Value of LTB4 and hBD-3 expression in gingival crevicular fluid combined with random forest model for predicting the risk of peri-implantitis during the maintenance period of implant restoration patients

doi:10.19439/j.sjos.2026.03.014

Abstract

Abstract: PURPOSE: To evaluate the value of combining leukotriene B4 (LTB4) and human beta-defensin-3 (hBD-3) expression in gingival crevicular fluid (GCF) with a random forest model for predicting the risk of peri-implantitis (PI) during the maintenance period of implant restoration patients. METHODS: A prospective study was conducted, totally 362 patients who underwent implant restoration from March 2023 to March 2025 were selected. They were divided into PI group(n=61) and non PI group (n=301) according to the occurrence of peri-implantitis during the maintenance period. Baseline data were compared between the two groups, binary logistic regression was used to analyze the influencing factors of peri-implantitis during the maintenance of implant repair patients. The random forest model was constructed using R (R 4.1.0) software package and the randomForest package. The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to test the predictive value of the random forest model for peri-implantitis during the maintenance of patients with implant restoration. RESULTS: The levels of Caspase-1, IL-1β and LTB4 in the PI group were significantly higher than those in the non PI group, and the level of hBD-3 was significantly lower than that in the non PI group (OR>1, P<0.05). hBD-3 was a protective factor for PI during maintenance (OR<1, P<0.05). The variable importance measure (%IncMse) was used to score and rank the feature importance. The top three importance indicators were LTB4, Caspase-1 and IL-1β, respectively. The %IncMse was 29.372, 27.488 and 23.123, respectively. The random forest model was P=0.01. Among the 362 patients, totally 317 were correctly predicted, and the correct rate was 87.57%. The random forest reached a stable performance period when the number was≥100. Based on the test set, a random forest model was established with Caspase-1, IL-1β, LTB4 and hBD-3 to predict the occurrence of peri-implantitis during the maintenance of implant restoration patients. The AUC was 0.841, the sensitivity was 0.833, the specificity was 0.769, the Youden index was 0.603, and the 95%CI was 0.736-0.923, which had good predictive efficacy. CONCLUSIONS: Caspase-1, IL-1βand LTB4 levels are risk factors for peri-implantitis during the maintenance period in patients undergoing implant restoration, while hBD-3 level is a protective factor. Random forest model analysis indicates that LTB4 is a key driver in predicting PI, and the model constructed based on these results demonstrates good predictive performance.

Key words: Implant restoration, Gingival crevicular fluid, Leukotriene B4, Human β-defensin-3, Peri-implantitis

CLC Number:

R781.4

Wu Yan, Yang Jianxin, Tang Zhaolong. Value of LTB4 and hBD-3 expression in gingival crevicular fluid combined with random forest model for predicting the risk of peri-implantitis during the maintenance period of implant restoration patients[J]. Shanghai Journal of Stomatology, 2026, 35(3): 305-311.

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