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Review
, 10 (11), e0142080
eCollection

Significance of Serum Pepsinogens as a Biomarker for Gastric Cancer and Atrophic Gastritis Screening: A Systematic Review and Meta-Analysis

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Review

Significance of Serum Pepsinogens as a Biomarker for Gastric Cancer and Atrophic Gastritis Screening: A Systematic Review and Meta-Analysis

Ya-kai Huang et al. PLoS One.

Abstract

Background: Human pepsinogens are considered promising serological biomarkers for the screening of atrophic gastritis (AG) and gastric cancer (GC). However, there has been controversy in the literature with respect to the validity of serum pepsinogen (SPG) for the detection of GC and AG. Consequently, we conducted a systematic review and meta-analysis to assess the diagnostic accuracy of SPG in GC and AG detection.

Methods: We searched PubMed, Embase, and the Chinese National Knowledge Infrastructure (CNKI) for correlative original studies published up to September 30, 2014. The summary sensitivity, specificity, positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR-), area under the summary receiver operating characteristic curve (AUC) and diagnostic odds ratio (DOR) were used to evaluate SPG in GC and AG screening based on bivariate random effects models. The inter-study heterogeneity was evaluated by the I2 statistics and publication bias was assessed using Begg and Mazumdar's test. Meta-regression and subgroup analyses were performed to explore study heterogeneity.

Results: In total, 31 studies involving 1,520 GC patients and 2,265 AG patients were included in the meta-analysis. The summary sensitivity, specificity, DLR+, DLR-, AUC and DOR for GC screening using SPG were 0.69 (95% CI: 0.60-0.76), 0.73 (95% CI: 0.62-0.82), 2.57 (95% CI: 1.82-3.62), and 0.43 (95% CI: 0.34-0.54), 0.76 (95% CI: 0.72-0.80) and 6.01 (95% CI: 3.69-9.79), respectively. For AG screening, the summary sensitivity, specificity, DLR+, DLR-, AUC and DOR were 0.69 (95% CI: 0.55-0.80), 0.88 (95% CI: 0.77-0.94), 5.80 (95% CI: 3.06-10.99), and 0.35 (95% CI: 0.24-0.51), 0.85 (95% CI: 0.82-0.88) and 16.50 (95% CI: 8.18-33.28), respectively. In subgroup analysis, the use of combination of concentration of PGI and the ratio of PGI:PGII as measurement of SPG for GC screening yielded sensitivity of 0.70 (95% CI: 0.66-0.75), specificity of 0.79 (95% CI: 0.79-0.80), DOR of 6.92 (95% CI: 4.36-11.00), and AUC of 0.78 (95% CI: 0.72-0.81), while the use of concentration of PGI yielded sensitivity of 0.55 (95% CI: 0.51-0.60), specificity of 0.79 (95% CI: 0.76-0.82), DOR of 6.88 (95% CI: 2.30-20.60), and AUC of 0.77 (95% CI: 0.73-0.92). For AG screening, the use of ratio of PGI:PGII as measurement of SPG yielded sensitivity of 0.69 (95% CI: 0.52-0.83), specificity of 0.84 (95% CI: 0.68-0.93), DOR of 11.51 (95% CI: 6.14-21.56), and AUC of 0.83 (95% CI: 0.80-0.86), the use of combination of concentration of PGI and the ratio of PGI:PGII yield sensitivity of 0.79 (95% CI: 0.72-0.85), specificity of 0.89 (95% CI: 0.85-0.93), DOR of 24.64 (95% CI: 6.95-87.37), and AUC of 0.87 (95% CI: 0.81-0.92), concurrently, the use of concentration of PGI yield sensitivity of 0.46 (95% CI: 0.38-0.54), specificity of 0.93 (95% CI: 0.91-0.95), DOR of 19.86 (95% CI: 0.86-456.91), and AUC of 0.86 (95% CI: 0.52-1.00).

Conclusion: SPG has great potential as a noninvasive, population-based screening tool in GC and AG screening. In addition, given the potential publication bias and high heterogeneity of the included studies, further high quality studies are required in the future.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flow chart of the included studies.
(a) Flow chart for GC; (b) Flow chart for AG.
Fig 2
Fig 2. Quality assessment of the included studies using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) criteria.
(a) Risk of bias and applicability concerns graph: review authors’ judgements about each domain presented as percentages across the included studies for GC; (b) Risk of bias and applicability concerns summary: review authors’ judgements about each domain for each included study for GC; (c) Risk of bias and applicability concerns graph: review authors’ judgements about each domain presented as percentages across the included studies for AG; (d) Risk of bias and applicability concerns summary: review authors’ judgements about each domain for each included study for AG.
Fig 3
Fig 3. Forest plots of sensitivity, specificity, DLR+, and DLR- for SPG detection in GC.
(a) The summary sensitivity was 0.69 (95% CI: 0.60–0.76; I2 = 88.27%; n = 15); (b) The summary specificity of all articles was 0.73 (95% CI: 0.62–0.82; I2 = 99.61%; n = 15); (c) The summary DLR+ of all articles was 2.57 (95% CI: 1.82–3.62; I2 = 90.39%; n = 15); (d) The summary DLR- of all articles was 0.43 (95% CI: 0.34–0.54; I2 = 85.21% n = 15).
Fig 4
Fig 4. Forest plots of sensitivity, specificity, DLR+, and DLR- for SPG detection in AG.
(a) The summary sensitivity was 0.69 (95% CI: 0.55–0.80; I2 = 93.67%; n = 16); (b) The summary specificity of all articles was 0.88 (95% CI: 0.77–0.94; I2 = 97.57%; n = 16); (c) The summary DLR+ of all articles was 5.80 (95% CI: 3.06–10.99; I2 = 93.82%; n = 16); (d) The summary DLR- of all articles was 0.35 (95% CI: 0.24–0.51; I2 = 96.57% n = 16).
Fig 5
Fig 5. Summary ROC curve (SROC) with 95% confidence region and 95% prediction region.
(a) SROC for SPG in the diagnosis of GC; (b) SROC for SPG in the diagnosis of AG.
Fig 6
Fig 6. Forest plots of DOR for SPG detection in GC and AG.
(a) For GC detection, the DOR was 6.01 (95% CI: 3.69–9.79); (b) For AG detection, the DOR was 16.50 (95% CI: 8.18–33.28).
Fig 7
Fig 7. Fagan’s nomogram was plotted to calculate posterior probabilities.
(a) Fagan plot for GC detection; (b) Fagan plot for AG detection.
Fig 8
Fig 8. Begg’s funnel plot was constructed to demonstrate publication bias.
(a) Begg’s funnel plot for GC; (b) Begg’s funnel plot for AG.

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Grant support

The present study was financially supported by Beijing Municipal Natural Science Foundation of China (No. 7132209; http://www.bjnsf.org/nsf_xmsq/nsf_zzxm/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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