Title: Novel Nomogram to Predict the Overall Survival of Postoperative Patients with Gastric
Signet
Version: 2 Date: 22 May 2023
Reviewer:  Sharvesh Raj Seeruttun
Reviewer's report:
1. Abstract:
(a) Methods: "randomly assigned to training and validation", do you mean "internal validation"?
Please make sure to clarify the different groups and use the same term consistently throughout
the whole text, including figures and tables. E.g.: in figure 6, it is mentioned "SEER testing"
(b) More data would be useful regarding 1-, 3-, and 5-year  ROC and OS in the Results.
(c) since this is a retrospective study, in the conclusion kindly consider revising "will help doctors
" to "may help doctors "
Introduction:
1. I agree the the TNM classification is not ideal for perfectly predicting the survival of GC
patients, but based on current guidelines, all non-early cases should undergo some sort of
adjuvant therapy (of course depending of high risk factors, cancer location, etc.). So, what is
the importance of this nomogram despite better OS prediction and stratifiction, there seems to
be no significant difference in patient selectability between the proposed nomogram and TNM
for treatment recommendation.
I would suggest:
(a) in the introdcution address how the TNM is limited in treatment selection for different stages
and what would be an ideal solution
(b) in the discussion, based on your results, please properly discuss how your nomogram is able
to be better used to stratify patient based on different stages for more individualized treatment.
2. Introduction: The main current issue with gastric cancer affecting OS is treatment outcomes.
Thus, please provide a good introduction about how the treatment of GSRC is different from
other types of GC. Also, consider using reference PMID: 34197702.
Methods:
1. Please clarify based on which  AJCC TNM classification were the patients staged
2. Study inclusion and exclusion criteria seems to limited, more clarification required. E.g.:
treatment naive? all R0 cases? type of gastrectomy? etc.
3. Statistical analysis for determining the number of cases required for the external validation
was not clarified.
Results:
1. Label for the Key of figure 2 a, d missing. Also, what does "larger high population" mean?
Further, key for the different colors in the other panels seems missing.
2. Seems confusing how can Stage and T, N, M be used for univariate analysis? These seems
to be conflicting, thus, the whole results should be double checked, including the variable used
for constructing the nomogram.
3. Another big concern of this work is that only surgery in not enough to improve the OS
of patients, this is why adjuvant therapies are recommended. However, none such variables
were accounted in this study. This indeed significantly impact the credibility of the proposed
nomogram.
4.Figures seems inconsistent for publication, e.g.: keys missing in some, terms used not
consistent with the text, avoid only mentioned survival better be more specific by using overall
survival
Discussion
1. Pay more attention to focus the discussion on how patients stratification using this nomogram
may indeed help clinical practice to better chose patients, based on different stages, for
individualized therapy.
2. How did the authors account for the different treatment prescribed in the US and China, and
how could these might have affected patient selection and the study results?
Title: Novel Nomogram to Predict the Overall Survival of Postoperative Patients with Gastric
Signet
Version: 2 Date: 22 May 2023
Reviewer:  Sharvesh Raj Seeruttun
Reviewer's report:
1. Abstract:
(a) Methods: "randomly assigned to training and validation", do you mean "internal validation"?
Please make sure to clarify the different groups and use the same term consistently throughout
the whole text, including figures and tables. E.g.: in figure 6, it is mentioned "SEER testing"
(b) More data would be useful regarding 1-, 3-, and 5-year  ROC and OS in the Results.
(c) since this is a retrospective study, in the conclusion kindly consider revising "will help doctors
" to "may help doctors "
Introduction:
1. I agree the the TNM classification is not ideal for perfectly predicting the survival of GC
patients, but based on current guidelines, all non-early cases should undergo some sort of
adjuvant therapy (of course depending of high risk factors, cancer location, etc.). So, what is
the importance of this nomogram despite better OS prediction and stratifiction, there seems to
be no significant difference in patient selectability between the proposed nomogram and TNM
for treatment recommendation.
I would suggest:
(a) in the introdcution address how the TNM is limited in treatment selection for different stages
and what would be an ideal solution
(b) in the discussion, based on your results, please properly discuss how your nomogram is able
to be better used to stratify patient based on different stages for more individualized treatment.
2. Introduction: The main current issue with gastric cancer affecting OS is treatment outcomes.
Thus, please provide a good introduction about how the treatment of GSRC is different from
other types of GC. Also, consider using reference PMID: 34197702.
Methods:
1. Please clarify based on which  AJCC TNM classification were the patients staged
2. Study inclusion and exclusion criteria seems to limited, more clarification required. E.g.:
treatment naive? all R0 cases? type of gastrectomy? etc.
3. Statistical analysis for determining the number of cases required for the external validation
was not clarified.
Results:
1. Label for the Key of figure 2 a, d missing. Also, what does "larger high population" mean?
Further, key for the different colors in the other panels seems missing.
2. Seems confusing how can Stage and T, N, M be used for univariate analysis? These seems
to be conflicting, thus, the whole results should be double checked, including the variable used
for constructing the nomogram.
3. Another big concern of this work is that only surgery in not enough to improve the OS
of patients, this is why adjuvant therapies are recommended. However, none such variables
were accounted in this study. This indeed significantly impact the credibility of the proposed
nomogram.
4.Figures seems inconsistent for publication, e.g.: keys missing in some, terms used not
consistent with the text, avoid only mentioned survival better be more specific by using overall
survival
Discussion
1. Pay more attention to focus the discussion on how patients stratification using this nomogram
may indeed help clinical practice to better chose patients, based on different stages, for
individualized therapy.
2. How did the authors account for the different treatment prescribed in the US and China, and
how could these might have affected patient selection and the study results?
Please review this paper.
user
Title: Novel Nomogram to Predict the Overall Survival of Postoperative Patients with Gastric
Signet
Version: 2 Date: 22 May 2023
Reviewer:  Sharvesh Raj Seeruttun
Reviewer's report:
1. Abstract:
(a) Methods: "randomly assigned to training and validation", do you mean "internal validation"?
Please make sure to clarify the different groups and use the same term consistently throughout
the whole text, including figures and tables. E.g.: in figure 6, it is mentioned "SEER testing"
(b) More data would be useful regarding 1-, 3-, and 5-year  ROC and OS in the Results.
(c) since this is a retrospective study, in the conclusion kindly consider revising "will help doctors
" to "may help doctors "
Introduction:
1. I agree the the TNM classification is not ideal for perfectly predicting the survival of GC
patients, but based on current guidelines, all non-early cases should undergo some sort of
adjuvant therapy (of course depending of high risk factors, cancer location, etc.). So, what is
the importance of this nomogram despite better OS prediction and stratifiction, there seems to
be no significant difference in patient selectability between the proposed nomogram and TNM
for treatment recommendation.
I would suggest:
(a) in the introdcution address how the TNM is limited in treatment selection for different stages
and what would be an ideal solution
(b) in the discussion, based on your results, please properly discuss how your nomogram is able
to be better used to stratify patient based on different stages for more individualized treatment.
2. Introduction: The main current issue with gastric cancer affecting OS is treatment outcomes.
Thus, please provide a good introduction about how the treatment of GSRC is different from
other types of GC. Also, consider using reference PMID: 34197702.
Methods:
1. Please clarify based on which  AJCC TNM classification were the patients staged
2. Study inclusion and exclusion criteria seems to limited, more clarification required. E.g.:
treatment naive? all R0 cases? type of gastrectomy? etc.
3. Statistical analysis for determining the number of cases required for the external validation
was not clarified.
Results:
1. Label for the Key of figure 2 a, d missing. Also, what does "larger high population" mean?
Further, key for the different colors in the other panels seems missing.
2. Seems confusing how can Stage and T, N, M be used for univariate analysis? These seems
to be conflicting, thus, the whole results should be double checked, including the variable used
for constructing the nomogram.
3. Another big concern of this work is that only surgery in not enough to improve the OS
of patients, this is why adjuvant therapies are recommended. However, none such variables
were accounted in this study. This indeed significantly impact the credibility of the proposed
nomogram.
4.Figures seems inconsistent for publication, e.g.: keys missing in some, terms used not
consistent with the text, avoid only mentioned survival better be more specific by using overall
survival
Discussion
1. Pay more attention to focus the discussion on how patients stratification using this nomogram
may indeed help clinical practice to better chose patients, based on different stages, for
individualized therapy.
2. How did the authors account for the different treatment prescribed in the US and China, and
how could these might have affected patient selection and the study results?
assistant