Development and validation of a risk model to predict the progression of ulcerative colitis patients to acute severe disease within one year

ABSTRACT

Background and aims

Acute severe ulcerative colitis (ASUC) is strongly associated with poor prognosis. We aimed to establish and validate a model predicting ASUC occurrence within 1 year after ulcerative colitis(UC) diagnosis.

Methods

A cohort of UC patients diagnosed between 2018 and 2020 at Northern Jiangsu People’s Hospital, who were followed up for one year, was used to develop a risk prediction model. An independent cohort from January to December 2021, monitored until December 2022 at the at the First Affiliated Hospital of Nanjing Medical University, was used for external validation. A multivariable logistic regression analysis was conducted to investigate the adjusted association between six risk factors and ASUC. Subsequently, a simplified model was developed by eliminating a relatively insignificant risk factor to create an easy-to-use index.

Results

The prediction model incorporates five parameters: disease extent, endoscopic appearance, histopathology, baseline response medication, and relapse frequency. It generates a nomogram in the end. The discriminant ability (c-index) was separately calculated as 0.982 and 0.925 in the development and validation cohorts.

Conclusions

The risk prediction model for developing ASUC within one year demonstrated excellent reliability and validity, which could be a straightforward and clinically valuable tool for predicting ASUC occurrence within 1 year.

Clinical trial registration

ChiCTR2300071794

KEYWORDS:

• Acute severe ulcerative colitis
• ulcerative colitis
• progression
• prediction
• disease phenotype
• risk model

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosure

Peer reviewers on this manuscript have received an honorarium from Expert Review of Gastroenterology & Hepatology for their review work but have no other relevant financial relationships to disclose.

Additional information

Funding

This paper was funded by Data Center of Management Science, National Natural Science Foundation of China - Peking University. No. 82070568. This study was also supported by grants from the New technology support project of Northern Jiangsu People’s Hospital (No. Fcjs202007).