Researchers developed a new prognostic model that is able to measure the effect of tumor- and patient-specific factors on overall survival in intrahepatic cholangiocarcinoma (iCCA) following surgery. 

“The proposed dynamic model . . . performed well at internal validation and could assist both patients and providers in predicting prognosis and in tailoring treatment and follow-up strategy for [iCCA] patients,” they wrote in a report they published in the Annals of Surgical Oncology.

To develop the model, the team led by Timothy Pawlik MD, MPH, PhD, FACS, FRACS(Hon), from the Department of Surgery, Oncology, Health Services Management and Policy at Ohio State University in Columbus analyzed 1220 patients who underwent curative-intent surgery for iCCA between 1999 and 2017.

Continue Reading

They selected a number of variables that changed over time and analyzed their interaction. They then performed a landmark analysis to predict overall survival.

Read more about the prognosis of cholangiocarcinoma

Variables such as the age of the patient, the size, margin status, morphologic type, histologic grade, T and N category, and recurrence of the tumor were retained in the overall survival model.

The effects of several of these variables on overall survival changed with time, the researchers reported. They provided these results as a survival plot and the predicted probability of overall survival.

For example, they reported that the calculated estimated 3-year overall survival of a patient aged 65 years who had an intraductal, T1, grade 3 or 4 iCCA measuring 3 cm who underwent an R0 resection was 76%. If the patient had already survived for 1 year, the overall survival estimate went up to 79%.

iCCA is a type of cholangiocarcinoma located inside the hepatic parenchyma that can occur at any location in the intrahepatic biliary tree and that has a particularly high mortality rate.


Spolverato G, Capelli G, Lorenzoni G, et al. Dynamic prediction of survival after curative resection of intrahepatic cholangiocarcinoma: a landmarking-based analysis. Ann Surg Oncol. Published online July 24, 2022. doi:10.1245/s10434-022-12156-1