Validation and Comparison of the Molecular International Prognostic Scoring System (IPSS-M) and the Revised International Prognostic Scoring System (IPSS-R) in Myelodysplastic Neoplasms (MDS): a Retrospective Study
Hematology (Amsterdam, Netherlands)（2025）
Abstract
Objectives To evaluate the prognostic value of the Molecular International Prognostic Scoring System (IPSS-M) compared to the Revised International Prognostic Scoring System (IPSS-R) in patients with myelodysplastic neoplasms (MDS) in the Jiangnan region of China.Methods A retrospective multicenter study analyzed data from 113 MDS patients across 10 centers in Jiangnan from 2019 to 2022. Patients were stratified using both IPSS-R and IPSS-M for prognostic comparison.Results Reclassification revealed that 63.7% of patients were shifted from their initial IPSS-R stratifications to IPSS-M categories. Survival analysis indicated significant differences in overall survival (OS) across risk groups, with shorter survival observed in higher-risk and older cohorts. Factors influencing OS included age (≥60), bone marrow blast percentage, IPSS-R chromosomal classification, and gene mutations. Receiver operating characteristic (ROC) analysis yielded areas under the curve (AUC) of 0.629 for IPSS-R and 0.705 for IPSS-M.Discussion This study reinforces the utility of IPSS-M for MDS prognosis, particularly in older patients, while acknowledging limitations such as a modest case number and variability in genetic testing methods.Conclusion IPSS-M demonstrates enhanced prognostic capability over IPSS-R for MDS patients, necessitating further validation in larger cohorts.
MoreTranslated text
Key words
IPSS-M,IPSS-R,myelodysplastic neoplasms (MDS),prognostic assessment,survival analysis
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined