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. 2022 Jun 9;13:868809. doi: 10.3389/fimmu.2022.868809

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Copyright © 2022 Yuan, Xie, Song, Li, Li, Hu, Zang, Cheng, Lu, Huang, Fan, Rong, Sun 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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Calibration curve of the nomogram in the training (A) and validation (B) set. X-axis represents the nomogram predicted probability of Progressive Diseases (PD). Y-axis represents the actual probability of PD, and the diagonal dashed line (represent ideal) indicates the ideal prediction by a perfect model. Results were plotted via bootstrapping with 1000 resamples. The closer the bias-corrected calibration curve (solid line) is to the diagonal line, the higher the prediction accuracy of the model.