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. 2021 Oct 22;11:756096. doi: 10.3389/fonc.2021.756096

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Copyright © 2021 Wang, Gu, Zhang, Zhou and Chen

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Combination of ERS and clinicopathological characteristics contributes to better risk stratification and survival prediction. (A) Risk stratification was improved by constructing a decision tree. (B) Kaplan-Meier analysis showed noticeably different prognoses of different risk strata. (C) In the whole cohort, ERS was the most important risk factor for OS. (D) Risk assessment of individuals was quantified by constructing a nomogram. (E) Calibration analysis revealed high accuracy of survival prediction. (F) DCA analysis indicated that nomogram has the optimum decision benefit under most thresholds. (G) tROC analysis demonstrated that the nomogram was the most stable and powerful indicator for OS among all the clinical variables.