Validated risk score predicts post-transplant survival in HCC

Investigators developed a validated risk score to predict post-transplant survival for patients with hepatocellular carcinoma that will help prioritize patients based on predicted survival, according to study results.

"In the United States, all patients with liver cancer or HCC who are waitlisted for a transplant and meet [United Network for Organ Sharing (UNOS)] exception criteria receive the same waitlist priority based on where they live,” David Goldberg, MD, MSCE, from the division of digestive health and liver diseases and the department of medicine, University of Miami Miller School of Medicine, told Healio Gastroenterology. “Waiting time is currently the tiebreaker for two patients with the same HCC waitlist priority. Our study provides an objective risk score that can predict a patient's long-term survival after transplant.”

Using national registry data, Goldberg and colleagues performed a retrospective cohort study of 6,502 adult HCC liver transplant recipients. Investigators estimated beta coefficients for a risk score using manual variable selection with Cox regression models. Absolute predicted survival time from the Liver Transplant Expected Survival HCC score was calculated and compared with available risk scores.

Researchers selected 11 variables in the final model. At 5- and 10 years the area under the curves were 0.62 (95% CI, 0.57-0.67) and 0.65 (95% CI, 0.58-0.7), respectively. However, this was not statistically significantly different compared with the Metroticket and Hazard Associated with Liver Transplantation for Hepatocellular Carcinoma scores.

According to researchers, Liver Transplant Expected Survival HCC score could discriminate patients based on post-transplant survival from patients meeting Milan and University of California, San Francisco binary tumor criteria.

“This score could therefore help to better prioritize patients waitlisted for a transplant by accounting for their expected long-term outcome,” Goldberg said. “Simply put, we can prioritize the patient who is predicted to live two years longer rather than the patient who has two more days of accrued waiting time."