Circulating Cell Free DNA as the Diagnostic Marker for Ovarian Cancer: A Systematic Review and Meta-Analysis. - Quan Zhou; Wei Li; Bingjie Leng; Wenfei Zheng; Ze He; Manzhen Zuo; Aihua Chen (PLoS ONE, 2016)
Background Quantitative analyses of circulating cell-free DNA (cfDNA) are potential methods for the detection of ovarian cancer. Many studies have evaluated these approaches, but the results were too inconsistent to be conclusive. This study is the first to systematically evaluate the accuracy of circulating cfDNA for the diagnosis of ovarian cancer by conducting meta-analysis. Methods We searched PubMed, Embase, Cochrane Library and the Chinese National Knowledge Infrastructure (CNKI) databases systematically for relevant literatures up to December 10, 2015. All analyses were conducted using Meta-DiSc1.4 and Stata 12.0 software. Sensitivity, specificity and other measures of accuracy of circulating cfDNA for the diagnosis of ovarian cancer were pooled. Meta-regression was performed to identify the sources of heterogeneity. Results This meta-analysis included a total of 9 studies, including 462 ovarian cancer patients and 407 controls. The summary estimates for quantitative analysis of circulating cfDNA in ovarian cancer screen were as follows: sensitivity, 0.70 (95% confidence interval (CI), 0.65-0.74); specificity, 0.90 (95% CI, 0.87-0.93); positive likelihood ratio, 6.60 (95% CI, 3.90-11.17); negative likelihood ratio, 0.34 (95% CI, 0.25-0.47); diagnostic odds ratio, 26.05 (95% CI, 14.67-46.26); and area under the curve, 0.89 (95% CI, 0.83-0.95), respectively. There was no statistical significance for the evaluation of publication bias. Conclusions Current evidence suggests that quantitative analysis of cfDNA has unsatisfactory sensitivity but acceptable specificity for the diagnosis of ovarian cancer. Further large-scale prospective studies are required to validate the potential applicability of using circulating cfDNA alone or in combination with conventional markers as diagnostic biomarker for ovarian cancer and explore potential factors that may influence the accuracy of ovarian cancer diagnosis.