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. 2022 Jun 13;9:889414. doi: 10.3389/fmolb.2022.889414

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Copyright © 2022 Ma, Jin, Lu, Zhang, Li and Cai.

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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The nomogram model with EXO1 shows a superior diagnostic and prognostic performance in HCC. (A) Diagnostic ROC curves to distinguish HCC tissues and normal tissues based on the EXO1 expression levels. (B) Time-dependent survival ROC curves to predict 1-, 3-, and 5-year survival rates of HCC patients based on the EXO1 expression levels. (C) ROC curve analysis to evaluate the prediction efficacy of the nomogram model that includes clinicopathological factors (T stages, tumor status, and pathologic stages) and EXO1 expression levels to predict the 1-, 3-, and 5-year survival rates of HCC patients.