A Composite Index for Distinguishing Benign and Malignant Obstructive Jaundice.

Objective: To explore a more effective and practical comprehensive index for differentiating benign from malignant obstructive jaundice by analyzing the clinical data of patients with benign obstructive jaundice (BJ) group and malignant obstructive jaundice (MJ) group.

Methods: A retrospective analysis was conducted on the clinical data of 339 patients with obstructive jaundice. The cases were divided into two data sets: training cohort and validation cohort. The cases were divided into two groups: malignant and benign obstructive jaundice group. Logistic regression analysis was used to build a prediction model for judging the nature of obstructive jaundice, and the prediction model was verified using the validation cohort.

Results: Multivariate analysis revealed that CEA, TBIL, and NLR were independent factors in malignant obstructive jaundice. A comprehensive index for differentiating benign from malignant obstructive jaundice was established based on these indicators. The sensitivity, specificity, and receiver operating characteristic curve of this model for differentiating benign from malignant obstructive jaundice were 79.57%, 93.26%, and 0.920, respectively.

Conclusion: The prediction model based on the comprehensive index of CEA, TBIL, and NLR has a higher accuracy in differentiating malignant obstructive jaundice.