Identification of HSCT-benefiting patients using the HSCT-64 parallel-risk framework at diagnosis. (IMAGE)
Caption
(A) Comparison of risk ranks generated by aHSCT-64 and nHSCT-64 models in the independent cohort. Patients with a decreased risk rank under aHSCT-64 (blue) were predicted to benefit from HSCT, while those with an increased rank (red) were predicted as non-benefiting. (B) Among the predicted HSCT-benefiting subgroup, transplanted patients showed significantly better overall survival (OS) than non-transplanted patients. (C) In the HSCT-nonbenefiting subgroup, transplantation did not lead to a significant difference in OS. (D, E) Kaplan–Meier survival analysis comparing transplanted and non-transplanted patients in the high-risk subgroup defined by aHSCT-64 (D) and nHSCT-64 (E). (F, G) Kaplan–Meier survival analysis comparing transplanted and non-transplanted patients in the low-risk subgroup defined by aHSCT-64 (F) and nHSCT-64 (G). (H, I) Distributions of p-values (H) and HRs (I) among 1000-replicate bootstrap predicting cases as HSCT-benefiting and HSCT-nonbenefiting illustrated that the parallel-risk HSCT framework had more predictive stratification. (J, K) Risk distributions of genetic (gene fusion) subtypes assessed by aHSCT-64 (J) and nHSCT-64 (K), with subtypes ordered according to median risk. Differences in survival curves were evaluated using the log-rank test. HR: hazard ratio.
Credit
Yance Feng, Yali Shen, Ke Huang, Qian Li, Yu Tao, Rongqiu Liu, Liping Zhan, Hua Yang, Yang Xun , Yichao Xu, Wenli Tang, Binjun Xiong, Hui Shi, Liting Cheng, Li Wei, Hua You
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