Threefold IPSS-M reclassification outperforms original stratification in predicting post-transplant outcomes for MDS patients

The predictive performance of the Molecular International Prognostic Scoring System (IPSS-M) for high-risk myelodysplastic syndromes (MDS) patients undergoing transplantation remains uncertain. We retrospectively analyzed 86 MDS patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) at our center from 2016 to 2023. According to IPSS-M, patients were classified as Low (<i>n</i> = 3), Moderate-Low (<i>n</i> = 9), Moderate-High (<i>n</i> = 15), High (<i>n</i> = 28), and Very-High risk (<i>n</i> = 31). The IPSS-M did not demonstrate good prognostic accuracy for overall survival (OS) (<i>P</i> = 0.227) and disease-free survival (DFS) (<i>P</i> = 0.095) in these 86 patients. We then divided the patients into three groups based on their IPSS-M scores: IPSS-M < 0.56 (<i>n</i> = 28), IPSS-M 0.56-1.75 (<i>n</i> = 30), and IPSS-M>1.75 (<i>n</i> = 28). There was a significant difference in the long-term OS (<i>P</i> = 0.010) and DFS among the three groups (<i>P</i> < 0.001). This indicates that, based on the original IPSS-M scores, we may be able to find a more precise risk stratification for high-risk MDS patients undergoing allo-HSCT. Compared with TP53 wild-type and TP53 monoallelic mutations, TP53 biallelic mutations have a significant negative impact on OS and DFS (<i>P</i> = 0.016, <i>P</i> = 0.006). It is crucial to identify TP53 allelic status at diagnosis to distinguish these patients and determine the need for early involvement in clinical trials.

Authors

Institutions

Publication Details

Journal
Cell Transplantation
Published
2025-06-24
DOI
https://doi.org/10.1177/09636897251348406
Citations
2
Primary Topic
Acute Myeloid Leukemia Research
Type
article
Field-Weighted Citation Impact
3.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Threefold IPSS-M reclassification outperforms original stratification in predicting post-transplant outcomes for MDS patients

Ruowen Wei, Linghui Xia, Xiena Cao, Ao Zhang et al.
2 citations
Cell Transplantation
Acute Myeloid Leukemia Research
3.54
article

Threefold IPSS-M reclassification outperforms original stratification in predicting post-transplant outcomes for MDS patients

Ruowen Wei, Linghui Xia, Xiena Cao, Ao Zhang, Wei Shi, Hongru Chen, Shan Jiang
article en
2 citations

Abstract

The predictive performance of the Molecular International Prognostic Scoring System (IPSS-M) for high-risk myelodysplastic syndromes (MDS) patients undergoing transplantation remains uncertain. We retrospectively analyzed 86 MDS patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) at our center from 2016 to 2023. According to IPSS-M, patients were classified as Low (<i>n</i> = 3), Moderate-Low (<i>n</i> = 9), Moderate-High (<i>n</i> = 15), High (<i>n</i> = 28), and Very-High risk (<i>n</i> = 31). The IPSS-M did not demonstrate good prognostic accuracy for overall survival (OS) (<i>P</i> = 0.227) and disease-free survival (DFS) (<i>P</i> = 0.095) in these 86 patients. We then divided the patients into three groups based on their IPSS-M scores: IPSS-M < 0.56 (<i>n</i> = 28), IPSS-M 0.56-1.75 (<i>n</i> = 30), and IPSS-M>1.75 (<i>n</i> = 28). There was a significant difference in the long-term OS (<i>P</i> = 0.010) and DFS among the three groups (<i>P</i> < 0.001). This indicates that, based on the original IPSS-M scores, we may be able to find a more precise risk stratification for high-risk MDS patients undergoing allo-HSCT. Compared with TP53 wild-type and TP53 monoallelic mutations, TP53 biallelic mutations have a significant negative impact on OS and DFS (<i>P</i> = 0.016, <i>P</i> = 0.006). It is crucial to identify TP53 allelic status at diagnosis to distinguish these patients and determine the need for early involvement in clinical trials.

Cell TransplantationVol. 34
Union Hospital (HK), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation for Young Scientists of Shanxi Province
Good health and well-being
Openalex Percentile: Top 7%
Acute Myeloid Leukemia Research
3.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.