Related Experiment Video
Updated: Jan 29, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Recognizing Preventable Death: Is There a Role of Survival Prediction Algorithms?
Oliver C Radke1, Catherine Heim2
1Department of Anesthesia and Intensive Care Medicine, Klinikum Bremerhaven-Reinkenheide, Postbrookstraße 103, Bremerhaven 27574, Germany; Department of Anesthesia and Perioperative Care, University of California in San Francisco, 1001 Potrero Avenue, San Francisco, CA 94110, USA; Department of Anesthesia, Technical University of Dresden, Fetscherstraße 74, 01307 Dresden, Germany.
Abstract:
Monitoring the quality of trauma care is important but particularly challenging. Preventable death assessment aims to identify those cases where the patient's death would have not occurred if the patient had been treated differently. Determination of preventable death in trauma care is often based on calculated probability of survival, commonly by using the Trauma and Injury Severity Score (TRISS). TRISS is not suited for identifying all cases with opportunities for improvement. Combined with other methods such as morbidity and mortality conferences, however, it might be a valid approach if a complete review of all trauma deaths is not feasible at an institution.
Related Concept Videos
Predicting Molecular Geometry
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Survival Tree
Building a Survival Tree
Constructing a...
Trial and Error and Algorithm
Cancer Prevention
Some...
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

