Proposal for Risk-Adjusted Surveillance Strategies in Extrahepatic Bile Duct Cancer with Cost-Effectiveness...

We developed a risk-adjusted surveillance strategy incorporating prognostic factors for disease-free survival (DFS) in patients with extrahepatic bile duct cancer after curative resection and lymph node dissection.

After ethical approval with informed consent waived, this retrospective analysis included 1,443 patients with extrahepatic bile duct cancer treated between 2000 and 2015 (median follow-up, 35.9 months). DFS, defined as the time from surgery to recurrence or death, was analyzed using multivariate Cox proportional hazards models to identify prognostic factors. A random survival forest model adjusted these factors and generated risk-adjusted survival curves stratified by radiation therapy (RT) status. Surveillance visit points were determined at intervals corresponding to a 7% recurrence or death risk increase.

Adverse prognostic factors for DFS included pT3-4 stage (hazard ratio [HR], 1.220; P = .005), pN1 stage (HR, 2.208; P < .001), margin involvement by invasive carcinoma (HR, 1.670; P < .001), moderate (HR, 1.342; P = .002) or poor (HR, 1.870; P < .001) tumor differentiation, and perineural invasion (HR, 1.573; P < .001). Favorable outcomes were observed in patients with distal tumors compared with those with perihilar tumors (HR, 0.773; P < .001) and in those receiving concurrent chemoradiation therapy followed by maintenance chemotherapy (HR, 0.549; P < .001). These factors were integrated into the random survival forest model to generate risk-adjusted survival curves tailored to the RT status. The resulting surveillance strategy, based on a 7% incremental risk, included 8 follow-up visits for RT(-) patients and 9 visits for RT(+) patients over 5 years, with no visits scheduled in year 5 and detection delays of 1.9 and 1.3 months, respectively. This approach yielded incremental cost-effectiveness ratios of $41,227 and $37,469 per quality-adjusted life year for the RT(-) and RT(+) groups, respectively.

A risk-adjusted survival model tailored to prognostic factors and RT status enables individualized surveillance, improves recurrence detection, and reduces unnecessary visits, supporting efficient and cost-effective survivorship care.