Table 1.
Demographic and Clinical Characteristics of PLCO-selected Study Population.
Table 2.
Complete List of Evaluated Biomarkers.
Table 3.
Reproducibility of measurements of representative biomarkers in duplicate PLCO samples.
Table 4.
Performance of Multimarker Combinations in PLCO Training and Validation Sets.
Figure 1.
Biomarker panel performance in the complete PLCO cohort.
A Metropolis algorithm with Monte-Carlo simulation was utilized to identify the top performing biomarker combinations in the discrimination of PDAC cases from matched controls within the PLCO cancer screening trial. ROC curves reflecting the performance of CA 19-9, the top two biomarker panel (CA 19-9/CEA), and the top three biomarker panel (CA 19-9/CEA/Cyfra 21-1) are shown. AUCs for the three models did not differ significantly according to the method of Hanley and McNeil [19].
Figure 2.
Prediagnostic distributions of serum biomarker levels.
Levels of 67 biomarkers were evaluated in sera obtained from 135 subjects enrolled in the PLCO cancer screening trial who were subsequently diagnosed with pancreatic cancer and 540 matched controls. Circulating levels of biomarkers demonstrating significant differences between cases and healthy controls are presented. Level of significance: * - p<0.03, ** - p<0.01, *** - p<0.001, **** - p<0.0001.
Table 5.
Individual Performance of Significantly Altered Serum Biomarkers.
Figure 3.
Biomarker levels in relation to time to diagnosis.
Biomarker levels were plotted against the elapsed time interval between blood draw and cancer diagnosis and plots were evaluated by linear regression. Biomarkers demonstrating slopes differing significantly from zero are presented.