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.
This is a preview of subscription content
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–405.
Malcovati L, Hellstrom-Lindberg E, Bowen D, Ades L, Cermak J, Del Canizo C, et al. Diagnosis and treatment of primary myelodysplastic syndromes in adults: recommendations from the European LeukemiaNet. Blood. 2013;122:2943–64.
Steensma DP, Bennett JM. The myelodysplastic syndromes: diagnosis and treatment. Mayo Clin Proc. 2006;81:104–30.
Malcovati L, Germing U, Kuendgen A, Della Porta MG, Pascutto C, Invernizzi R, et al. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes. J Clin Oncol. 2007;25:3503–10.
Bejar R. Prognostic models in myelodysplastic syndromes. Hematol Am Soc Hematol Educ Program. 2013;2013:504–10.
Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G, et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood 1997;89:2079–88.
Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Sole F, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454–65.
Montalban-Bravo G, Garcia-Manero G. Myelodysplastic syndromes: 2018 update on diagnosis, risk-stratification and management. Am J Hematol. 2018;93:129–47.
Cheson BD, Bennett JM, Kantarjian H, Pinto A, Schiffer CA, Nimer SD, et al. Report of an international working group to standardize response criteria for myelodysplastic syndromes. Blood. 2000;96:3671–4.
Abel GA, Efficace F, Buckstein RJ, Tinsley S, Jurcic JG, Martins Y, et al. Prospective international validation of the Quality of Life in Myelodysplasia Scale (QUALMS). Haematologica. 2016;101:781–8.
Stauder R, Yu G, Koinig KA, Bagguley T, Fenaux P, Symeonidis A, et al. Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched reference populations: a European LeukemiaNet study. Leukemia. 2018;32:1380–92.
Sekeres MA, Gore SD, Stablein DM, DiFronzo N, Abel GA, DeZern AE, et al. The National MDS Natural History Study: design of an integrated data and sample biorepository to promote research studies in myelodysplastic syndromes. Leuk Lymphoma. 2019;60:3161–71.
Efficace F, Gaidano G, Breccia M, Criscuolo M, Cottone F, Caocci G, et al. Prevalence, severity and correlates of fatigue in newly diagnosed patients with myelodysplastic syndromes. Br J Haematol. 2015;168:361–70.
Steensma DP, Heptinstall KV, Johnson VM, Novotny PJ, Sloan JA, Camoriano JK, et al. Common troublesome symptoms and their impact on quality of life in patients with myelodysplastic syndromes (MDS): results of a large internet-based survey. Leuk Res. 2008;32:691–8.
Troy JD, de Castro CM, Pupa MR, Samsa GP, Abernethy AP, LeBlanc TW. Patient-reported distress in myelodysplastic syndromes and its association with clinical outcomes: a retrospective cohort study. J Natl Compr Canc Netw. 2018;16:267–73.
Efficace F, Gaidano G, Breccia M, Voso MT, Cottone F, Angelucci E, et al. Prognostic value of self-reported fatigue on overall survival in patients with myelodysplastic syndromes: a multicentre, prospective, observational, cohort study. Lancet Oncol. 2015;16:1506–14.
Platzbecker U. Treatment of MDS. Blood. 2019;133:1096–107.
Fenaux P, Platzbecker U, Ades L. How we manage adults with myelodysplastic syndrome. Br J Haematol. 2019. https://doi.org/10.1111/bjh.16206. [E-pub ahead of print].
Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood. 2002;100:2292–302.
Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114:937–51.
Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;85:365–76.
Yellen SB, Cella DF, Webster K, Blendowski C, Kaplan E. Measuring fatigue and other anemia-related symptoms with the functional assessment of cancer therapy (FACT) measurement system. J Pain Symptom Manag. 1997;13:63–74.
Cella D, Zagari MJ, Vandoros C, Gagnon DD, Hurtz HJ, Nortier JW. Epoetin alfa treatment results in clinically significant improvements in quality of life in anemic cancer patients when referenced to the general population. J Clin Oncol. 2003;21:366–73.
Cella D. The Functional Assessment of Cancer Therapy-Anemia (FACT-An) Scale: a new tool for the assessment of outcomes in cancer anemia and fatigue. Semin Hematol. 1997;34(3 Suppl 2):13–9.
Cella D, Eton DT, Lai JS, Peterman AH, Merkel DE. Combining anchor and distribution-based methods to derive minimal clinically important differences on the functional assessment of cancer therapy (FACT) anemia and fatigue scales. J Pain Symptom Manag. 2002;24:547–61.
Pfeilstocker M, Tuechler H, Sanz G, Schanz J, Garcia-Manero G, Sole F, et al. Time-dependent changes in mortality and transformation risk in MDS. Blood. 2016;128:902–10.
Sorror ML, Maris MB, Storb R, Baron F, Sandmaier BM, Maloney DG, et al. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106:2912–9.
Escalante CP, Chisolm S, Song J, Richardson M, Salkeld E, Aoki E, et al. Fatigue, symptom burden, and health-related quality of life in patients with myelodysplastic syndrome, aplastic anemia, and paroxysmal nocturnal hemoglobinuria. Cancer Med. 2019;8:543–53.
Abel GA, Buckstein R. Integrating frailty, comorbidity, and quality of life in the management of myelodysplastic syndromes. Am Soc Clin Oncol Educ Book. 2016;35:e337–44.
Santini V. Treatment of low-risk myelodysplastic syndromes. Hematol Am Soc Hematol Educ Program. 2016;2016:462–9.
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.
Author LBO was funded by National Institutes of Health, National Cancer Institute training grant T32-CA-193193.
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.
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.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
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
Content validity and psychometric evaluation of the Functional Assessment of Chronic Illness Therapy-Fatigue scale in patients with chronic lymphocytic leukemia
Journal of Patient-Reported Outcomes (2021)
Annals of Hematology (2021)