are described.

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Risk stratification based on both disease status and extra-hematologic comorbidities in patients with myelodysplastic syndrome

Cited by 213 publications

References 35 publications

Non-hematologic predictors of mortality improve the prognostic value of the international prognostic scoring system for MDS in older adults

Non-hematologic predictors of mortality improve the prognostic value of the international prognostic scoring system for MDS in older adults

Comparable outcome after single-antigen-mismatched versus matched unrelated donor haematopoietic cell transplantation

MDS prognostic scoring systems – Past, present, and future

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