Related Experiment Video
Updated: Nov 11, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk
Gerine Nijman1,2, Maike Wientjes3, Jordache Ramjith4
1Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Background:
To date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk.
Methods:
In this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery.
Results:
1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes.
Conclusion:
Our competing risk survival analysis confirms specific risk factors for COVID-19 mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
Cancer Survival Analysis
The Mantel-Cox Log-Rank Test
Assumptions of Survival Analysis
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...

