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Updated: Dec 9, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and Validation of a Nomogram for Predicting Death within 2 days After Intracerebral Hemorrhage
Objective:
This study aimed to establish and verify a model for predicting death within 2 days after spontaneous cerebral hemorrhage based on the patient's characteristics at the time of admission.
Methods:
During 2015-2017, the records of a cohort of 397 patients with clinically diagnosed cerebral hemorrhage were collected for model development. Minimum absolute contraction and the selection operator (lasso) regression model were used to determine factors that most consistently and correctly predicted death after cerebral hemorrhage. Discrimination and calibration were used to evaluate the performance of the resulting nomogram. After internal validation, the nomogram was further assessed during 2017-2018 using a different cohort of 200 consecutive subjects.
Results:
The nomogram included four predictors from the lasso regression analysis: Glasgow Coma Scale, hematoma location, hematoma volume, and primary intraventricular hemorrhage. The nomogram showed good discrimination and good calibration for both training and verification cohorts. Decision curve analysis showed that the prediction nomogram was clinically useful.
Conclusion:
This prediction model can be used for early, simple, and accurate prediction of early death following cerebral hemorrhage.
