A predictive model for survival of gallbladder adenocarcinoma.

BACKGROUND

Gallbladder cancer (GBC) is a life-threatening disease with a poor prognosis worldwide. Although several risk factors for survival have been identified, an ideal model for predicting prognosis has still not been developed due to the low incidence of GBC. This study aims to solve this dilemma by attempting to develop an efficient survival prediction model for GBC.

METHODS

This is a retrospective study. From January 2009 to June 2016, 164 patients with a confirmed histological diagnosis of gallbladder adenocarcinoma were enrolled in this study. The cohort was randomly divided into two cohorts, the development cohort (n = 110) and validation cohort (n = 54). On the basis of the risk factors identified in the development cohort, a nomogram-based predictive model (P-risk Plus), composed of carbohydrate antigen 199 and pathological characteristics, was established for prognosis.

RESULTS

In this model, the calibration curves for the 1-, 2-, and 3-year survival probabilities were well-matched with the actual survival rates. In addition, the highest C-index and best decision curve analysis were able to be obviously determined. Meanwhile, the P-risk Plus model result yielded a better fit for survival between the development and validation groups.

CONCLUSION

Compared with conventional tumor stages, our nomogram-based P-risk Plus model for gallbladder adenocarcinoma has a better predictive capacity and thereby has a better potential to facilitate decision-making clinically.