2,188
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

The burden of red blood cell transfusions in patients with lower-risk myelodysplastic syndromes and ring sideroblasts: an analysis of the prospective MDS-CAN registry

ORCID Icon, , ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, , , , , ORCID Icon, , , ORCID Icon, , , , ORCID Icon & ORCID Icon show all
Pages 651-661 | Received 05 Jul 2022, Accepted 03 Dec 2022, Published online: 06 Jan 2023

References

  • Mohamedali A, Gaken J, Twine NA, et al. Prevalence and prognostic significance of allelic imbalance by single-nucleotide polymorphism analysis in low-risk myelodysplastic syndromes. Blood. 2007;110(9):3365–3373.
  • Issa JP. The myelodysplastic syndrome as a prototypical epigenetic disease. Blood. 2013;121(19):3811–3817.
  • Cogle CR. Incidence and burden of the myelodysplastic syndromes. Curr Hematol Malig Rep. 2015;10(3):272–281.
  • Carraway HE, Saygin C. Therapy for lower-risk MDS. Hematology Am Soc Hematol Educ Program. 2020;2020(1):426–433.
  • Slack J, Nguyen L, Naugler C, et al. Incidence of myelodysplastic syndromes in a major Canadian metropolitan area. J Appl Lab Med. 2018;3(3):378–383.
  • Pfeilstocker M, Tuechler H, Sanz G, et al. Time-dependent changes in mortality and transformation risk in MDS. Blood. 2016;128(7):902–910.
  • Cuker A, Altman J, Gerds A, et al. editors. American society of hematology self-assessment program. 7th ed. Washington (DC): American Society of Hematology; 2019.
  • Li Z, Tang D, Tang J, et al. Estimating life-year loss of lower-risk myelodysplastic syndromes in. Europe. HemaSphere. 2019;3(S1):693.
  • 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–e344.
  • Starkman R, Alibhai A, Wells RA, et al. An MDS-specific frailty index based on cumulative deficits adds independent prognostic information to clinical prognostic scoring. Leukemia. 2020;34(5):1394–1406.
  • Wan BA, Nazha A, Starkman R, et al. Revised 15-item MDS-specific frailty scale maintains prognostic potential. Leukemia. 2020;34(12):3434–3438.
  • Fenaux P, Adès L. How we treat lower-risk myelodysplastic syndromes. Blood. 2013;121(21):4280–4286.
  • Santini V. Treatment of low-risk myelodysplastic syndromes. Hematology Am Soc Hematol Educ Program. 2016;2016(1):462–469.
  • Malcovati L, Porta MG, Pascutto C, et al. Prognostic factors and life expectancy in myelodysplastic syndromes classified according to WHO criteria: a basis for clinical decision making. J Clin Oncol. 2005;23(30):7594–7603.
  • Platzbecker U, Hofbauer LC, Ehninger G, et al. The clinical, quality of life, and economic consequences of chronic anemia and transfusion support in patients with myelodysplastic syndromes. Leuk Res. 2012;36(5):525–536.
  • Shenoy N, Vallumsetla N, Rachmilewitz E, et al. Impact of iron overload and potential benefit from iron chelation in low-risk myelodysplastic syndrome. Blood. 2014;124(6):873–881.
  • de Swart L, Crouch S, Hoeks M, EUMDS Registry Participants, et al. Impact of red blood cell transfusion dose density on progression-free survival in patients with lower-risk myelodysplastic syndromes. Haematologica. 2020;105(3):632–639.
  • Ohba R, Furuyama K, Yoshida K, et al. Clinical and genetic characteristics of congenital sideroblastic anemia: comparison with myelodysplastic syndrome with ring sideroblast (MDS-RS). Ann Hematol. 2013;92(1):1–9.
  • Patnaik MM, Tefferi A. Refractory anemia with ring sideroblasts (RARS) and RARS with thrombocytosis: 2019 update on diagnosis, risk-stratification, and management. Am J Hematol. 2019;94(4):475–488.
  • Park S, Hamel J-F, Toma A, et al. Outcome of lower-risk myelodysplastic syndrome with ring sideroblasts (MDS-RS) after failure of erythropoiesis-stimulating agents. Leuk Res. 2020;99:106472.
  • Vardiman JW, Thiele J, Arber DA, 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(5):937–951.
  • Cox DR. Regression models and life‐tables. J R Stat Soc B. 1972;34(2):187–202.
  • Zhang Z, Reinikainen J, Adeleke KA, et al. Time-varying covariates and coefficients in cox regression models. Ann Transl Med. 2018;6(7):121.
  • Breslow NE, Clayton DG. Approximate inference in generalized linear mixed models. J Am Stat Assoc. 1993;88(421):9–25.
  • Gelman A, Hill J. Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press; 2006.
  • Gelman A, Carlin JB, Stern HS, et al. Bayesian data analysis. Boca Raton (FL): CRC Press; 2013.
  • Bürkner PC. Advanced bayesian multilevel modeling with the R package brms. R Journal. 2018;10(1):395–411.
  • Kruschke JK. Rejecting or accepting parameter values in bayesian estimation. Adv Methods Pract Psychol Sci. 2018;1(2):270–280.
  • Wagenmakers E-J, Marsman M, Jamil T, et al. Bayesian inference for psychology. Part I: theoretical advantages and practical ramifications. Psychon Bull Rev. 2018;25(1):35–57.
  • Afrabandpey H, Peltola T, Piironen J, et al. A decision-theoretic approach for model interpretability in bayesian framework. Mach Learn. 2020;109(9-10):1855–1876.
  • R Core Team. R: a language and environment for statistical computing. Vienna, Austria: r Foundation for Statistical Computing; 2018.
  • von Elm E, Altman D, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. 2022 [Accessed 14 July 2022]. https://www.equator-network.org/reporting-guidelines/strobe/
  • Vandenbroucke JP, von Elm E, Altman DG, STROBE Initiative, et al. Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007;18(6):805–835.
  • de Swart L, Smith A, Fenaux P, et al. Management of 1000 patients with low- and intermediate-1 risk myelodysplastic syndromes in the European LeukemiaNet MDS registry. Leuk Res. 2011;35(Suppl 1):s3.
  • Germing U, Strupp C, Giagounidis A, et al. Evaluation of dysplasia through detailed cytomorphology in 3156 patients from the düsseldorf registry on myelodysplastic syndromes. Leuk Res. 2012;36(6):727–734.
  • de Swart L, Reiniers C, Bagguley T, EUMDS Steering Committee, et al. Labile plasma iron levels predict survival in patients with lower-risk myelodysplastic syndromes. Haematologica. 2018;103(1):69–79.
  • Stauder R, Yu G, Koinig KA, 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(6):1380–1392.
  • Malcovati L, Germing U, Kuendgen A, et al. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes. J Clin Oncol. 2007;25(23):3503–3510.
  • Arber DA, Orazi A, Hasserjian RP, et al. International consensus classification of myeloid neoplasms and acute leukemia: integrating morphological, clinical, and genomic data. Blood. 2022;140(11):1200–1228.
  • Khoury JD, Solary E, Abla O, et al. The 5th edition of the world health organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms. Leukemia. 2022;36(7):1703–1719.
  • Patnaik MM, Hanson CA, Sulai NH, et al. Prognostic irrelevance of ring sideroblast percentage in world health organization-defined myelodysplastic syndromes without excess blasts. Blood. 2012;119(24):5674–5677.
  • Patnaik MM, Lasho TL, Hodnefield JM, et al. SF3B1 mutations are prevalent in myelodysplastic syndromes with ring sideroblasts but do not hold independent prognostic value. Blood. 2012;119(2):569–572.