A disease model predicting placebo response and remission status of patients with ulcerative colitis using modified Mayo score
Introduction
Read about the maximal usage of information from the modified Mayo clinic score by applying a novel modeling method in this paper, illustrating how a novel disease model utilizing item response theory — bounded integer methodology — was used to assess placebo effect, and predict remission status of patients with ulcerative colitis, using modified Mayo Score to enhance model informed drug development.
The response to placebo treatment in inflammatory bowel disease and in particular ulcerative colitis is substantial and variable. Novel methods are needed to better describe, predict, and distinguish from active treatment, such placebo effects.
By using the item response theory — bounded integer model — they were able to describe and predict individual modified Mayo clinic subscores, as well as composite scores and the key derived endpoint: modified remission. Importantly, the predictive performance was good for the analysis data, as well as unseen external evaluation data.
Significance
Ulcerative colitis, an inflammatory bowel disease, affecting the rectum and the colon, impacting the quality of life of the afflicted. It is estimated that there are around 5 million cases worldwide (Le Berre et al., The Lancet, issue 10401, 2023).
This publication illustrates how a novel disease model utilizing item response theory – bounded integer methodology was used to assess placebo effect and predict remission status of patients with ulcerative colitis using modified Mayo Score to enhance model informed drug development.
