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Comprehensive analysis of psychological symptoms and quality of life in early patients with IBD: a multicenter study from China

  • Yupei Liu,
  • Jiaming Hu,
  • Shan Tian,
  • Jixiang Zhang,
  • Ping An,
  • Yanrui Wu,
  • Zhongchun Liu,
  • Changqing Jiang,
  • Jie Shi,
  • Kaichun Wu,
  • Weiguo Dong

摘要

Objective

To investigate the prevalence and risk factors of psychological symptoms and quality of life (QoL) in early patients with inflammatory bowel disease (IBD).

Methods

From September 2021 to May 2022, a unified questionnaire was developed to collect clinical data from early patients with IBD from 42 tertiary care hospitals. The influencing factors of psychological symptoms and poor QoL are screened by logistic regression analysis for constructing model in predicting poor QoL. The consistency index, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the model.

Results

A total of 939 early patients with IBD were surveyed, Among them, 20.3% exhibited anxiety, 21.7% had depression, 57.3% experienced sleep disturbance, and 41.9% reported poor QoL. The factors influencing psychological symptoms varied between ulcerative colitis (UC) and Crohn’s disease (CD) patients. The QoL was primarily affected by disease activity, income level and depression. The AUC value of the model in the training group was 0.781 (95% CI: 0.748–0.814). The calibration diagram of the model closely matched the ideal curve. Compared to other prediction models, our model showed superior predictive capability, with NRI and IDI values of 0.324 (95%CI:0.196–0.4513) and 0.026 (95%CI:0.014–0.038), respectively. DCA indicated that the nomogram model could provide clinical benefits.

Conclusion

Early patients with IBD exhibit a high prevalence of psychological symptoms and poor QoL. The nomogram prediction model we constructed demonstrates high accuracy and performance in predicting QoL in early patients with IBD.