New model accurately predicted HCC recurrence after transplantation
A novel clinicopathologic prognostic nomogram developed by researchers at the University of California, Los Angeles, accurately predicted liver transplant recipients’ chance of hepatocellular carcinoma recurrence post-transplant, according to new study data.
In a retrospective study, Vatche G. Agopian, MD, assistant professor of surgery, division of liver transplantation at UCLA, and colleagues developed a clinicopathologic risk score and nomogram from a multivariate Cox regression analysis of 865 patients who underwent liver transplantation to predict post-transplant recurrence of HCC.
Vatche G. Agopian
“This novel nomogram includes three important groups of information that proved to be very accurate in predicting recurrence in liver cancer patients, better than any other system out there,” Agopian said in a press release. “Physicians can use our nomogram and have a meaningful discussion with transplant recipients regarding their post-transplant risk of cancer recurrence.”
The three groups used for predicting recurrence were pre-transplant radiologic information or the number and size of tumors on MRI and CT scans, three pre-transplant blood biomarkers and pathological characteristics of the explanted liver, according to the research.
HCC recurred in 117 transplant recipients with a median time of 15 months to recurrence. HCC recurrence-free survival rates were 79% at 1 year, 63% at 3 years and 56% at 5 years post-transplant. Overall patient survival rates were 83% at 1 year, 68% at 3 years and 60% at 5 years post-transplant.
Multivariate analysis showed tumor grade/differentiation, macrovascular and microvascular invasion, non-downstaged tumors outside Milan criteria, among other factors, to be predictors of recurrence.
The clinicopathologic nomogram had enhanced abilities in predicting post-transplant recurrence (c-statistic=0.85), according to the research. A pre-transplant model that included only radiographic and laboratory parameters showed increased accuracy in predicting HCC recurrence post-transplant (c-statistic=0.79) compared with the Milan and University of California, San Francisco, criteria (c-statistic=0.64 for both).
“The Milan criteria presented a major step in improving the outcomes of liver cancer patients undergoing transplant,” Agopian said. “However, there is now a growing consensus and body of evidence that these criteria are too conservative, and that incorporation of other factors may improve the ability to select for patients with favorable tumor biology, regardless of size, who stand to benefit from liver transplantation.”
“Incorporation of routine pre-transplant biomarkers to existing radiographic size criteria significantly improves the ability to predict post-transplant recurrence and should be considered in recipient selection,” the researchers wrote. “A novel clinicopathologic prognostic nomogram accurately predicts liver cancer recurrence and liver transplant may guide frequency of post-transplant surveillance and adjuvant therapy.”
Disclosure: The researchers report no relevant financial disclosures.