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. 2022 Sep 27;13:1004425. doi: 10.3389/fphar.2022.1004425

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Copyright © 2022 Zhou, Gu, Tan, Yu, Liu, Ding, Liu and Shi.

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 the pyroptosis signature and clinicopathological features improves risk stratification and survival prediction. (A) A decision tree was constructed to improve risk stratification. (B) Performance of the decision tree. (C) A nomogram was constructed to quantify risk assessment for individual patients. (D) Calibration analysis indicated a high accuracy of survival prediction. (E,F) tROC analysis and decision curve analysis (DCA) demonstrated that the nomogram was the most stable and powerful predictor for OS among all the clinical variables.