Site Editor

Al B. Benson III, MD, FACP, FASCO

Advertisement
Advertisement

Novel Nomogram May Help to Predict Cancer Risk and Survival Among Some Patients With Liver Cancer

By: Vanessa A. Carter, BS
Posted: Friday, September 30, 2022

Youming Ding, MD, of Renmin Hospital of Wuhan University, China, and colleagues created a risk-stratification system and novel nomogram to aid in the prediction of cancer-specific survival in patients with hepatocellular carcinoma and severe liver fibrosis. Published in Frontiers in Surgery, this new protocol appears to be a feasible tool for managing individualized treatment regimens.

“A practical and reliable nomogram for predicting cancer-specific survival for hepatocellular carcinoma patients with severe liver fibrosis was constructed based on the significant risk factors identified in the analysis, which could effectively solve the survival paradox caused by the American Joint Committee on Cancer (AJCC) staging system and might help physicians make appropriate clinical decisions,” concluded the investigators.

Data on 1,878 patients with hepatocellular carcinoma who were diagnosed with severe liver fibrosis from 1975 to 2017 were collected from the Surveillance, Epidemiology, and End Results database (SEER). Patients were randomly assigned to training (n = 1,316) and validation (n = 562) cohorts. The nomogram and risk stratification of the nomogram were compared with the AJCC staging system.

A total of seven variables—age, pathologic grade, AJCC stages, tumor size, alpha fetoprotein, surgery, and income—were used as the basis for the nomogram. The consistency index among the training and validation cohorts appeared to be consistent, with values of 0.781 and 0.793, respectively. Additionally, the time-dependent AUC among both groups was similar, with the training cohort demonstrating 1-, 3-, and 5-year values of 0.845, 0.835, and 0.842, and the validation cohort exhibiting values of 0.861, 0.870, and 0.876, respectively.

Of note, the calibration plots identified that this nomogram appeared to be consistent with actual observations. Decision-curve analysis also determined the nomogram seemed to have better recognition than the current system. Furthermore, the integrated discrimination improvement and net reclassification index revealed that this nomogram outperformed the AJCC staging system significantly (P < .001), the investigators reported.

Disclosure: The study authors reported no conflicts of interest.


By continuing to browse this site you permit us and our partners to place identification cookies on your browser and agree to our use of cookies to identify you for marketing. Read our Privacy Policy to learn more.