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Updated: Jan 2, 2026
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
One- to 10-year Status Epilepticus Mortality (SEM) score after 30 days of hospital discharge: development and
Prapassara Sirikarn1,2, Porjai Pattanittum1, Somsak Tiamkao3,4
1Department of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand.
Background:
Status epilepticus (SE) is an emergency neurological disorder that affects quality of life and is associated with high mortality risk. Three scores have been developed to predict the risk of in-hospital death, but these scores are poor discrimination of mortality after discharge. This study aimed to develop and validate a simple risk score for long-term mortality in SE patients.
Methods:
This retrospective cohort study was conducted using SE patient data collected from Thailand's Universal Coverage Scheme database between the fiscal years of 2005 and 2015 and followed-up to 2016. Patients who died in hospital or within 30 days after discharge were excluded. Data were divided at random into either a derivation or validation set. A proportional hazards model for the sub-distribution of competing risks was fitted with backward stepwise method. The coefficients from the model were used to develop a point-based scoring system. The discrimination ability of the model was evaluated using a time-dependent receiver operating characteristic (ROC) curve.
Results:
A total of 20,792 SE patients (with ages ranging from the first day of life to 99 years at first admission) were randomly separated into two groups: 13,910 in the development group and 6882 in the validation group. A sub-distribution hazard model was used to determine nine predictors to be included in the final model, which was, in turn, used to develop the scoring system: age (0-19 points), male (two points), brain tumor (12 points), stroke (three points), cancer (11 points), diabetes (three points), chronic kidney disease (five points), pneumonia (five points), and urinary tract infection (four points). The possible total score ranged from zero to 64 and the cumulative incidence function was used to determine the probability of mortality associated with each total score within the first 10 years after the first admission. The area under the ROC curve (AUC) of the first to last time point ranged from 0.760 to 0.738.
Conclusion:
A nine-factor risk score for predicting 10-year mortality in SE patients was developed. Further studies should focus on external validity and including a range seizure types and duration of seizure as the predictors.
