Related Experiment Video
Updated: Sep 29, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
External validation of a prognostic model for predicting survival of cirrhotic patients with refractory ascites
Jordi Guardiola1, Carme Baliellas, Xavier Xiol
1Gastroenterology Unit, Hospital de L'Alt Penedès, Vilafranca del Penedès, Barcelona, Spain.
Objective:
Cirrhotic patients with refractory ascites (RA) have a poor prognosis, although individual survival varies greatly. A model that could predict survival for patients with RA would be helpful in planning treatment. Moreover, in cases of potential liver transplantation, a model of these characteristics would provide the bases for establishing priorities of organ allocation and the selection of patients for a living donor graft. Recently, we developed a model to predict survival of patients with RA. The aim of this study was to establish its generalizability for predicting the survival of patients with RA.
Methods:
The model was validated by assessing its performance in an external cohort of patients with RA included in a multicenter, randomized, controlled trial that compared large-volume paracentesis and peritoneovenous shunt. The values for actual and model-predicted survival of three risk groups of patients, established according to the model, were compared graphically and by means of the one-sample log-rank test.
Results:
The model provided a very good fit to the survival data of the three risk groups in the validation cohort. We also found good agreement between the survival predicted from the model and the observed survival when patients treated with peritoneovenous shunt and with paracentesis were considered separately.
Conclusion:
Our survival model can be used to predict the survival of patients with RA and may be a useful tool in clinical decision making, especially in deciding priority for liver transplantation.