Using multiple imputation of real-world data to estimate clinical remission in pediatric inflammatory bowel disease

Abstract

Aims: To evaluate the performance of the multiple imputation (MI) method for estimating clinical effectiveness in pediatric Crohn's disease in the ImproveCareNow registry; to address the analytical challenge of missing data. Materials & methods: Simulation studies were performed by creating missing datasets based on fully observed data from patients with moderate-to-severe Crohn's disease treated with non-ustekinumab biologics. MI was used to impute sPCDAI remission statuses in each simulated dataset. Results: The true remission rate (75.1% [95% CI: 72.6%, 77.5%]) was underestimated without imputation (72.6% [71.8%, 73.3%]). With MI, the estimate was 74.8% (74.4%, 75.2%). Conclusion: MI reduced nonresponse bias and improved the validity, reliability, and efficiency of real-world registry data to estimate remission rate in pediatric patients with Crohn's disease.