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. 2023 Aug 6;36:101753. doi: 10.1016/j.tranon.2023.101753

Fig. 3.

FIGURE 3

Evaluation of prognostic predictive power of LRPS. (A) ROC curves for diagnosing patient viability status using LRPS in training group. (B) ROC curves showing that LRPS predicted osteosarcoma prognosis more accurately than all clinical features. (C) Kaplan-Meier curves of LRPS for predicting patients' survival of osteosarcoma in the training set. (D, E) Scatter plots of the viability of osteosarcoma patients in the training set. Green: low risk; Orange: high risk. (F) Heat map showing the expression levels of risk DELRLs in the training set. roc curve, receiver operating characteristic curve; AUC, area under the curve; p<0.05, statistically significant. (G) Univariate Cox analysis for all clinical characteristics and prognostic models. (H) Multivariate Cox analysis.