A preliminary exploration of a predictive model and nomogram for the efficacy of compound digestive enzyme therapy based on serum (PGI, PGII, VIP, and PRDX1) in patients with functional dyspepsia.

Abstract

Objective: This study aimed to explore the feasibility of constructing compound digestive enzyme therapeutic effect prediction model based on serum pepsinogen I (PGI), pepsinogen II (PGII), vasoactive intestinal peptide (VIP), and peroxidase 1 (PRDX1) in patients with functional dyspepsia (FD), and draw nomograms, to provide reference for the selection of clinical treatment.

Methods: A total of 249 FD patients who visited the Department of Gastroenterology in our hospital from January 2021 to December 2024 were selected, and the preoperative clinical and laboratory indicators were collected. the patient cohort was split in a 7:3 ratio into a training set (n = 174) and a validation set (n = 75). The risk factors were screened by univariate and multivariate logistic regression in the training set, and the nomogram model was constructed. The receiver operating characteristic curve (ROC) was drawn and the calibration curve was used to evaluate the effectiveness of the model. The model was verified in the verification set, and the clinical value was evaluated by decision curve analysis (DCA).

Results: The results of multivariate logistic regression showed that PGI, PGII, VIP, PRDX1, white blood cell count, aspartate aminotransferase and high density lipoprotein cholesterol were the independent risk factors for poor efficacy of compound digestive enzymes in the treatment of FD. The C-index was 0.830 and 0.827, respectively, the area under the ROC curve (AUC) was 0.835 (95% CI: 0.792-0.941) and 0.835 (95% CI: 0.687-0.983), and the sensitivity and specificity were 0.768, 0.857, and 0.778, 0.780, respectively.

Conclusion: The therapeutic effect prediction model of compound digestive enzyme base on serum PGI, PGII, VIP, PRDX1 in patients with FD has some clinical value, but it still need to be further verified by large sample size and multi-center study.