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Updated: Jan 13, 2026
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and Validation of a Novel Nomogram for Risk Stratification of Posthemorrhagic Chronic Hydrocephalus
Sai Du1, Chao Zhang2, Liansheng Mou3
1Department of Neurosurgery, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, People's Republic of China.
Background:
To develop and validate the first nomogram for the individualized risk assessment of posthemorrhagic chronic hydrocephalus in patients with intraventricular hemorrhage (IVH).
Methods:
This multicenter retrospective cohort study analyzed clinical data from patients with IVH treated at seven centers in China between December 2020 and December 2022. The study population specifically comprised patients whose external ventricular drain management was limited to a maximum of 2 weeks, without shunt placement during this period. Patients were randomly categorized into training and validation sets (7:3 ratio). Key predictors were identified using LASSO regression and multivariable logistic regression. Model performance was assessed via the C-index, area under the receiver operating characteristic curve, calibration curves, and decision curve analysis.
Results:
A total of 280 patients were included in the study, of whom 82 (29.3%) developed chronic hydrocephalus. Three risk factors, including acute hydrocephalus, ventricular hematoma volume at 24 h, and parenchymal hematoma volume on admission, were identified as significant determinants for chronic hydrocephalus. The nomogram demonstrated robust discriminative ability, with a C-index of 0.850 (95% confidence interval [CI] 0.791-0.909) in the training cohort and 0.785 (95% CI 0.649-0.922) in the validation cohort, surpassing the threshold of 0.70 for clinical utility. The area under the receiver operating characteristic curve was found to be 0.826 (95% CI 0.756-0.896) in the training set and 0.785 (95% CI 0.661-0.910) in the validation set. Furthermore, calibration curves and the Hosmer-Lemeshow test revealed favorable agreement between the nomogram model and actual observations. Decision curve analysis indicated that the nomogram provided clinical net benefit across threshold probabilities ranging from 8 to 80% in the training set and from 18 to 95% in the validation set.
Conclusions:
This study developed and validated the first nomogram for assessing the risk of posthemorrhagic chronic hydrocephalus in patients with IVH, providing a valuable tool for individualized risk stratification and clinical decision-making. The study was registered on medicalresearch.org.cn (MR-50-23-048489).
