Diagnostic and prognostic value of circulating tumor DNA in gastric cancer: a meta-analysis

Yunhe Gao, Kecheng Zhang, Hongqing Xi, Aizhen Cai, Xiaosong Wu, Jianxin Cui, Jiyang Li, Zhi Qiao, Bo Wei, Lin Chen, Yunhe Gao, Kecheng Zhang, Hongqing Xi, Aizhen Cai, Xiaosong Wu, Jianxin Cui, Jiyang Li, Zhi Qiao, Bo Wei, Lin Chen

Abstract

Background: Circulating tumor DNA (ctDNA) has offered a minimally invasive approach for detection and measurement of gastric cancer (GC). However, its diagnostic and prognostic value in gastric cancer still remains unclear.

Results: A total of 16 studies comprising 1193 GC patients met our inclusion criteria. The pooled sensitivity and specificity were 0.62 (95% confidence intervals (CI) 0.59-0.65) and 0.95 (95% CI 0.93-0.96), respectively. The AUSROC (area under SROC) curve was 0.94 (95% CI 0.89-0.98). The results showed that the presence of certain ctDNA markers was associated with larger tumor size (OR: 0.26, 95% CI 0.11-0.61, p = 0.002), TNM stage (I + II/III + IV, OR: 0.11, 95% CI 0.07-0.17, p = 0.000), as well as H. pylori infection. (H.p negative/H.p positive, OR: 0.57, 95% CI 0.36-0.91, p = 0.018). Moreover, there was also a significant association between the presence of ctDNA and worse overall survival (HR 1.77, 95% CI 1.38-2.28, p < 0.001), as well as disease-free survival (HR 4.36, 95% CI 3.08-6.16, p < 0.001).

Materials and methods: Pubmed, Embase, Cochrane Library and Web of Science databases were searched for relating literature published up until November 30, 2016. Diagnostic accuracy variables were pooled by the Meta-Disc software. Engauge Digitizer and Stata software were applied for prognostic data extraction and analysis.

Conclusions: Our meta-analysis indicates the detection of certain ctDNA targets is significantly associated with poor prognosis of GC patients, with high specificity and relatively moderate sensitivity.

Keywords: ctDNA; diagnosis; gastric cancer; meta-analysis; prognosis.

Conflict of interest statement

CONFLICTS OF INTEREST

The authors declare no competing financial interests.

Figures

Figure 1. Flow chart of selection process…
Figure 1. Flow chart of selection process to enroll eligible studies
Figure 2. Summarized genetic alterations arranged by…
Figure 2. Summarized genetic alterations arranged by main gene function
Figure 3. Diagnosis quality assessments of included…
Figure 3. Diagnosis quality assessments of included studies using the QUADAS-2 tool criteria
Figure 4. Diagnostic accuracy forest plots
Figure 4. Diagnostic accuracy forest plots
(A) Forest plots of overall sensitivity. (B) Forest plots of overall specificity. (C) Forest plots of positive likelihood ratio. (D) Forest plots of negative likelihood ratio.
Figure 5. Summary receiver operating characteristic plot…
Figure 5. Summary receiver operating characteristic plot for the included studies with the associated 95% confidence region
Figure 6. Forest plot of the HRs…
Figure 6. Forest plot of the HRs for survival in ctDNA detection of GC patients
(A) Association with overall survival; (B) Association with disease free survival.
Figure 7. Heterogeneity exploration in DFS analysis
Figure 7. Heterogeneity exploration in DFS analysis
(A) Galbraith blot of association between ctDNA and disease free survival; (B) Forest plot of HRs for disease free survival after omission of Yu JL's study.
Figure 8. Funnel plot for the evaluation…
Figure 8. Funnel plot for the evaluation of potential publication bias in the impact of ctDNA on overall survival of GC patients
(A) Begg's funnel plot; (B) Egger's funnel plot.

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