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Using multiple imputation of real-world data to estimate clinical remission in pediatric inflammatory bowel disease
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Becaris Publishing Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402781/ https://www.ncbi.nlm.nih.gov/pubmed/36799351 http://dx.doi.org/10.57264/cer-2022-0136 |
Sumario: | 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. |
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