Weimin Cai, Xinran Lin, Yu Guo, Xiuqing Lin, Chao Chen

A Nomogram For Predicting Prognosis in Patients with TIPS Creation Based on deep learning derived Spleen Volume-to-Platelet Ratio

  • Radiology, Nuclear Medicine and imaging
  • General Medicine
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Abstract Objectives The objective of our study was to develop a nomogram to predict post-transjugular intrahepatic portosystemic shunt (TIPS) survival in patients with cirrhosis based on CT images. Methods This retrospective cohort study included patients who had received TIPS operation at the …… between November 2013 and April 2017. To predict prognosis, a nomogram and Web-based probability were developed to assess the overall survival (OS) rates at 1, 3, and 5 years based on multivariate analyses. With deep learning algorithm, the automated measurement of liver and spleen volumes can be realized. We assessed the predictive accuracy and discriminative ability of the nomogram using the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) Results Age, total bilirubin, and spleen volume-to-platelet ratio (SVPR) were identified as the independent risk factors of OS. The nomogram was constructed based on the above risk factors. The C-index (0.80, 0.74, 0.70), ROC curve (area under curve: 0.828, 0.761, 0.729), calibration curve, and DCA showed that nomogram good at predictive value, stability, and clinical benefit in the prediction of 1-, 3-, 5-year OS in patients with TIPS creation. Conclusion We constructed a nomogram for predicting prognosis in patients with TIPS creation based on risk factors. The nomogram can help clinicians in identifying patients with poor prognosis, eventually facilitating earlier treatment and selecting suitable patients before TIPS. Advances in knowledge This study developed the first nomogram based on SVPR to predict the prognosis of patients treated with TIPS. The nomogram could help clinician non-invasively decision-making.

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