A combined bile and urine proteomic test increases diagnostic accuracy of cholangiocarcinoma in patients with biliary strictures of unknown origin
Background: Detection of cholangiocarcinoma (CC) remains a diagnostic challenge particularly in patients with primary sclerosing cholangitis (PSC) who are at risk for CC development. We recently established diagnostic peptide marker models in bile and urine to detect both local and systemic changes during CC progression. Our aim was to combine both models to reach a higher diagnostic accuracy of CC in patients with unknown biliary strictures.
Methods: On the basis of bile and urine proteomic analysis by capillary electrophoresis mass spectrometry, a case-control phase II study on 87 patients (36 CC including 5 with CC on top of PSC, 33 PSC and 18 other benign disorders) was initiated to elucidate the potential of a combined bile and urine test for CC diagnosis. Furthermore, a logistic regression model based on both proteomic tests was developed to further improve the accuracy of CC diagnosis compared to single bile or urine proteomic test application. Moreover, the tumour marker CA19–9 and bilirubin was combined with both proteomic tests to potentially increase accuracy.
Results: Receiver operating characteristics analysis of proteomic CC-classification of the 87 study patients revealed AUC values of 0.85 in case of bile (odds ratio: 6.2) and 0.93 in case of urine (odds ratio: 14.0). From all tested clinical laboratory parameters only bilirubin and CA19–9 demonstrated acceptable discrimination performance with an AUC above 0.75. A logistic regression model composed of the bile and urine proteomic classification factors lead to an AUC of 0.96, and 92% sensitivity and 84% specificity at the best cut-off. Most notably only three of the 36 CC patients were false negative and two of the 33 PSC patients were false positive classified. Inclusion of CA19–9 and bilirubin values to the logistic regression model was of minor benefit as indicated by small correlation coefficients and insignificant P values for these serological markers.
Conclusion: A logistic regression model combining the classification factors of bile and urine proteome analysis enables CC diagnosis with an accuracy >90% most applicable for patients with biliary strictures of unknown origin referred to endoscopy. This model substantially improves the diagnosis of CC and may lead to early therapy and improved prognosis.