Validation of four candidate pancreatic cancer serological biomarkers that improve the performance of CA19.9

BMC Cancer

Table 4 Biomarker modeling in independent validation set (Sample Set A)

Biomarker combination^a	AUC^b of combination	Lower 95% confidence interval	Upper 95% confidence interval	p-value of AUC of panel compared to AUC of CA19.9
CA19.9 REG1B	0.875	0.825	0.918	0.001
CA19.9 SYCN REG1B	0.873	0.823	0.918	0.033
CA19.9 AGR2 REG1B	0.869	0.816	0.913	0.004
CA19.9 REG1B LOXL2	0.859	0.803	0.907	0.071
CA19.9 SYCN AGR2	0.858	0.804	0.907	0.117
CA19.9 SYCN	0.857	0.804	0.905	0.157
CA19.9 SYCN LOXL2	0.850	0.792	0.901	0.276
CA19.9 AGR2	0.824	0.764	0.883	0.946
CA19.9	0.824	0.765	0.877	1.000
CA19.9 AGR2 LOXL2	0.805	0.741	0.863	0.296
CA19.9 LOXL2	0.803	0.740	0.864	0.246
SYCN REG1B	0.782	0.716	0.845	0.297
SYCN REG1B LOXL2	0.776	0.707	0.842	0.264
SYCN AGR2 REG1B	0.774	0.708	0.834	0.243
REG1B LOXL2	0.747	0.677	0.813	0.086
AGR2 REG1B LOXL2	0.709	0.636	0.779	0.009
SYCN AGR2	0.706	0.634	0.778	0.009
SYCN AGR2 LOXL2	0.702	0.622	0.771	0.008
SYCN LOXL2	0.701	0.625	0.775	0.011
AGR2 REG1B	0.680	0.600	0.757	0.002
AGR2 LOXL2	0.582	0.493	0.660	0.000

^aBiomarker models for two and three marker combinations generated in PDAC versus disease-free controls of Sample Set B and presented in Table 3 were validated in PDAC (n = 100) versus healthy controls (n = 92) of Sample Set A and ordered from greatest to lowest AUC. Confidence intervals (CI) for AUC were calculated using DeLong’s method. The top three models showed a significant improvement in AUC to that of CA19.9 alone. P-values were calculated by taking 2000 stratified bootstrap samples; ^bAUC, area under the receiver operating characteristic curve; PDAC, pancreatic ductal adenocarcinoma.

ISSN: 1471-2407