What question did this study set out to answer?

The study aims to examine the link between serum interleukin levels and the likelihood of postoperative recurrence in pelvic organ prolapse.

March 19, 2026Open Access

Exploring the role of serum interleukins in postoperative recurrence of pelvic organ prolapse: Development and validation of a predictive model

Key Points

The study aims to examine the link between serum interleukin levels and the likelihood of postoperative recurrence in pelvic organ prolapse.
Analyzed serum interleukin levels in patients post-surgery for pelvic organ prolapse.
Included 184 patients from March 2022 to June 2024.
Utilized multivariate analysis to identify risk factors for recurrence.
Higher serum IL-1β, IL-6, and IL-8 levels were found in patients with recurrence (P<0.001).
Identified IL-1β, IL-6, IL-8, age, menopause status, POP-Q stage, and chronic constipation as independent risk factors.
The predictive model showed excellent performance with AUCs of 0.965 in training and 0.946 in validation sets.

Abstract

To explore the correlation between serum interleukins and postoperative recurrence of pelvic organ prolapse (POP). Additionally, a predictive model incorporating both clinical parameters and inflammatory markers was developed to support individualized recurrence prevention and management strategies. The analysis included 184 patients who underwent POP surgery between March 2022 and June 2024. Among them, 44 experienced recurrence (recurrence group), while 140 did not (non-recurrence group). The serum levels of Interleukin (IL)-1β, IL-6 and IL-8 in the recurrence group were higher than those in the non-recurrence group (P<0.001). Multivariate analysis showed that, IL-1β (OR: 1.420, 95%CI: 1.189 - 1.695), IL-6 (OR: 1.693, 95%CI: 1.298 - 2.207)，IL-8 (OR: 1.443, 95%CI: 1.174 - 1.774), Age (OR: 1.138, 95%CI: 1.031 1.257), Menopause (OR: 6.484, 95%CI: 1.600 - 26.275), POP-Q stage (OR: 9.162, 95%CI: 2.180-38.510) and chronic constipation (OR: 5.029, 95%CI: 1.219-20.753) were independent risk factors for postoperative recurrence. The risk model based on this model showed excellent prediction performance in both the training set (AUC=0.965, sensitivity 93.75%, specificity 87.63%) and the validation set (AUC=0.946, sensitivity 91.67%, specificity 88.37%) (P<0.05).

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