Part II | Chapter 8 164 Cox proportional hazards models Table 2 presents the results frommultivariable Cox regressions for model 1 and 2. At baseline (model 1), four variables were identified as significant predictors of biochemical failure: age (HR 0.94), presalvage PSA (HR 2.19), GTV (HR 1.05), and pre-salvage PSADT (HR 0.87 and 1.18 for PSADT and PSADT’, respectively). For model 2, six predictors were identified: age (HR 0.92), pre-salvage PSADT (HR 0.89 and 1.16), pre-salvage PSA (HR 4.47), seminal vesicle involvement (HR 1.49), post-salvage time to PSA nadir (HR 0.82), and PSA reduction (HR 0.98). Although seminal vesicle involvement was not statistically significant in model 2 (p = 0.14), its exclusion affected AIC notably and therefore it remained in the model. The ranges of the continuous variables in our dataset are displayed in Table S2 (Supplementary D). Calibration and internal validation Calibration curves at 12, 24, and 36 months for both models are depicted in Figure 1. Calibration was reasonable up to 24 months. Internal validation showed an optimism of 0.15 and 0.19 for model 1 and 2, respectively. The b-coefficients were therefore adjusted with a factor of 0.85 (model 1) and 0.81 (model 2). The C-statistic was adjusted from 0.75 to 0.73 (95% CI: 0.66-0.81) for model 1 and from 0.85 to 0.84 (95%CI: 0.78-0.90) for model 2. The full regression equation for bothmodels can be found in Supplementary E. Nomogram The static nomograms for models 1 and 2 are depicted in Figure 2 and 3, respectively. An exemplary case is included in the figure caption. The Kaplan-Meier curves for bDFS for low-, intermediate-, and high-risk groups, as identified by model 1 (nomogram score < 193, 193-222, and > 222, respectively) and model 2 (nomogram score < 297, 297-334, and > 334, respectively) are shown in Figure 4. Estimated bDFS at 24 months for low-, intermediate, and high-risk groups was 84%, 70%, and 31% for model 1 (p < 0.0001) and 100%, 71%, and 5% for model 2 (p < 0.0001), respectively. Both models can be used as web tools through: https://fs-hdr-bt-prediction.shinyapps.io/model1/ (model 1) and https://fs-hdr-bt-prediction.shinyapps.io/model2/ (model 2).
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