Table 3.

Multiparameter logistic regression analysis of proteome and clinical variable contributions to the diagnosis of CC in the retrospective 87-patient cohort. For normalized CA 19-9 and bilirubin serum levels, it was tested if they significantly contribute to CC diagnosis when added to the logistic regression model of combined bile and urine proteome analysis.

Independent variable†	Multivariate logistic regression analysis
	Regression coefficient ± SE	Odds ratio‡ [95% CI]	Significance level (p)
Bile proteome analysis (BPA)	1.83 ± 0.62	6.25 [1.87–20.94]	0.003
Urine proteome analysis (UPA)	2.64 ± 0.67	13.96 [3.73–52.22]	0.0001
Logit BPA/UPA regression model	6.17 ± 1.63	479.16 [19.59–11718.10]	0.00015
+CA19-9	4.48 ± 12.53	32.56 [0.00–1.49E + 12]	0.78
+ bilirubin	1.07 ± 1.17	2.91 [0.29–28.66]	0.36

Abbreviations: CI, confidence interval; ROC, receiver operating characteristic; SE, standard error.

^†All clinical variables were normalized by subtraction of the mean and division by the standard deviation.

^#Regression coefficient expresses the coefficient with which the variable is multiplied in the regression equation.

^‡Odds ratio expresses the amount of change in the logistic regression equation by one unit change in the variable.