Title: A Preliminary Exploration of a Predictive Model and Nomogram for the Efficacy of
Compound Digestive Enzyme Therapy Based on Serum (PG#, PG#, VIP, and PRDX1) in
Patients with Functional Dyspepsia
Version: 0 Date: 05 Apr 2025
Reviewer's report:
Overall Evaluation
This study aims to construct a predictive model and a nomogram for the efficacy of combined
digestive enzymes in patients with functional dyspepsia (FD) based on serum PG#, PG#, VIP
and PRDX1. The research topic is of clinical significance, and the overall methodology design
is reasonable. The result analysis is relatively sufficient. The model shows high discrimination
in both the training set and the validation set (AUC # 0.83), suggesting its potential application
value. However, the study has the following issues that need to be focused on and further clarified
or improved.
1. The research type was not clearly stated.
2. Sample size and validation set: The validation set only included 75 cases (accounting for 30%
of the total sample), which is relatively small and may affect the external validity assessment.
It is recommended to supplement external validation (such as multi-center data) to enhance the
model's universality.
3. Statistical methods need to include the description of VIF and the criteria for collinearity
determination.
4. Subjectivity in efficacy assessment: The efficacy determination is based on symptom
improvement (marked effect/effective/ineffective), lacking quantitative scoring (such as
symptom scoring scale), which may introduce bias. It is recommended to refer to standardized
assessment tools.
5. Variable selection and biological mechanism: In the multivariate analysis, indicators such
as white blood cell count, AST, and HDL-C were included, but the biological mechanism
explanation of these indicators and efficacy in the text was insufficient.
6. Collinearity issue: Although VIF < 10 was mentioned, no specific values were provided. It is
recommended to supplement the VIF results to confirm the independence of variables.
7. Risk of model overfitting: The AUC of the training set and validation set was highly consistent
(both 0.835), and overfitting should be vigilant. It is recommended to increase the number of
Bootstrap resampling times or cross-validation.
8. The variables in Figure 1 caption are inconsistent with the variables in the main text.
9. The discussion part elaborates on the mechanism of action of markers such as PRDX1 and
VIP relatively vaguely. It is recommended to deepen the mechanism association by combining
FD pathophysiology (such as oxidative stress, gastrointestinal motility).
Title: A Preliminary Exploration of a Predictive Model and Nomogram for the Efficacy of
Compound Digestive Enzyme Therapy Based on Serum (PG#, PG#, VIP, and PRDX1) in
Patients with Functional Dyspepsia
Version: 0 Date: 05 Apr 2025
Reviewer's report:
Overall Evaluation
This study aims to construct a predictive model and a nomogram for the efficacy of combined
digestive enzymes in patients with functional dyspepsia (FD) based on serum PG#, PG#, VIP
and PRDX1. The research topic is of clinical significance, and the overall methodology design
is reasonable. The result analysis is relatively sufficient. The model shows high discrimination
in both the training set and the validation set (AUC # 0.83), suggesting its potential application
value. However, the study has the following issues that need to be focused on and further clarified
or improved.
1. The research type was not clearly stated.
2. Sample size and validation set: The validation set only included 75 cases (accounting for 30%
of the total sample), which is relatively small and may affect the external validity assessment.
It is recommended to supplement external validation (such as multi-center data) to enhance the
model's universality.
3. Statistical methods need to include the description of VIF and the criteria for collinearity
determination.
4. Subjectivity in efficacy assessment: The efficacy determination is based on symptom
improvement (marked effect/effective/ineffective), lacking quantitative scoring (such as
symptom scoring scale), which may introduce bias. It is recommended to refer to standardized
assessment tools.
5. Variable selection and biological mechanism: In the multivariate analysis, indicators such
as white blood cell count, AST, and HDL-C were included, but the biological mechanism
explanation of these indicators and efficacy in the text was insufficient.
6. Collinearity issue: Although VIF < 10 was mentioned, no specific values were provided. It is
recommended to supplement the VIF results to confirm the independence of variables.
7. Risk of model overfitting: The AUC of the training set and validation set was highly consistent
(both 0.835), and overfitting should be vigilant. It is recommended to increase the number of
Bootstrap resampling times or cross-validation.
8. The variables in Figure 1 caption are inconsistent with the variables in the main text.
9. The discussion part elaborates on the mechanism of action of markers such as PRDX1 and
VIP relatively vaguely. It is recommended to deepen the mechanism association by combining
FD pathophysiology (such as oxidative stress, gastrointestinal motility).
Please review this paper.
user
Title: A Preliminary Exploration of a Predictive Model and Nomogram for the Efficacy of
Compound Digestive Enzyme Therapy Based on Serum (PG#, PG#, VIP, and PRDX1) in
Patients with Functional Dyspepsia
Version: 0 Date: 05 Apr 2025
Reviewer's report:
Overall Evaluation
This study aims to construct a predictive model and a nomogram for the efficacy of combined
digestive enzymes in patients with functional dyspepsia (FD) based on serum PG#, PG#, VIP
and PRDX1. The research topic is of clinical significance, and the overall methodology design
is reasonable. The result analysis is relatively sufficient. The model shows high discrimination
in both the training set and the validation set (AUC # 0.83), suggesting its potential application
value. However, the study has the following issues that need to be focused on and further clarified
or improved.
1. The research type was not clearly stated.
2. Sample size and validation set: The validation set only included 75 cases (accounting for 30%
of the total sample), which is relatively small and may affect the external validity assessment.
It is recommended to supplement external validation (such as multi-center data) to enhance the
model's universality.
3. Statistical methods need to include the description of VIF and the criteria for collinearity
determination.
4. Subjectivity in efficacy assessment: The efficacy determination is based on symptom
improvement (marked effect/effective/ineffective), lacking quantitative scoring (such as
symptom scoring scale), which may introduce bias. It is recommended to refer to standardized
assessment tools.
5. Variable selection and biological mechanism: In the multivariate analysis, indicators such
as white blood cell count, AST, and HDL-C were included, but the biological mechanism
explanation of these indicators and efficacy in the text was insufficient.
6. Collinearity issue: Although VIF < 10 was mentioned, no specific values were provided. It is
recommended to supplement the VIF results to confirm the independence of variables.
7. Risk of model overfitting: The AUC of the training set and validation set was highly consistent
(both 0.835), and overfitting should be vigilant. It is recommended to increase the number of
Bootstrap resampling times or cross-validation.
8. The variables in Figure 1 caption are inconsistent with the variables in the main text.
9. The discussion part elaborates on the mechanism of action of markers such as PRDX1 and
VIP relatively vaguely. It is recommended to deepen the mechanism association by combining
FD pathophysiology (such as oxidative stress, gastrointestinal motility).
assistant