10.6084/M9.FIGSHARE.C.6252862.V1
Junying Wu
Junying
Wu
Chinese Academy of Medical Sciences & Peking Union Medical College
Yudi Zhang
Yudi
Zhang
Chinese Academy of Medical Sciences & Peking Union Medical College
Tiejun Qin
Tiejun
Qin
Chinese Academy of Medical Sciences & Peking Union Medical College
Zefeng Xu
Zefeng
Xu
Chinese Academy of Medical Sciences & Peking Union Medical College
Shiqiang Qu
Shiqiang
Qu
Chinese Academy of Medical Sciences & Peking Union Medical College
Lijuan Pan
Lijuan
Pan
Chinese Academy of Medical Sciences & Peking Union Medical College
Bing Li
Bing
Li
Chinese Academy of Medical Sciences & Peking Union Medical College
Yujiao Jia
Yujiao
Jia
Chinese Academy of Medical Sciences & Peking Union Medical College
Chengwen Li
Chengwen
Li
Chinese Academy of Medical Sciences & Peking Union Medical College
Huijun Wang
Huijun
Wang
Chinese Academy of Medical Sciences & Peking Union Medical College
Qingyan Gao
Qingyan
Gao
Chinese Academy of Medical Sciences & Peking Union Medical College
Wenyu Cai
Wenyu
Cai
Chinese Academy of Medical Sciences & Peking Union Medical College
Jingye Gong
Jingye
Gong
Chinese Academy of Medical Sciences & Peking Union Medical College
Songyang Zhao
Songyang
Zhao
Chinese Academy of Medical Sciences & Peking Union Medical College
Fuhui Li
Fuhui
Li
Chinese Academy of Medical Sciences & Peking Union Medical College
Robert Peter Gale
Robert Peter
Gale
Imperial College London
Zhijian Xiao
Zhijian
Xiao
Chinese Academy of Medical Sciences & Peking Union Medical College
IPSS-M has greater survival predictive accuracy compared with IPSS-R in persons ≥ 60 years with myelodysplastic syndromes
Abstract There are considerable new data on mutation topography in persons with myelodysplastic syndromes (MDS). These data have been used to update conventional risk models such as the Revised International Prognostic Scoring System (IPSS-R). Whether the molecular IPSS (IPSS-M) which includes these data improves survival prediction accuracy is untested. To answer this question, we compared survival prediction accuracies of the IPSS-R and IPSS-M in 852 consecutive subjects with de novo MDS. Concordance statistics (C-statistics) of the IPSS-R and IPSS-M in the entire cohort were similar, 0.67 (95% Confidence Interval [CI] 0.64, 0.71) and 0.68 (0.64, 0.71). Average numbers of mutations and of IPSS-M related mutations were greater in persons ≥ 60 years (2.0 [Interquartile Range [IQR], 1, 3] vs. 1.6 [0, 2], P = 0.003; 1.6 [0, 2] vs. 1.3 [0, 2], P = 0.006). Subjects ≥ 60 years had a higher incidence of mutations in RUNX1, TP53, TET2, SRSF2, DNMT3A, STAG2, EZH2 and DDX41. In contrast, mutations in U2AF1 were more common in persons < 60 years. Next we tested survival prediction accuracy based on age < or ≥ 60 years. C-statistics of the IPSS-R and IPSS-M in subjects ≥ 60 years were 0.66 (0.61, 0.71) and 0.69 (0.64, 0.73) whereas in subjects < 60 years they were 0.67 (0.61, 0.72) and 0.65 (0.59, 0.71). These data indicate an advantage for the IPSS-M over the IPSS-R in subjects ≥ 60 years but not in those < 60 years probably because of a great frequency of mutations correlated with survival in those ≥ 60 years.
Medicine
Genetics
Biotechnology
Mathematical Sciences not elsewhere classified
Cancer
figshare
2022
2022-10-18
2022-10-18
Collection
10.6084/m9.figshare.c.6252862
CC BY 4.0