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. 2023 Oct 23;30(2):356–367. doi: 10.1158/1078-0432.CCR-23-1013

Figure 4.

Figure 4. Multivariable survival modelling (trained with backward elimination using AIC) for composite (molecular biomarkers + clinical factors) and clinical factors only with OS. A–D, Assessment of composite and clinical only models in the validation cohort split into two and three risk groups. E–H, Assessment of composite and clinical only models’ predicted risk groups (low- and high-risk) stratified by surgery in the training (E and F) and validation cohorts (G and H). Risk groups in the validation cohort were created using the thresholds (two-group classification: median; three-group classification: tertiles) derived from the training set. In E, the estimate of HR (95% CI) was not possible due to absence of events in low, surgery+ group. Color key: same as Fig. 3.

Multivariable survival modelling (trained with backward elimination using AIC) for composite (molecular biomarkers + clinical factors) and clinical factors only with OS. A–D, Assessment of composite and clinical only models in the validation cohort split into two and three risk groups. E–H, Assessment of composite and clinical only models’ predicted risk groups (low- and high-risk) stratified by surgery in the training (E and F) and validation cohorts (G and H). Risk groups in the validation cohort were created using the thresholds (two-group classification: median; three-group classification: tertiles) derived from the training set. In E, the estimate of HR (95% CI) was not possible due to absence of events in low, surgery+ group. Color key: same as Fig. 3.