Preoperative Prediction Of The Nature Of Gallbladder Polypoid

Objective: Polypoid lesion of gallbladder(PLG)is a kind of morphological disease name,and its corresponding pathologic name has more than 20 kinds.To provide a scientific basis for proper management of such diseases,we analyzed the risk factors of the gallbladder neoplastic polyps and established the logistic regression equation,which predicted the risk of gallbladder neoplastic polyps and gallbladder cancer.Methods: In this study,we retrospectively collected clinicopathological data of 580 patients who underwent cholecystectomy for gallbladder polyps.Compared to the clinicopathological parameters between non-neoplastic polyps and neoplastic polyps,and adenomas and gallbladder cancer by univariate and multivariate analysis,we fit logistic regression equations to conduct diagnostic test.Results: The univariate analyses showed that ultrasonic measuring the width of gallbladder basal > 0.72 cm width,the CT value > 34.50 Hu,CEA > 1.51 ng·ml-1,CA199 > 12.92 U·ml-1 for the diagnosis of gallbladder adenomatous polyps were statistically significant respectively(p < 0.05).Multivariate regression analysis showed regression equations 1.When p > 0.256,the sensitivity of the diagnosis of adenomatous polyps was 72.4%,the specialty was 80.0%,and the whole correct ratio was 77.8%.The positive likelihood ratio of adenomatous polyps was 10.44,AUC was 0.828.When the patients with neoplasm risk factors,the CT value > 32.50 Hu for the diagnosis of malignancy was statistically significant(p < 0.05).Multivariate regression analysis displayed regression equations 2.When p > 0.496,the sensitivity of the diagnosis of adenomatous polyps was 86.0%,the specialty was 90.5%,and the whole correct ratio was 89.0%.The positive likelihood ratio for malignant tumor was 9.08,AUC was 0.938.Conclusion: In preoperative,according to patients’ age,symptoms,ultrasonic parameters,we can obtain the regression equations which will predict the gallbladder polyps nature more accurate and guide the clinical intervention.