Prognostic models for predicting postoperative recurrence in Crohn's disease: a systematic review and critical appraisal

Rirong Chen; Jieqi Zheng; Chao Li; Qia Chen; Zhirong Zeng; Li Li; Minhu Chen; Shenghong Zhang

doi:10.3389/fimmu.2023.1215116

Prognostic models for predicting postoperative recurrence in Crohn's disease: a systematic review and critical appraisal

Front Immunol. 2023 Jun 30:14:1215116. doi: 10.3389/fimmu.2023.1215116. eCollection 2023.

Authors

Rirong Chen¹, Jieqi Zheng², Chao Li², Qia Chen², Zhirong Zeng¹, Li Li¹, Minhu Chen¹, Shenghong Zhang¹

Affiliations

¹ Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
² Department of Clinical Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.

Abstract

Background and aims: Prophylaxis of postoperative recurrence is an intractable problem for clinicians and patients with Crohn's disease. Prognostic models are effective tools for patient stratification and personalised management. This systematic review aimed to provide an overview and critically appraise the existing models for predicting postoperative recurrence of Crohn's disease.

Methods: Systematic retrieval was performed using PubMed and Web of Science in January 2022. Original articles on prognostic models for predicting postoperative recurrence of Crohn's disease were included in the analysis. The risk of bias was assessed using the Prediction Model Risk of Bias Assessment (PROBAST) tool. This study was registered with the International Prospective Register of Systematic Reviews (PROSPERO; number CRD42022311737).

Results: In total, 1948 articles were screened, of which 15 were ultimately considered. Twelve studies developed 15 new prognostic models for Crohn's disease and the other three validated the performance of three existing models. Seven models utilised regression algorithms, six utilised scoring indices, and five utilised machine learning. The area under the receiver operating characteristic curve of the models ranged from 0.51 to 0.97. Six models showed good discrimination, with an area under the receiver operating characteristic curve of >0.80. All models were determined to have a high risk of bias in modelling or analysis, while they were at low risk of applicability concerns.

Conclusions: Prognostic models have great potential for facilitating the assessment of postoperative recurrence risk in patients with Crohn's disease. Existing prognostic models require further validation regarding their reliability and applicability.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022311737.

Keywords: Crohn’s disease; patient management; postoperative recurrence; prognostic model; systematic review.

Publication types

Research Support, Non-U.S. Gov't
Systematic Review

MeSH terms

Crohn Disease* / diagnosis
Crohn Disease* / drug therapy
Crohn Disease* / surgery
Humans
Prognosis
Reproducibility of Results

Grants and funding

This study was supported by grants from the National Natural Science Foundation of China (#82070538, #81870374), Guangzhou Science and Technology Department (#202002030041), and Guangdong Science and Technology Department (#2021A1515220107).