Development and validation of a preoperative nomogram for predicting gallbladder adenoma.

Background: Gallbladder cholesterol polyp (GCP) and gallbladder adenoma (GA) are easily confused in clinical diagnosis. This study aims to establish a nomogram prediction model for preoperative prediction of the risk of GA patients.

Study Design: We retrospectively collected clinical data of GCP or GA patients who underwent laparoscopic cholecystectomy (LC) between January 2020 and April 2023. We compared and analyzed the differences between the GCP group and the GA group. The data were divided into a training set and a validation set in a 7:3 ratio. Independent risk factors were determined using LASSO and Logistic regression analysis, and a nomogram model was established. The model was comprehensively validated and evaluated using the area under the ROC curve (AUC), Hosmer-Lemeshow test and clinical decision curve analysis (DCA).

Results: This study ultimately included 497 patients. The independent predictors of the nomogram model include blood type (O-type blood, OR 2.00, 95% CI 1.02-3.94; P = 0.046), number of lesions (solitary, OR 2.11; 95% CI 1.08-4.12; P = 0.033), sessile polyp (OR 2.04; 95% CI 1.06-3.92; P = 0.033), age (OR 1.10; 95% CI 1.07-1.20; P < 0.001), diameter (OR 1.30; 95% CI 1.17-1.45; P < 0.001). For the training and validation set, the area under the ROC curve (AUC) was 0.843 and 0.837, respectively, and the P-value for the Hosmer-Lemeshow test was 0.056 and 0.300, respectively. In addition, the calibration curve and DCA curve indicate that the model has accurate predictive ability and reliable clinical practicality.

Conclusions: The blood type, number of lesions, sessile polyp, age and diameter are significant risk factors for GA. This nomogram model can use simple and readily available clinical data to predict the risk of having GA and can assist in guiding surgical decisions.