A Novel Prognostic Scoring Model for Myelodysplastic Syndrome Patients With SF3B1 Mutation
Liya Ma1, Bin Liang2, Huixian Hu3
1Department of Hematology, The First Affiliated Hospital of Zhejiang University, Hangzhou, China.
Abstract:
The outcomes of myelodysplastic syndrome (MDS) patients with SF3B1 mutation, despite identified as a favorable prognostic biomarker, are variable. To comprehend the heterogeneity in clinical characteristics and outcomes, we reviewed 140 MDS patients with SF3B1 mutation in Zhejiang province of China. Seventy-three (52.1%) patients diagnosed as MDS with ring sideroblasts (MDS-RS) following the 2016 World Health Organization (WHO) classification and 118 (84.3%) patients belonged to lower risk following the revised International Prognostic Scoring System (IPSS-R). Although clonal hematopoiesis-associated mutations containing TET2, ASXL1 and DNMT3A were the most frequent co-mutant genes in these patients, RUNX1, EZH2, NF1 and KRAS/NRAS mutations had significant effects on overall survival (OS). Based on that we developed a risk scoring model as IPSS-R×0.4+RUNX1×1.1+EZH2×0.6+RAS×0.9+NF1×1.6. Patients were categorized into two subgroups: low-risk (L-R, score <= 1.4) group and high risk (H-R, score > 1.4) group. The 3-year OS for the L-R and H-R groups was 91.88% (95% CI, 83.27%-100%) and 38.14% (95% CI, 24.08%-60.40%), respectively (P<0.001). This proposed model distinctly outperformed the widely used IPSS-R. In summary, we constructed and validated a personalized prediction model of MDS patients with SF3B1 mutation that can better predict the survival of these patients.
Insights
A new risk model for myelodysplastic syndrome (MDS) with SF3B1 mutations improves survival prediction. This personalized model, incorporating genetic mutations, outperforms the existing IPSS-R, offering better patient stratification and management strategies for MDS patients.
Area of Science:
- Hematology
- Oncology
- Genetics
Background:
- Myelodysplastic syndromes (MDS) with SF3B1 mutations are characterized by variable outcomes despite being a favorable prognostic marker.
- Understanding the heterogeneity in clinical presentation and prognosis is crucial for effective patient management.
Purpose of the Study:
- To develop and validate a personalized risk scoring model for MDS patients harboring SF3B1 mutations.
- To improve the prediction of overall survival (OS) in this specific patient cohort.
Main Methods:
- Retrospective review of 140 MDS patients with SF3B1 mutations in Zhejiang province, China.
- Analysis of co-mutant genes and their impact on overall survival (OS).
- Development of a novel risk scoring model incorporating IPSS-R and specific gene mutations (RUNX1, EZH2, RAS, NF1).
Main Results:
- The new risk model effectively stratified patients into low-risk and high-risk subgroups.
- The 3-year OS differed significantly between the low-risk (91.88%) and high-risk (38.14%) groups (P<0.001).
- The proposed model demonstrated superior performance in predicting survival compared to the established IPSS-R.
Conclusions:
- A personalized prediction model for MDS patients with SF3B1 mutations has been successfully constructed and validated.
- This model offers enhanced accuracy in predicting survival, aiding in tailored treatment strategies and patient care.
- The findings highlight the importance of integrating genetic mutation data into risk stratification for MDS.
