Abstract

BackgroundThe ability to provide accurate prognostic data after hepatectomy for intrahepatic cholangiocarcinoma (ICC) remains poor. We sought to develop and validate a nomogram to predict survival, as well as investigate the clinical implications of underestimating patients’ risk of recurrence. MethodsPatients undergoing curative-intent resection of ICC between 1990 and 2015 at 14 major hepatobiliary centers were included. Variables significant on multivariable analysis were used to construct a nomogram to predict disease-free survival (DFS). The nomogram assigned a score to each variable included in the model and calculated the risk of recurrence. ResultsEight hundred ninety-seven patients are included in the analytic cohort. On multivariable Cox regression analysis, tumor size > 5 cm (HR 1.98, 95% CI 1.44–2.13; p < 0.001), multifocal ICC (HR 1.64, 95% CI 1.32–2.03; p < 0.001), lymph node metastasis (HR 1.63, 95% CI 1.25–2.11; p < 0.001), poorly differentiated tumor grade (HR 1.50, 95% CI 1.21–1.89; p < 0.001), and periductal infiltrating type (PI) morphology (HR 1.42, 95% CI 1.09–1.83; p = 0.008) were independent adverse risk factors associated with decreased DFS. The Harrell’s c-index for the nomogram was 0.633 (with n = 5000 bootstrapping resamples) and the plot comparing predicted and actuarial DFS demonstrated a good calibration of the model. A subset of patients (n = 282) had a DFS worse than predicted (ΔPredicted DFS − Actuarial DFS > 6 months). Moreover, underestimation of a recurrence risk was more common among patients with clinicopathologic features traditionally considered “favorable.” ConclusionA nomogram based on standard clinicopathologic characteristics was suboptimal in its ability to predict accurately risk of recurrence among patients with ICC after curative-intent liver resection. Particularly, the risk of underestimating patient risk of recurrence was highest among patients with historically favorable characteristics. Over one third of patients recurred > 6 months earlier than the DFS predicted by the nomogram.

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