Title: Construction and validation of a novel nomogram based on the log odds of positive lymph
nodes to predict cancer-specific survival in elderly patients with gastric adenocarcinoma after
radical surgery
Version: 1 Date: 12 Jan 2025
Reviewer's report:
I would like to thank the authors for submitting their research findings. The authors are using
some advanced methods to develop a model for predicting cancer-specific survival in elderly
patients with gastric adenocarcinoma after gastrectomy. The effort is commendable. There are
also some concerns about the manuscript.
Major Comments:
1.) Previous studies have found that the log odds of positive lymph nodes (LODDS) seems
to be the most reliable lymph node classification in predicting the prognosis of patients
with resected gastric adenocarcinoma. Ex: "Prognostic Nomograms Based on Three Lymph
Node Classification Systems for Resected Gastric Adenocarcinoma: A Large Population-
Based Cohort Study and External Validation. Ann Surg Oncol. 2021 Dec;28(13):8937-8949.
doi:10.1245/s10434-021-10299-1." I suggest that this study should fully explain the inadequacy
of previous related studies in the introduction section, so as to draw out the significance and
value of conducting this study more precisely. I do not recommend dedicating a large amount of
space in the introduction section to the SEER database and the nomogram as a predictive tool. In
addition, the discussion section should provide an in-depth discussion of each of the results, e.g.,
which predictors were included in this study for model construction, what are the similarities
and differences with previous studies, and what are the possible reasons for the differences in
the results should be considered.
2.) The AUC is good, but not outstanding, suggesting that there are other factors that are not
included. There are also methodologic concerns with model construction in this highly selected
population: On Page 3, Line 33 - the authors state that variables showing statistical significance
(P<0.05) in the univariate Cox analysis were included in the LASSO equation for feature
selection. Why not use the LASSO to select the most significant prognostic variables of all initial
variables? By performing both variable selection and penalization, the LASSO is able to build
accurate models without under-fitting or overfitting, which leads to superior performance over
traditional multivariable regression (Tibshirani R. Regression shrinkage and selection via the
lasso. Journal of the Royal Statistical Society: Series B (Methodological). 1996; 58:267-288).
3.) It seems to me that the title and the abstract section should be rewritten. I would not
recommend using the abbreviations “LODDS” and “SEER” in the title. In the results of the
abstract section, I would suggest describing which prognostic variables were identified to
construct the nomogram, rather than “The nomogram was constructed based on multivariate
analysis results”, which should be in the methods section.
Minor Comments:
1.) Abstract:
a. Objective: Since only one predictive model was constructed in this manuscript, “and to
construct relevant survival prediction models” should be “and to construct a/the relevant survival
prediction model”.
b. Methods: “construct nomogram” should be “construct a/the nomogram”. “of nomogram”
should be “of the nomogram”.
2.) INTRODUCTION: “For instance, The latest research” should be “For instance, the latest
research”. (Page 2, Line 13)
3.) Table 1: As a reader, I would like to know the P value between cohorts.
4.) Could you please explain the N stage in the nomogram. Why N1 get more points than N2?
In the univariate analysis of table2, HR of N2 is higher than N1.
5.) This study focused only on constructing the model for cancer-specific survival prediction.
Why not also perform overall survival prediction for this study population?
6.) I would recommend establishing the user-friendly dynamic nomogram if possible.
Title: Construction and validation of a novel nomogram based on the log odds of positive lymph
nodes to predict cancer-specific survival in elderly patients with gastric adenocarcinoma after
radical surgery
Version: 1 Date: 12 Jan 2025
Reviewer's report:
I would like to thank the authors for submitting their research findings. The authors are using
some advanced methods to develop a model for predicting cancer-specific survival in elderly
patients with gastric adenocarcinoma after gastrectomy. The effort is commendable. There are
also some concerns about the manuscript.
Major Comments:
1.) Previous studies have found that the log odds of positive lymph nodes (LODDS) seems
to be the most reliable lymph node classification in predicting the prognosis of patients
with resected gastric adenocarcinoma. Ex: "Prognostic Nomograms Based on Three Lymph
Node Classification Systems for Resected Gastric Adenocarcinoma: A Large Population-
Based Cohort Study and External Validation. Ann Surg Oncol. 2021 Dec;28(13):8937-8949.
doi:10.1245/s10434-021-10299-1." I suggest that this study should fully explain the inadequacy
of previous related studies in the introduction section, so as to draw out the significance and
value of conducting this study more precisely. I do not recommend dedicating a large amount of
space in the introduction section to the SEER database and the nomogram as a predictive tool. In
addition, the discussion section should provide an in-depth discussion of each of the results, e.g.,
which predictors were included in this study for model construction, what are the similarities
and differences with previous studies, and what are the possible reasons for the differences in
the results should be considered.
2.) The AUC is good, but not outstanding, suggesting that there are other factors that are not
included. There are also methodologic concerns with model construction in this highly selected
population: On Page 3, Line 33 - the authors state that variables showing statistical significance
(P<0.05) in the univariate Cox analysis were included in the LASSO equation for feature
selection. Why not use the LASSO to select the most significant prognostic variables of all initial
variables? By performing both variable selection and penalization, the LASSO is able to build
accurate models without under-fitting or overfitting, which leads to superior performance over
traditional multivariable regression (Tibshirani R. Regression shrinkage and selection via the
lasso. Journal of the Royal Statistical Society: Series B (Methodological). 1996; 58:267-288).
3.) It seems to me that the title and the abstract section should be rewritten. I would not
recommend using the abbreviations “LODDS” and “SEER” in the title. In the results of the
abstract section, I would suggest describing which prognostic variables were identified to
construct the nomogram, rather than “The nomogram was constructed based on multivariate
analysis results”, which should be in the methods section.
Minor Comments:
1.) Abstract:
a. Objective: Since only one predictive model was constructed in this manuscript, “and to
construct relevant survival prediction models” should be “and to construct a/the relevant survival
prediction model”.
b. Methods: “construct nomogram” should be “construct a/the nomogram”. “of nomogram”
should be “of the nomogram”.
2.) INTRODUCTION: “For instance, The latest research” should be “For instance, the latest
research”. (Page 2, Line 13)
3.) Table 1: As a reader, I would like to know the P value between cohorts.
4.) Could you please explain the N stage in the nomogram. Why N1 get more points than N2?
In the univariate analysis of table2, HR of N2 is higher than N1.
5.) This study focused only on constructing the model for cancer-specific survival prediction.
Why not also perform overall survival prediction for this study population?
6.) I would recommend establishing the user-friendly dynamic nomogram if possible.
Please review this paper.
user
Title: Construction and validation of a novel nomogram based on the log odds of positive lymph
nodes to predict cancer-specific survival in elderly patients with gastric adenocarcinoma after
radical surgery
Version: 1 Date: 12 Jan 2025
Reviewer's report:
I would like to thank the authors for submitting their research findings. The authors are using
some advanced methods to develop a model for predicting cancer-specific survival in elderly
patients with gastric adenocarcinoma after gastrectomy. The effort is commendable. There are
also some concerns about the manuscript.
Major Comments:
1.) Previous studies have found that the log odds of positive lymph nodes (LODDS) seems
to be the most reliable lymph node classification in predicting the prognosis of patients
with resected gastric adenocarcinoma. Ex: "Prognostic Nomograms Based on Three Lymph
Node Classification Systems for Resected Gastric Adenocarcinoma: A Large Population-
Based Cohort Study and External Validation. Ann Surg Oncol. 2021 Dec;28(13):8937-8949.
doi:10.1245/s10434-021-10299-1." I suggest that this study should fully explain the inadequacy
of previous related studies in the introduction section, so as to draw out the significance and
value of conducting this study more precisely. I do not recommend dedicating a large amount of
space in the introduction section to the SEER database and the nomogram as a predictive tool. In
addition, the discussion section should provide an in-depth discussion of each of the results, e.g.,
which predictors were included in this study for model construction, what are the similarities
and differences with previous studies, and what are the possible reasons for the differences in
the results should be considered.
2.) The AUC is good, but not outstanding, suggesting that there are other factors that are not
included. There are also methodologic concerns with model construction in this highly selected
population: On Page 3, Line 33 - the authors state that variables showing statistical significance
(P<0.05) in the univariate Cox analysis were included in the LASSO equation for feature
selection. Why not use the LASSO to select the most significant prognostic variables of all initial
variables? By performing both variable selection and penalization, the LASSO is able to build
accurate models without under-fitting or overfitting, which leads to superior performance over
traditional multivariable regression (Tibshirani R. Regression shrinkage and selection via the
lasso. Journal of the Royal Statistical Society: Series B (Methodological). 1996; 58:267-288).
3.) It seems to me that the title and the abstract section should be rewritten. I would not
recommend using the abbreviations “LODDS” and “SEER” in the title. In the results of the
abstract section, I would suggest describing which prognostic variables were identified to
construct the nomogram, rather than “The nomogram was constructed based on multivariate
analysis results”, which should be in the methods section.
Minor Comments:
1.) Abstract:
a. Objective: Since only one predictive model was constructed in this manuscript, “and to
construct relevant survival prediction models” should be “and to construct a/the relevant survival
prediction model”.
b. Methods: “construct nomogram” should be “construct a/the nomogram”. “of nomogram”
should be “of the nomogram”.
2.) INTRODUCTION: “For instance, The latest research” should be “For instance, the latest
research”. (Page 2, Line 13)
3.) Table 1: As a reader, I would like to know the P value between cohorts.
4.) Could you please explain the N stage in the nomogram. Why N1 get more points than N2?
In the univariate analysis of table2, HR of N2 is higher than N1.
5.) This study focused only on constructing the model for cancer-specific survival prediction.
Why not also perform overall survival prediction for this study population?
6.) I would recommend establishing the user-friendly dynamic nomogram if possible.
assistant