Title: The potential value of serum pepsinogen and gastrin-17 for the diagnosis of chronic
atrophic gastritis at different stages of severity: a clinical diagnostic study
Version: 0 Date: 25 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While 300 participants were included, it would be helpful to mention whether this sample
size is statistically powered to detect significant differences, especially when comparing
subgroups. The study focuses on individuals from a specific region in China, which may
limit generalizability to other populations or regions with different dietary habits, genetics, or
environmental factors.
-The study doesn't seem to address potential confounding factors like dietary patterns, smoking,
or alcohol consumption, which can all affect gastric health and the levels of biomarkers like PG
and G-17. Including such factors in the analysis could strengthen the findings.
-While the study mentions HP infection as an important factor, it doesn't provide detailed insight
into how HP infection may alter PG and G-17 levels specifically in CAG progression. Since
HP is a known risk factor for both CAG and GC, exploring this relationship more deeply could
enhance the study's findings.
-Although the study uses ROC curves to assess the diagnostic accuracy of PG and G-17,
a detailed discussion of the sensitivity, specificity, positive predictive value, and negative
predictive value for these biomarkers across different stages of CAG would be useful. This could
provide a more nuanced understanding of their clinical utility.
-The study is cross-sectional, which limits its ability to track how serum PG and G-17 levels
change over time and how these biomarkers correlate with progression to gastric cancer. A
longitudinal follow-up study would strengthen the argument that these biomarkers can be
predictive of cancer development.
-While the biomarkers are tested, there is limited discussion on the physiological mechanisms
behind their alterations in CAG. Including some background on how PG and G-17 correlate
with gastric mucosal damage could help readers better understand the biological basis for their
diagnostic potential.
-While the study suggests that PGII is more sensitive to HP infection and inflammation, it
would be helpful to delve deeper into the role of PGI in diagnosing the early stages of CAG.
Even though the study found no significant difference in PGI levels across groups, exploring
why PGI’s role might be more limited in detecting CAG progression would add depth to the
interpretation.
-Additionally, the discussion could provide a stronger explanation of the pathophysiology
behind why PGI levels are less effective in later stages of CAG, given the loss of gastric
corpus cells that produce PGI. A more in-depth biological explanation could enhance the clinical
applicability of these biomarkers.
-While the ROC curve results are mentioned, a more detailed discussion of the AUC values and
their clinical implications could be beneficial. For instance, you could explain what the AUC
thresholds indicate in terms of the biomarkers’ diagnostic sensitivity and specificity in detecting
CAG at different stages, especially in comparison with traditional methods like endoscopy.
-Although you mention that the PGR yielded better diagnostic results than PGI, more details on
how PGR performs relative to other diagnostic methods (e.g., biopsy or endoscopy) would be
valuable. The discussion could benefit from exploring why the PGR might be more reliable in
certain subgroups and what advantages it offers over other biomarkers in terms of clinical utility.
Title: The potential value of serum pepsinogen and gastrin-17 for the diagnosis of chronic
atrophic gastritis at different stages of severity: a clinical diagnostic study
Version: 0 Date: 25 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While 300 participants were included, it would be helpful to mention whether this sample
size is statistically powered to detect significant differences, especially when comparing
subgroups. The study focuses on individuals from a specific region in China, which may
limit generalizability to other populations or regions with different dietary habits, genetics, or
environmental factors.
-The study doesn't seem to address potential confounding factors like dietary patterns, smoking,
or alcohol consumption, which can all affect gastric health and the levels of biomarkers like PG
and G-17. Including such factors in the analysis could strengthen the findings.
-While the study mentions HP infection as an important factor, it doesn't provide detailed insight
into how HP infection may alter PG and G-17 levels specifically in CAG progression. Since
HP is a known risk factor for both CAG and GC, exploring this relationship more deeply could
enhance the study's findings.
-Although the study uses ROC curves to assess the diagnostic accuracy of PG and G-17,
a detailed discussion of the sensitivity, specificity, positive predictive value, and negative
predictive value for these biomarkers across different stages of CAG would be useful. This could
provide a more nuanced understanding of their clinical utility.
-The study is cross-sectional, which limits its ability to track how serum PG and G-17 levels
change over time and how these biomarkers correlate with progression to gastric cancer. A
longitudinal follow-up study would strengthen the argument that these biomarkers can be
predictive of cancer development.
-While the biomarkers are tested, there is limited discussion on the physiological mechanisms
behind their alterations in CAG. Including some background on how PG and G-17 correlate
with gastric mucosal damage could help readers better understand the biological basis for their
diagnostic potential.
-While the study suggests that PGII is more sensitive to HP infection and inflammation, it
would be helpful to delve deeper into the role of PGI in diagnosing the early stages of CAG.
Even though the study found no significant difference in PGI levels across groups, exploring
why PGI’s role might be more limited in detecting CAG progression would add depth to the
interpretation.
-Additionally, the discussion could provide a stronger explanation of the pathophysiology
behind why PGI levels are less effective in later stages of CAG, given the loss of gastric
corpus cells that produce PGI. A more in-depth biological explanation could enhance the clinical
applicability of these biomarkers.
-While the ROC curve results are mentioned, a more detailed discussion of the AUC values and
their clinical implications could be beneficial. For instance, you could explain what the AUC
thresholds indicate in terms of the biomarkers’ diagnostic sensitivity and specificity in detecting
CAG at different stages, especially in comparison with traditional methods like endoscopy.
-Although you mention that the PGR yielded better diagnostic results than PGI, more details on
how PGR performs relative to other diagnostic methods (e.g., biopsy or endoscopy) would be
valuable. The discussion could benefit from exploring why the PGR might be more reliable in
certain subgroups and what advantages it offers over other biomarkers in terms of clinical utility.
Please review this paper.
user
Title: The potential value of serum pepsinogen and gastrin-17 for the diagnosis of chronic
atrophic gastritis at different stages of severity: a clinical diagnostic study
Version: 0 Date: 25 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While 300 participants were included, it would be helpful to mention whether this sample
size is statistically powered to detect significant differences, especially when comparing
subgroups. The study focuses on individuals from a specific region in China, which may
limit generalizability to other populations or regions with different dietary habits, genetics, or
environmental factors.
-The study doesn't seem to address potential confounding factors like dietary patterns, smoking,
or alcohol consumption, which can all affect gastric health and the levels of biomarkers like PG
and G-17. Including such factors in the analysis could strengthen the findings.
-While the study mentions HP infection as an important factor, it doesn't provide detailed insight
into how HP infection may alter PG and G-17 levels specifically in CAG progression. Since
HP is a known risk factor for both CAG and GC, exploring this relationship more deeply could
enhance the study's findings.
-Although the study uses ROC curves to assess the diagnostic accuracy of PG and G-17,
a detailed discussion of the sensitivity, specificity, positive predictive value, and negative
predictive value for these biomarkers across different stages of CAG would be useful. This could
provide a more nuanced understanding of their clinical utility.
-The study is cross-sectional, which limits its ability to track how serum PG and G-17 levels
change over time and how these biomarkers correlate with progression to gastric cancer. A
longitudinal follow-up study would strengthen the argument that these biomarkers can be
predictive of cancer development.
-While the biomarkers are tested, there is limited discussion on the physiological mechanisms
behind their alterations in CAG. Including some background on how PG and G-17 correlate
with gastric mucosal damage could help readers better understand the biological basis for their
diagnostic potential.
-While the study suggests that PGII is more sensitive to HP infection and inflammation, it
would be helpful to delve deeper into the role of PGI in diagnosing the early stages of CAG.
Even though the study found no significant difference in PGI levels across groups, exploring
why PGI’s role might be more limited in detecting CAG progression would add depth to the
interpretation.
-Additionally, the discussion could provide a stronger explanation of the pathophysiology
behind why PGI levels are less effective in later stages of CAG, given the loss of gastric
corpus cells that produce PGI. A more in-depth biological explanation could enhance the clinical
applicability of these biomarkers.
-While the ROC curve results are mentioned, a more detailed discussion of the AUC values and
their clinical implications could be beneficial. For instance, you could explain what the AUC
thresholds indicate in terms of the biomarkers’ diagnostic sensitivity and specificity in detecting
CAG at different stages, especially in comparison with traditional methods like endoscopy.
-Although you mention that the PGR yielded better diagnostic results than PGI, more details on
how PGR performs relative to other diagnostic methods (e.g., biopsy or endoscopy) would be
valuable. The discussion could benefit from exploring why the PGR might be more reliable in
certain subgroups and what advantages it offers over other biomarkers in terms of clinical utility.
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