AUTHOR=Ma Liya , Liang Bin , Hu Huixian , Yang Wenli , Lin Shengyun , Cao Lihong , Li Kongfei , Kuang Yuemin , Shou Lihong , Jin Weimei , Lan Jianping , Ye Xingnong , Le Jing , Lei Huyi , Fu Jiaping , Lin Ying , Jiang Wenhua , Zheng Zhiying , Jiang Songfu , Fu Lijuan , Su Chuanyong , Yin XiuFeng , Liu Lixia , Qin Jiayue , Jin Jie , Qian Shenxian , Ouyang Guifang , Tong Hongyan 

TITLE=A Novel Prognostic Scoring Model for Myelodysplastic Syndrome Patients With SF3B1 Mutation

JOURNAL=Frontiers in Oncology

VOLUME=12

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.905490

DOI=10.3389/fonc.2022.905490

ISSN=2234-943X

ABSTRACT=<p>The outcomes of myelodysplastic syndrome (MDS) patients with <italic>SF3B1</italic> 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 <italic>SF3B1</italic> 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 <italic>TET2</italic>, <italic>ASXL1</italic> and <italic>DNMT3A</italic> were the most frequent co-mutant genes in these patients, <italic>RUNX1, EZH2, NF1</italic> and <italic>KRAS/NRAS</italic> mutations had significant effects on overall survival (OS). Based on that we developed a risk scoring model as IPSS-R×0.4+<italic>RUNX1</italic>×1.1+<italic>EZH2</italic>×0.6+<italic>RAS</italic>×0.9+<italic>NF1</italic>×1.6. Patients were categorized into two subgroups: low-risk (L-R, score &lt;= 1.4) group and high risk (H-R, score &gt; 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&lt;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 <italic>SF3B1</italic> mutation that can better predict the survival of these patients.</p>