Decision of surgical approach for advanced gallbladder adenocarcinoma based on a Bayesian network.

BACKGROUND AND OBJECTIVES

To determine whether radical resection can benefit patients with advanced gallbladder adenocarcinoma using a Bayesian network (BN) with clinical data.

METHODS

In total, 362 patients who had undergone surgical treatment of gallbladder adenocarcinoma at a tertiary institute were evaluated to establish two BN models using a tree-augmented naïve Bayes algorithm. We then chose 250 patients with T3-4N0-2M0 stage gallbladder adenocarcinoma to test the posterior probability after the surgical type was taken into account.

RESULTS

In total, 170 patients (≤7 months) and 137 patients (>7 months) were correctly classified in the median survival time model (accuracy, 84.81%), and 204 patients (≤12 months), 15 patients (12-36 months), 17 patients (36-60 months), and 34 patients (>60 months) were correctly classified in the 1-, 3-, and 5-year survival model (accuracy, 74.59%), respectively. Every posterior probability in the two models upregulated the ratio of the longer survival time and suggested a better prognosis for gallbladder adenocarcinoma that can be improved by R0 resection.

CONCLUSIONS

These BN models indicate that stages T4 and N2 gallbladder adenocarcinoma are not contraindications for surgery and that R0 resection can improve survival in patients with advanced gallbladder adenocarcinoma.