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Updated: Aug 3, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Independently derived survival risk ratios yield better estimates of survival than traditional survival risk ratios
J Wayne Meredith1, Patrick D Kilgo, Turner M Osler
1Department of Surgery, Wake Forest Univeresity School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157-1063, USA. merediw@wfubmc.edu
Background:
The International Classification of Diseases, Ninth Revision Injury Severity Score (ICISS) is criticized because it relies on survival risk ratios (SRRs) that are contaminated by incidents with multiple injuries. An SRR for an International Classification of Diseases, Ninth Revision code is the number of patients who survive the injury divided by the number who display it. The ICISS is the product of SRRs that correspond to a patient's injuries. Traditional SRRs are derived from databases that include patients with multiple injuries and are biased toward mortality, making them nonindependent. Independent SRRs are derived from incidents where patients sustained only an isolated injury. The objective of this study is to compare the mortality prediction abilities of independent and traditional SRRs via the ICISS.
Methods:
A 10-fold cross-validation design was used to estimate independent and traditional SRRs and their resulting ICISSs from 192,347 National Trauma Data Bank patients. Logistic regression modeled the scores as a function of mortality. The area under the receiver operating characteristic curve measured discrimination. Model fit was measured with the Akaike information criterion, a deviance statistic (lower is better). R2 values were compared to determine which score explained the most variance.
Results:
The independent ICISS statistically outperforms the traditional ICISS.
Conclusion:
Traditional SRRs used by the ICISS produce less accurate estimates of mortality than independent SRRs. The ICISS can be calculated in 97.9% of incidents using independent SRRs.
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