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Development and validation of multivariable prediction models for adverse COVID-19 outcomes in patients with IBD
John Sperger1, Kushal S Shah2, Minxin Lu2
1Department of Biostatistics, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA jsperger@live.unc.edu.
Insights
This study developed a tool to predict adverse COVID-19 outcomes in inflammatory bowel disease (IBD) patients. The models accurately identify individuals at higher risk, aiding clinical decision-making for better patient care.
Area of Science:
- Epidemiology
- Clinical Informatics
- Gastroenterology
Background:
- Inflammatory bowel disease (IBD) patients may face increased risks from COVID-19.
- Predictive tools are needed to stratify risk and guide management for IBD patients during the pandemic.
Purpose of the Study:
- To develop and validate an individualized prognostic risk prediction tool for adverse COVID-19 outcomes in patients with IBD.
- To identify key factors associated with severe COVID-19 outcomes in this population.
Main Methods:
- Utilized penalized logistic regression models developed on data from the international Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease (SECURE-IBD) registry.
- Trained models on 85% of cases (March-September 2020) and validated on the remaining 15% plus later cases (September-October 2020).
- Assessed model discrimination using the area under the receiver operator characteristic curves (AUC).
Main Results:
- The study included 2709 cases from 59 countries.
- Developed models demonstrated excellent discrimination for predicting hospitalization (AUC 0.79), ICU admission (AUC 0.88), and death (AUC 0.94).
- Factors associated with increased mortality risk included age, comorbidities, corticosteroid use, and male gender; biological therapy use was associated with lower risk.
Conclusions:
- Prognostic models effectively predict COVID-19-related adverse outcomes in IBD patients.
- An online risk calculator is available to assist healthcare providers in discussing risks with IBD patients.
- These tools can support personalized risk assessment and management strategies for IBD patients during the COVID-19 pandemic.
Objectives:
Develop an individualised prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with inflammatory bowel disease (IBD).
Design And Setting:
This study developed and validated prognostic penalised logistic regression models using reports to the international Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease voluntary registry from March to October 2020. Model development was done using a training data set (85% of cases reported 13 March-15 September 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported 16 September-20 October 2020).
Participants:
We included 2709 cases from 59 countries (mean age 41.2 years (SD 18), 50.2% male). All submitted cases after removing duplicates were included.
Primary And Secondary Outcome Measures:
COVID-19 related: (1) Hospitalisation+: composite outcome of hospitalisation, ICU admission, mechanical ventilation or death; (2) Intensive Care Unit+ (ICU+): composite outcome of ICU admission, mechanical ventilation or death; (3) Death. We assessed the resulting models' discrimination using the area under the curve of the receiver operator characteristic curves and reported the corresponding 95% CIs.
Results:
Of the submitted cases, a total of 633 (24%) were hospitalised, 137 (5%) were admitted to the ICU or intubated and 69 (3%) died. 2009 patients comprised the training set and 700 the test set. The models demonstrated excellent discrimination, with a test set area under the curve (95% CI) of 0.79 (0.75 to 0.83) for Hospitalisation+, 0.88 (0.82 to 0.95) for ICU+ and 0.94 (0.89 to 0.99) for Death. Age, comorbidities, corticosteroid use and male gender were associated with a higher risk of death, while the use of biological therapies was associated with a lower risk.
Conclusions:
Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of patients with IBD. A free online risk calculator (https://covidibd.org/covid-19-risk-calculator/) is available for healthcare providers to facilitate discussion of risks due to COVID-19 with patients with IBD.
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