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Myelodysplastic syndrome

The IPSS-R more accurately captures fatigue severity of newly diagnosed patients with myelodysplastic syndromes compared with the IPSS index

Leukemia volume 34, pages 2451–2459 (2020)Cite this article

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Abstract

We aimed to compare fatigue of newly diagnosed patients with myelodysplastic syndromes (MDS) with that of the general population (GP). We also investigated the ability of the IPSS and IPSS-R to capture severity of patient-reported fatigue at diagnostic workup. A sample of 927 newly diagnosed patients with MDS was consecutively enrolled in a large international observational study and all patients completed the FACIT-Fatigue questionnaire at baseline. Fatigue was compared with that of the GP (N = 1075) and a 3-point difference in mean scores was considered as clinically meaningful. Fatigue of MDS patients was on average 4.6 points below the mean of the GP (95% CI, −5.9 to −3.2, p < 0.001), reflecting clinically meaningful worse fatigue. Unlike the IPSS, the IPSS-R identified clearly distinct subgroups with regard to burden of fatigue. Mean scores differences compared with GP ranged from nonclinically relevant for very low risk (Δ = −1.8, 95% CI, −4.0 to 0.5, p = 0.119) to large clinically meaningful differences for very high-risk IPSS-R patients (Δ = −8.2, 95% CI, −10.3 to −6.2, p < 0.001). At diagnostic workup, fatigue of MDS is clinically meaningful worse than that reported by the GP. Compared with the IPSS classification, the IPSS-R provides a better stratification of patients with regard to fatigue severity.

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Fig. 1: The Functional Assessment of Chronic Illness Therapy (FACIT) Fatigue Questionnaire.
Fig. 2: Cumulative distribution of FACIT-Fatigue scores in patients with MDS and the general adult population.
Fig. 3: Cumulative distribution of FACIT-Fatigue scores in patients with MDS by transfusion dependency and the general adult population.
Fig. 4: Mean differences in FACIT-Fatigue scores between MDS patients and the GP by IPSS-R risk classification.

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Acknowledgements

The authors gratefully acknowledge all patients who participated in GIMEMA-PROMYS Study for dedicating their time in completing quality of life questionnaires and having contributed in advancing knowledge in this research area. We also acknowledge the important contribution over the years to the coordination of the Data Management activities of Dr Francesco Sparano. LBO institutional affiliation has since changed to Health Outcomes and Behavior Program, Moffitt Cancer Center, Tampa, FL, USA.

Funding

Author LBO was funded by National Institutes of Health, National Cancer Institute training grant T32-CA-193193.

Author contributions

Conception and design: FE, FC, LBO, and DC. Data analysis and interpretation: all authors. Statistical analysis: FC, FE. Manuscript writing: FE, FC, LBO, and DC. Final approval of manuscript: all authors.

Author information

Authors and Affiliations

  1. Data Center and Health Outcomes Research Unit, Italian Group for Adult Haematologic Diseases (GIMEMA), Rome, Italy

    Fabio Efficace, Francesco Cottone, Paola Fazi & Marco Vignetti

  2. Department of Medical Social Sciences, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA

    Fabio Efficace, Laura B. Oswald & David Cella

  3. Division of Hematology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy

    Andrea Patriarca

  4. Hematology Unit, Sant’Eugenio Hospital, Rome, Italy

    Pasquale Niscola

  5. Division of Hematology, Department of Cellular Biotechnologies and Hematology, Sapienza University, Rome, Italy

    Massimo Breccia

  6. Clinic and Policlinic of Hematology and Cellular Therapy, Oncology and Hemostaseology, University Hospital Leipzig, Leipzig, Germany

    Uwe Platzbecker

  7. Dipartimento di Scienze Mediche, Chirurgiche e Tecnologie Avanzate “G.F. Ingrassia”, University of Catania, Catania, Italy

    Giuseppe A. Palumbo

  8. Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy

    Giovanni Caocci

  9. Department of Internal Medicine V (Hematology and Oncology), Innsbruck Medical University, Innsbruck, Austria

    Reinhard Stauder

  10. Hematology and Transplants Unit, University of Bari, Bari, Italy

    Alessandra Ricco

  11. Department of Hematology, Clinical Hospital Center Rijeka, Rijeka, Croatia

    Duska Petranovic

  12. Department of Hematology, CHU de Liège, University of Liege, Liege, Belgium

    Jo Caers

  13. University of Modena and Reggio Emilia, AOU Modena, Modena, Italy

    Mario Luppi

  14. Dipartimento Scienze Radiologiche Radioterapiche ed Ematologiche, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Roma, Italy

    Luana Fianchi

  15. Division of Hematology, Department of Oncology, AOU Città della Salute e della Scienza, Turin, Italy

    Chiara Frairia

  16. Hematology Unit, Azienda Unità Sanitaria Locale-IRCCS, Reggio Emilia, Italy

    Isabella Capodanno

  17. Department of Medicine and Surgery, University of Parma, Parma, Italy

    Elena Follini

  18. Hematology and Stem Cell Transplantation Unit, University Campus Bio-Medico, Rome, Italy

    Chiara Sarlo

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  1. Fabio Efficace
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Correspondence to Fabio Efficace.

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Conflict of interest

FE: Consultancy: Bristol-Myers Squibb, Amgen, Orsenix, Incyte, Takeda; Research funding to his insitution: Amgen. DC: President, FACIT.org. AP: Advisory board: Sanofi, Amgen, Novartis. GAP: Honoraria: Jannsen, Novartis, Celgene. ML: Consultancy: Abbvie, Gilead Sci, Novartis, Daiichi Sankyo, MSD, Sanofi; Honoraria for speaking: Gilead Sci, Novartis. MB: Honoraria: Novartis, Pfizer, Incyte, Celgene. RS: Honoraria, Membership on an entity’s Board of Directors or advisory committees: Novartis, Celgene; Research funding: Teva. UP: Research funding and Honoraria: Celgene, Amgen, Janssen, Novartis. MV: personal fees: Pfizer, Amgen, Novartis. DP: received support for active participation on congresses from Roche and Sanofi Genzyme.

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Efficace, F., Cottone, F., Oswald, L.B. et al. The IPSS-R more accurately captures fatigue severity of newly diagnosed patients with myelodysplastic syndromes compared with the IPSS index. Leukemia 34, 2451–2459 (2020). https://doi.org/10.1038/s41375-020-0746-8

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