The performance of the SEPT9 gene methylation assay and a comparison with other CRC screening tests: A meta-analysis

Abstract

The SEPT9 gene methylation assay is the first FDA-approved blood assay for colorectal cancer (CRC) screening. Fecal immunochemical test (FIT), FIT-DNA test and CEA assay are also in vitro diagnostic (IVD) tests used in CRC screening. This meta-analysis aims to review the SEPT9 assay performance and compare it with other IVD CRC screening tests. By searching the Ovid MEDLINE, EMBASE, CBMdisc and CJFD database, 25 out of 180 studies were identified to report the SEPT9 assay performance. 2613 CRC cases and 6030 controls were included, and sensitivity and specificity were used to evaluate its performance at various algorithms. 1/3 algorithm exhibited the best sensitivity while 2/3 and 1/1 algorithm exhibited the best balance between sensitivity and specificity. The performance of the blood SEPT9 assay is superior to that of the serum protein markers and the FIT test in symptomatic population, while appeared to be less potent than FIT and FIT-DNA tests in asymptomatic population. In conclusion, 1/3 algorithm is recommended for CRC screening, and 2/3 or 1/1 algorithms are suitable for early detection for diagnostic purpose. The SEPT9 assay exhibited better performance in symptomatic population than in asymptomatic population.

Figure 1

The PRISMA flow diagram for literature selection from relevant studies for this meta-analysis. The design of the diagram and the screening of the literatures were based on the PRISMA statement for reporting systematic reviews and meta-analysis^, .

Figure 2

The sROC and forest plots of summary estimates of sensitivity and specificity of SEPT9 assay with various algorithms. The sROC curves and the Forest plots are shown for 1/3 (A), 2/3 (B), 1/2 (C) and 1/1 (D) algorithms. The sROC curves represent the ROC plot of the hierarchical summary estimates of sensitivity and specificity for SEPT9 assay with 95% confidence and prediction ellipses for various algorithms. In the Forest plot, the sensitivity or specificity for each study was plotted as solid squares with bars indicating 95% confidence interval. The red lines indicate the pooled estimates of sensitivity or specificity. The rhombus indicates the 95% confidence interval of the pooled estimates.

Figure 3

The stage-dependent sensitivity for each CRC stage with 1/3, 2/3, 1/2 or 1/1 algorithm. Panel A compares the sensitivity for each CRC stage at each algorithm. It is clear that the sensitivity increased with the elevation of stages, no matter what algorithm was applied. Panel B compares the sensitivity calculated from each algorithm at each CRC stage. Generally, 1/3 algorithm exhibited the highest sensitivity, followed by 2/3, 1/1 and 1/2 algorithms, no matter what stage was compared.

Figure 4

The sensitivity and specificity of the SEPT9 assay were superior to serum protein markers in symptomatic population. The sensitivity of the SEPT9 assay in CRC screening or detection appeared to be much higher than that of the CEA, CA199, CA242, CA50 and CA724, as shown in panel A. In contrast, its specificity was at the same range as these serum protein markers (panel B). Bars indicate 95% confidence interval.

Figure 5

The sensitivity and specificity of the SEPT9 assay were lower than FIT and FIT-DNA tests in asymptomatic population. The sensitivity of the SEPT9 assay in CRC screening in asymptomatic average-risk population appeared to be lower than that of the FIT and FIT-DNA tests, as shown in panel A. Similarly, its specificity was also lower than the other two tests (panel B). Bars indicate 95% confidence interval.

Figure 6

Deeks’ funnel plot asymmetry test for all studies included in this meta-analysis.

Figure 7

Heterogeneity analysis is performed for studies in all four algorithms in SEPT9 assay data interpretation. RR and OR are used as indicators for heterogeneity in 1/3 algorithm (A), 2/3 algorithm (B), 1/2 algorithm (C) and 1/1 algorithm (D). Left figures in each panel represent RR analysis and right figures in each panel represent OR analysis.