A Systematic Review and Meta-Analysis of Diagnostic and Prognostic Serum Biomarkers of Colorectal Cancer

<div><p>Background</p><p>Our systematic review summarizes the evidence concerning the accuracy of serum diagnostic and prognostic tests for colorectal cancer (CRC).</p><p>Methods</p><p>The databases MEDLINE and EMBASE were searched iteratively to identify the relevant literature for serum markers of CRC published from 1950 to August 2012. The articles that provided adequate information to meet the requirements of the meta-analysis of diagnostic and prognostic markers were included. A 2-by-2 table of each diagnostic marker and its hazard ratio (HR) and the confidence interval (CI) of each prognostic marker was directly or indirectly extracted from the included papers, and the pooled sensitivity and specificity of the diagnostic marker and the pooled HR and the CI of the prognostic marker were subsequently calculated using the extracted data.</p><p>Results</p><p>In total, 104 papers related to the diagnostic markers and 49 papers related to the prognostic serum markers of CRC were collected, and only 19 of 92 diagnostic markers were investigated in more than two studies, whereas 21 out of 44 prognostic markers were included in two or more studies. All of the pooled sensitivities of the diagnostic markers with > = 3 repetitions were less than 50%, and the meta-analyses of the prognostic markers with more than 3 studies were performed, VEGF with highest (2.245, CI: 1.347–3.744) and MMP-7 with lowest (1.099, CI: 1.018–1.187)) pooled HRs are presented.</p><p>Conclusions</p><p>The quality of studies addressing the diagnostic and prognostic accuracy of the tests was poor, and the results were highly heterogeneous. The poor characteristics indicate that these tests are of little value for clinical practice.</p></div

Results of the meta-analysis of the diagnostic markers for colorectal cancer.

<p>Notes: If the number of is more than three, the HSROC Plot and forest plot can be drawn, if the number of studies is more than two, only the forest plot can be drawn. Reference IDs to these studies are prefaced by a ‘D’ and listed in Appendix 4 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103910#pone.0103910.s007" target="_blank">Materials S1</a>. Y denotes Yes; N denotes No; N/A denotes not applicable, which means the value is not available. If the number of the studies is less than three, the p value of publication bias cannot be calculated. In addition, the false positive rate of marker P53 is zero, and then the odd ratio (OD) cannot be calculated, so all values are not applicable.</p

The flowchart of the selection of the relevant articles.

<p>The flowchart of the selection of the relevant articles.</p

Meta-analysis plots of the progression-free and overall survival hazard ratios in individual trials.

<p>A is the forest plot and B, C, and D are the “filled” funnel plots of OS, DFS, and the unclear group, respectively. The meta-analysis displayed a significant effect in favor of a high volume. The pooled and filled results are presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103910#pone-0103910-t002" target="_blank">Table 2</a>.</p

Summary of quality of the included studies, according to the QUADAS criteria (see Table S2 for details).

<p>Summary of quality of the included studies, according to the QUADAS criteria (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103910#pone.0103910.s002" target="_blank">Table S2</a> for details).</p

The ROC and forest plots of summary estimates of sensitivity and specificity of diagnostic marker CEA.

<p>A is the ROC plot of the hierarchical summary estimates of sensitivity and specificity for CEA with 95% confidence and prediction ellipses. B and C are forest plots of sensitivity and specificity of the diagnostic marker CEA for colorectal cancer plotted with a HSROC model. The size of the squares in B and C are proportional to the study size and weight for each study. The rhombus represents the pooled estimates, which are 0.461 (CI: 0.448–0.474) and 0.892 (CI: 0.882–0.902) for specificity and sensitivity, respectively.</p

Effect of pulse current on SOD, MDA and glycogen contents of liver.

(1)<p>Compared with control group: P>0.05;</p>(2)<p>Compared with control group: P<0.05;</p>(3)<p>Compared with exercise training group: P<0.05.</p

Effect of pulse current on the expression of Bcl-2 and Bax.

(1)<p>Compared with control group: P>0.05;</p>(2)<p>Compared with training group: P>0.05;</p>(3)<p>Compared with control group: P<0.05;</p>(4)<p>Compared with training group: P<0.05.</p

Sections of liver tissue were stained with hematoxylin and eosin.

<p>A, control group; B, five weeks exercise-training group; C, five weeks stimulating group.</p

Effect of pulse current on swimming time to exhaustion of rats.

(1)<p>Compared with control group: P>0.05;</p>(2)<p>Compared with training group, P>0.05;</p>(3)<p>Compared with control group: P<0.05;</p>(4)<p>Compared with training group, P<0.05;</p>(5)<p>Compared with A and C group: P<0.05;</p>(6)<p>Compared with A group: P>0.05.</p