Exact(60)
AT and KM2 segmentation methods developed identical prognostic models.
Additional file 1: Prognostic models developed from PET auto-segmentation methods excluded from the study.
However, studies have investigated the inclusion of shape metrics in prognostic models [42].
The significant variables in the developed prognostic models were dependent upon the delineation method.
Discrimination between prognostic models was assessed using the concordance index (C-index).
For interest, Additional file 1 describes the developed prognostic models for the excluded PET-AS methods.
Future research should focus on improving prognostic models for aged patients.
The performance of prognostic models encompasses two objective measures: calibration and discrimination.
Commonly used prognostic models for aged patients in the ICU lack calibration.
Prognostic models are used for mortality predictions and illness severity assessment.
Hosmer-Lemeshow statistics showed good calibration for all 6 prognostic models.
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