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. 2022 Oct 5;13:956246. doi: 10.3389/fgene.2022.956246

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Copyright © 2022 Li, Zhang, Li, Wu, Feng, Wang, Liu, Zhang, Cai, Jia, Qiao, Wu and Zhang.

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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Construction and evaluation of the LRLPS. (A) The univariate Cox regression analysis of LRLs in the training cohort. (B) The cross-validation graph shows the optimal parameter selection with minimum criteria in the LASSO model. (C)The LASSO coefficient profiles of the 14 LRLs. (D) The forest graph showed the results of stepwise multivariable cox proportional hazards regression analysis. (E) The OS curve of the two risk groups. (F) The time-dependent ROC curves of the LRLPS. (G) The risk score, clinical event, and the model genes in the two risk groups. (H) The ROC curves of the risk score and other clinicopathological parameters. The univariate (I) and multivariate (J) Cox regression analyses.