Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 5 (5), 668-676

A Combined Bile and Urine Proteomic Test for Cholangiocarcinoma Diagnosis in Patients With Biliary Strictures of Unknown Origin


A Combined Bile and Urine Proteomic Test for Cholangiocarcinoma Diagnosis in Patients With Biliary Strictures of Unknown Origin

Torsten Voigtländer et al. United European Gastroenterol J.


Background: Detection of cholangiocarcinoma (CC) remains a diagnostic challenge particularly in patients with primary sclerosing cholangitis (PSC). We recently established diagnostic peptide marker models in bile and urine to detect CC. Our aim was to combine both models to reach a higher diagnostic accuracy of CC diagnosis.

Methods: Bile (BPA) and urine (UPA) proteome analysis by capillary electrophoresis mass spectrometry was performed in a case-control phase II study on 87 patients (36 CC including 13 with CC on top of PSC, 33 PSC and 18 other benign disorders). A logistic regression model with both analyses was developed and subsequently validated in a prospective cohort of 45 patients.

Results: In the retrospective study, single BPA and UPA showed sensitivities of 83 and 89 % and specificities of 80 and 86 % with an area under the curve (AUC) value of 0.85 and 0.93. If CC was defined as positive UPA and BPA the combination resulted in a sensitivity of 72 % and a specificity of 96 %. The logistic regression model resulted in an increase in sensitivity to 92 % at 84 % specificity with an AUC of 0.96. Applied to the prospective study cohort, the logistic regression model was superior in its sensitivity (94%) and specificity (76%) over single BPA (63% sensitivity, 69% specificity) and UPA (81% sensitivity, 72% specificity) with an AUC of 0.84.

Conclusion: Our logistic regression model enables CC diagnosis with a higher accuracy than currently available diagnostic tools leading potentially to an earlier diagnosis.

Keywords: Cholangiocarcinoma diagnosis; biliary stricture; primary sclerosing cholangitis; proteomics; tumor marker.


Figure 1.
Figure 1.
Receiver operating characteristic (ROC) curves for classification of the retrospective patient cohort consisting of 36 CC patients of whom 13 have CC on-top-of PSC as case and 33 PSC and 18 non-PSC benign biliary stricture patients as control group by (a) single bile (BPA) and (b) single urine (UPA) proteome analysis. (c) Combination of BPA and UPA for CC diagnosis by a simple majority vote decision model. In this case, CC is defined as a positive test result in both BPA and UPA. In the Cartesian graph, this is true for samples with classification values in the upper right quadrant, designated as BPA/UPA positive area. Contrary, double negative or single positive test results are voted as CC negative.
Figure 2.
Figure 2.
Receiver operating characteristic (ROC) curve for the diagnosis of cholangiocarcinoma (CC) and its discrimination from primary sclerosing cholangitis (PSC) and other benign biliary disorders by the logistic regression model. The regression model showed an increase in the area under ROC curve (AUC) of 0.11 compared to bile proteome analysis (p = 0.009) and 0.03 compared to urine proteome analysis (p = 0.112) by improving sensitivity of CC diagnosis at the same level of specificity in comparison to the single proteomic tests presented in Figure 1(a) and (b).
Figure 3.
Figure 3.
Classification of the prospective patient cohort consisting of 28 patients with primary sclerosing cholangitis (PSC) and one patient with common bile duct dilatation (CBDD) as negative group and 16 cholangiocarcinoma (CC) (including six with CC on-top-of PSC) patients as positive group by the BPA/UPA logistic regression model in comparison to single bile (BPA) or urine (UPA) proteome analysis.

Similar articles

See all similar articles

Cited by 5 articles

LinkOut - more resources