Incorporating mutations and bone marrow fibrosis into the revised international prognostic scoring system in myelodysplastic syndromes

Abstract

The independent prognostic significance of bone marrow fibrosis (BMF) in myelodysplastic syndromes (MDS) is challenged under currently molecular prognostic models. In this study, the clinical and genetic data from 438 MDS patients were analyzed retrospectively. The patients were randomly divided into training (n = 306) and validation (n = 132) cohorts. The independent significant prognostic factors included age, IPSS-R, BMF, TP53 and U2AF1. Using their weighted coefficients, we developed a simplified prognostic system. Four risk groups were produced: low, intermediate, high and very high. The new model yielded more clearly separated survival curves than the IPSS-R. In addition, our model achieved higher C-indexes (0.61 in the training cohort and 0.63 in the validation cohort) than the IPSS-RM model (0.59 and 0.58) and IPSS-R (0.57 and 0.56). In conclusion, BMF was an independent significant prognostic factor for MDS, and adding BMF into the IPSS-R improved its predictive capability.

Keywords:

• Myelodysplastic syndromes
• prognosis
• bone marrow fibrosis
• model
• TP53

Ethics approval

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Shanghai Sixth People’s Hospital (protocol code 2021-033, date of approval 25 February 2021). All informed consent was obtained from the subjects

Author contributions

Y.Z. designed the research, collected the data and wrote the paper; C.C. and J.G. designed the research study and reviewed the paper; S.Z., R.W. and L.S. collected and analyzed the data. D.W. reviewed the paper.

Informed consent

All participants signed informed consent forms.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the Clinical Research Plan of SHDC (NO. SHDC2020CR6004) and the Program for Outstanding Medical Academic Leader (NO. 2019LJ16).