Literature DB >> 29707769

Prognostic scoring systems for myelodysplastic syndromes (MDS) in a population-based setting: a report from the Swedish MDS register.

Daniel Moreno Berggren1, Yasin Folkvaljon2, Marie Engvall3, Johan Sundberg1, Mats Lambe2,4, Petar Antunovic5, Hege Garelius6, Fryderyk Lorenz7, Lars Nilsson8, Bengt Rasmussen9, Sören Lehmann1, Eva Hellström-Lindberg10, Martin Jädersten10, Elisabeth Ejerblad1.   

Abstract

The myelodysplastic syndromes (MDS) have highly variable outcomes and prognostic scoring systems are important tools for risk assessment and to guide therapeutic decisions. However, few population-based studies have compared the value of the different scoring systems. With data from the nationwide Swedish population-based MDS register we validated the International Prognostic Scoring System (IPSS), revised IPSS (IPSS-R) and the World Health Organization (WHO) Classification-based Prognostic Scoring System (WPSS). We also present population-based data on incidence, clinical characteristics including detailed cytogenetics and outcome from the register. The study encompassed 1329 patients reported to the register between 2009 and 2013, 14% of these had therapy-related MDS (t-MDS). Based on the MDS register, the yearly crude incidence of MDS in Sweden was 2·9 per 100 000 inhabitants. IPSS-R had a significantly better prognostic power than IPSS (P < 0·001). There was a trend for better prognostic power of IPSS-R compared to WPSS (P = 0·05) and for WPSS compared to IPSS (P = 0·07). IPSS-R was superior to both IPSS and WPSS for patients aged ≤70 years. Patients with t-MDS had a worse outcome compared to de novo MDS (d-MDS), however, the validity of the prognostic scoring systems was comparable for d-MDS and t-MDS. In conclusion, population-based studies are important to validate prognostic scores in a 'real-world' setting. In our nationwide cohort, the IPSS-R showed the best predictive power.
© 2018 John Wiley & Sons Ltd.

Entities:  

Keywords:  International Prognostic Scoring System; WHO Classification-based Prognostic Scoring System; myelodysplastic syndrome; revised International Prognostic Scoring System; therapy-related myelodysplastic syndrome

Mesh:

Year:  2018        PMID: 29707769     DOI: 10.1111/bjh.15243

Source DB:  PubMed          Journal:  Br J Haematol        ISSN: 0007-1048            Impact factor:   6.998


  14 in total

1.  Comorbidities and malignancies negatively affect survival in myelodysplastic syndromes: a population-based study.

Authors:  Johanne Rozema; Mels Hoogendoorn; Robby Kibbelaar; Eva van den Berg; Nic Veeger; Eric van Roon
Journal:  Blood Adv       Date:  2021-03-09

2.  Patterns of transfusion burden in an unselected population of patients with myelodysplastic syndromes: A population-based study.

Authors:  Johanne Rozema; Eric N van Roon; Robby E Kibbelaar; Nic J G M Veeger; Christiaan L Slim; Harry de Wit; Mels Hoogendoorn
Journal:  Transfusion       Date:  2021-09-03       Impact factor: 3.337

3.  Guideline-based indicators for adult patients with myelodysplastic syndromes.

Authors:  Kristina Stojkov; Tobias Silzle; Georg Stussi; David Schwappach; Juerg Bernhard; David Bowen; Jaroslav Čermák; Avinash G Dinmohamed; Corien Eeltink; Sabrina Eggmann; Pierre Fenaux; Ulrich Germing; Manuel Haschke; Eva Hellstrom-Lindberg; Monika Heger; Arjan A van de Loosdrecht; Jakob Passweg; Michael Pfeilstöcker; Uwe Platzbecker; Luca Malcovati; António Medina de Almeida; Moshe Mittelman; Christine Morgenthaler; David P Steensma; Valeria Santini; Reinhard Stauder; Argiris Symeonidis; Sämi Schär; Charlotte Maddox; Theo de Witte; Julia Bohlius; Nicolas Bonadies
Journal:  Blood Adv       Date:  2020-08-25

4.  Genomic context and TP53 allele frequency define clinical outcomes in TP53-mutated myelodysplastic syndromes.

Authors:  Guillermo Montalban-Bravo; Rashmi Kanagal-Shamanna; Christopher B Benton; Caleb A Class; Kelly S Chien; Koji Sasaki; Kiran Naqvi; Yesid Alvarado; Tapan M Kadia; Farhad Ravandi; Naval Daver; Koichi Takahashi; Elias Jabbour; Gautham Borthakur; Naveen Pemmaraju; Marina Konopleva; Kelly A Soltysiak; Sherry R Pierce; Carlos E Bueso-Ramos; Keyur P Patel; Hagop Kantarjian; Guillermo Garcia-Manero
Journal:  Blood Adv       Date:  2020-02-11

Review 5.  Myelodysplastic syndromes: moving towards personalized management.

Authors:  Eva Hellström-Lindberg; Magnus Tobiasson; Peter Greenberg
Journal:  Haematologica       Date:  2020-05-21       Impact factor: 9.941

6.  Gender disparity in the survival of patients with primary myelodysplastic syndrome.

Authors:  Fangfang Wang; Jun Ni; Lei Wu; Ying Wang; Bin He; Duonan Yu
Journal:  J Cancer       Date:  2019-01-30       Impact factor: 4.207

Review 7.  Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes.

Authors:  Hussein Awada; Carmelo Gurnari; Arda Durmaz; Hassan Awada; Simona Pagliuca; Valeria Visconte
Journal:  Int J Mol Sci       Date:  2022-03-03       Impact factor: 5.923

Review 8.  Management of the Older Patient with Myelodysplastic Syndrome.

Authors:  Rory M Shallis; Amer M Zeidan
Journal:  Drugs Aging       Date:  2021-08-03       Impact factor: 3.923

Review 9.  EnvIRONmental Aspects in Myelodysplastic Syndrome.

Authors:  Verena Petzer; Igor Theurl; Günter Weiss; Dominik Wolf
Journal:  Int J Mol Sci       Date:  2021-05-14       Impact factor: 5.923

10.  The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records.

Authors:  Tine Bichel Lauritsen; Jan Maxwell Nørgaard; Kirsten Grønbæk; Anders Pommer Vallentin; Syed Azhar Ahmad; Louise Hur Hannig; Marianne Tang Severinsen; Kasper Adelborg; Lene Sofie Granfeldt Østgård
Journal:  Clin Epidemiol       Date:  2021-06-14       Impact factor: 4.790

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