Potential Diagnostic Value of Serum p53 Antibody for Detecting Esophageal Cancer: A Meta-Analysis

Mutant p53 protein overexpression has been reported to induce serum antibodies against p53. Various studies assessing the diagnostic value of serum p53 antibody in patients with esophageal cancer remain controversial. This study aims to comprehensively and quantitatively summarize the potential diagnostic value of serum p53 antibody in esophageal cancer.We systematically searched PubMed and Embase until 31st May 2012, without language restriction. Studies were assessed for quality using QUADAS (quality assessment of studies of diagnostic accuracy). Positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were pooled separately and compared with overall accuracy measures diagnostic odds ratio (DOR) and symmetric summary receiver operating characteristic (sROC). The PLR and NLR and their 95% confidence interval (CI) were calculated using a fixed effects model according to the Mantel-Haensed method and random effects model based on the work of Der Simonian and laird, respectively.Fifteen studies (cases = 1079, controls = 2260) met the inclusion criteria for the meta-analysis. Approximately 53.33% (8/15) of the included studies were of high quality (QUADAS score≥8), which were retrospective case-control studies. The summary estimates for quantitative analysis of serum p53 antibody in the diagnosis of esophageal cancer were PLR 6.95 (95% CI: 4.77–9.51), NLR 0.75 (95%CI: 0.72–0.78) and DOR 9.65 (95%CI: 7.04–13.22). However, we found significant heterogeneity between NLRs.The current evidence suggests serum p53 antibody has a potential diagnostic value for esophageal cancer. However, its discrimination power is not perfect because of low sensitivity.These results suggest that s-p53-antibody may be useful for monitoring residual tumor cells and for aiding in the selection of candidates for less invasive treatment procedures because of the high specificity of s-p53-antibody. Further studies may need to identify patterns of multiple biomarkers to further increase the power of EC detection