Title: Using a nomogram based on the controlling nutritional status score to predict prognosis
after surgery in patients with resectable gastric cancer
Version: 0 Date: 21 Jan 2024
Reviewer's report:
The authors reported “using a nomogram based on the controlling nutritional status score to
predict prognosis after surgery in patients with resectable gastric cancer”. The authors concluded
that the nomogram model based on the CONUT score is a credible model for predicting the
postoperative survival of GC patients and provides a crucial foundation for developing tailored
postoperative therapy regimens..
However, there are many problems in this paper, I think.
1. In the first place, it is doubtful whether it is possible to create an excellent predictive model
with a combination of about only 4 factors.
2. I believe that both count score and nerve invasion are not factors that are used in daily clinical
practice and lack simplicity. The bigger drawback is that it takes time and effort unless the
predictive ability of this model is very good.
3. The authors should present the Kaplan-Meier survival curves based upon AJCC (UICC)
staging with number at risk.
4. There are many studies regarding to nomogram. It would be of little value to publish unless
the authors describe in detail how this model changes daily clinical practice.
5. Why did the authors include AJCC (UICC) staging as a factor to construct the nomogram?
AJCC Staging is made up of a combination of T and N. Most researchers usually create a model
with T and N as separate and independent factors to improve predictive ability.
6. I find it a little strange that treatment factors (type of gastrectomy) and prognostic factors are
treated as prognostic factors of the same dimension.
7. The authors categorized COUNT score (originally continuous variable). Harrell’s guideline
(Harrell FE. Regression Modeling Strategies: With Applications to Linear Models, Logistic
Regression, and Survival Analysis. 2nd edition. New York: Springer; 2015) emphasized
avoiding the categorization of continuous variables because some categorical variables are
subjective and hard to standardize and do not contain the same amount of statistical information
as continuous variables.
Title: Using a nomogram based on the controlling nutritional status score to predict prognosis
after surgery in patients with resectable gastric cancer
Version: 0 Date: 21 Jan 2024
Reviewer's report:
The authors reported “using a nomogram based on the controlling nutritional status score to
predict prognosis after surgery in patients with resectable gastric cancer”. The authors concluded
that the nomogram model based on the CONUT score is a credible model for predicting the
postoperative survival of GC patients and provides a crucial foundation for developing tailored
postoperative therapy regimens..
However, there are many problems in this paper, I think.
1. In the first place, it is doubtful whether it is possible to create an excellent predictive model
with a combination of about only 4 factors.
2. I believe that both count score and nerve invasion are not factors that are used in daily clinical
practice and lack simplicity. The bigger drawback is that it takes time and effort unless the
predictive ability of this model is very good.
3. The authors should present the Kaplan-Meier survival curves based upon AJCC (UICC)
staging with number at risk.
4. There are many studies regarding to nomogram. It would be of little value to publish unless
the authors describe in detail how this model changes daily clinical practice.
5. Why did the authors include AJCC (UICC) staging as a factor to construct the nomogram?
AJCC Staging is made up of a combination of T and N. Most researchers usually create a model
with T and N as separate and independent factors to improve predictive ability.
6. I find it a little strange that treatment factors (type of gastrectomy) and prognostic factors are
treated as prognostic factors of the same dimension.
7. The authors categorized COUNT score (originally continuous variable). Harrell’s guideline
(Harrell FE. Regression Modeling Strategies: With Applications to Linear Models, Logistic
Regression, and Survival Analysis. 2nd edition. New York: Springer; 2015) emphasized
avoiding the categorization of continuous variables because some categorical variables are
subjective and hard to standardize and do not contain the same amount of statistical information
as continuous variables.
Please review this paper.
user
Title: Using a nomogram based on the controlling nutritional status score to predict prognosis
after surgery in patients with resectable gastric cancer
Version: 0 Date: 21 Jan 2024
Reviewer's report:
The authors reported “using a nomogram based on the controlling nutritional status score to
predict prognosis after surgery in patients with resectable gastric cancer”. The authors concluded
that the nomogram model based on the CONUT score is a credible model for predicting the
postoperative survival of GC patients and provides a crucial foundation for developing tailored
postoperative therapy regimens..
However, there are many problems in this paper, I think.
1. In the first place, it is doubtful whether it is possible to create an excellent predictive model
with a combination of about only 4 factors.
2. I believe that both count score and nerve invasion are not factors that are used in daily clinical
practice and lack simplicity. The bigger drawback is that it takes time and effort unless the
predictive ability of this model is very good.
3. The authors should present the Kaplan-Meier survival curves based upon AJCC (UICC)
staging with number at risk.
4. There are many studies regarding to nomogram. It would be of little value to publish unless
the authors describe in detail how this model changes daily clinical practice.
5. Why did the authors include AJCC (UICC) staging as a factor to construct the nomogram?
AJCC Staging is made up of a combination of T and N. Most researchers usually create a model
with T and N as separate and independent factors to improve predictive ability.
6. I find it a little strange that treatment factors (type of gastrectomy) and prognostic factors are
treated as prognostic factors of the same dimension.
7. The authors categorized COUNT score (originally continuous variable). Harrell’s guideline
(Harrell FE. Regression Modeling Strategies: With Applications to Linear Models, Logistic
Regression, and Survival Analysis. 2nd edition. New York: Springer; 2015) emphasized
avoiding the categorization of continuous variables because some categorical variables are
subjective and hard to standardize and do not contain the same amount of statistical information
as continuous variables.
assistant