Title: A risk prediction model for nausea and vomiting after TACE : a cross-sectional study
Version: 2 Date: 27 Dec 2024
Reviewer:  Tsvetan R. Yordanov
Reviewer's report:
Please find line-specific comments below :
L10: Overstated 52.5%, where in fact this was the upper bound of a range.
L17: I believe you meant to say "predictors"  instead of "prediction models". Also the sentence
is hard to read, suggest rephrasing to make clearer.
L18: You reported different AUCs in the main results (suspect you flipped train and validation
results).
L18: You refer to datasets as "train and test", whilst everywhere else they are "train and validate".
Please be consistent.
L26: Rephrase, these numbers are for 2020 only, not cumulative. Unclear right now which one
of the two interpretations you meant.
L53-54: Unclear what you meant in this sentence. Please rephrase.
L65-66: Use different word than "cases", many readers will first think you mean patients with
a positive outcome by "cases" (i.e., cases vs controls), whilst I believe you meant "patients
included in the study cohort".
L74: Not a proper sentence, please rephrase.
L77: Not clear, please provide more information if possible on how the "score" influenced
follow-up. If not available, please write as limitation.
L78: What is NCI-CTCAE 5.0? Please provide a definition for this acronym, as well as others
that were missed (I see them defined only under table caption, but should also be defined in
main body).
L93: Not clear what you meant to say here. Please rephrase this sentence. Currently I assume you
meant to say that you checked if the training and validation groups were properly randomized.
L94: Please clarify if predictor screening was done on the training set or on the whole dataset
(training + validation).
L97: Missing word "test" after "Hosmer-Lemeshow". Would useful to provide a reference for
the readers unaware of this test. The H-L test is applied to the predictions of the model, not
directly to it's fit -please correct this. Please be explicit and specify what the H-L test, the AUC,
and the DCA are measuring (is it accuracy, is it calibration etc.).
L122: Remove word "including", as you do list all five variables in the text, i.e., these were
all the variables. If these were not all the variables, then either list all of them or provide some
reason for why only these 5 are listed and not the others.
L140: Please correct use of "training groups" and "validating groups" from plural to singular.
Unless you did actually have multiple training and validation groups, the way I understood from
the methods was there was one of each only.
L241: Not clear what was meant by "enhances the provision of precise for high-risk patients"  -
believe a word is missing there. Please correct/rephrase.
Other lines with text unclear/missing a word - L247, L251.
L253: What is DEB-TACE. Please provide a definition.
Please find general study comments below:
A section that I missed from the methods was about handling of missing data - was there any
such in your data, how was it handled? Please provide this information.
On a more fundamental level, the AUC, DCA and H-L test are all sensitive to class-imbalance.
In your dataset you had a positive-class rate of 33%, whilst we know this can be very different
in other cohorts (up to 52%).
In order to have a more robust understanding of the models performance I would suggest to
incorporate a metric like the brier score, which is less sensitive to changes in prevalence.
Even-better you could consider reporting the positive-only and negative-only brier score as well,
the former being the brier score from only the records that experienced the outcome, and the
latter being the brier score from only the records that did not experience the outcome.
Conclusion does not follow naturally from research aims (investigating factors associated with
nausea and vomiting after TACE and developing a prediction model). Please include in the
conclusion what were the factors and how well the model performed.
Title: A risk prediction model for nausea and vomiting after TACE : a cross-sectional study
Version: 2 Date: 27 Dec 2024
Reviewer:  Tsvetan R. Yordanov
Reviewer's report:
Please find line-specific comments below :
L10: Overstated 52.5%, where in fact this was the upper bound of a range.
L17: I believe you meant to say "predictors"  instead of "prediction models". Also the sentence
is hard to read, suggest rephrasing to make clearer.
L18: You reported different AUCs in the main results (suspect you flipped train and validation
results).
L18: You refer to datasets as "train and test", whilst everywhere else they are "train and validate".
Please be consistent.
L26: Rephrase, these numbers are for 2020 only, not cumulative. Unclear right now which one
of the two interpretations you meant.
L53-54: Unclear what you meant in this sentence. Please rephrase.
L65-66: Use different word than "cases", many readers will first think you mean patients with
a positive outcome by "cases" (i.e., cases vs controls), whilst I believe you meant "patients
included in the study cohort".
L74: Not a proper sentence, please rephrase.
L77: Not clear, please provide more information if possible on how the "score" influenced
follow-up. If not available, please write as limitation.
L78: What is NCI-CTCAE 5.0? Please provide a definition for this acronym, as well as others
that were missed (I see them defined only under table caption, but should also be defined in
main body).
L93: Not clear what you meant to say here. Please rephrase this sentence. Currently I assume you
meant to say that you checked if the training and validation groups were properly randomized.
L94: Please clarify if predictor screening was done on the training set or on the whole dataset
(training + validation).
L97: Missing word "test" after "Hosmer-Lemeshow". Would useful to provide a reference for
the readers unaware of this test. The H-L test is applied to the predictions of the model, not
directly to it's fit -please correct this. Please be explicit and specify what the H-L test, the AUC,
and the DCA are measuring (is it accuracy, is it calibration etc.).
L122: Remove word "including", as you do list all five variables in the text, i.e., these were
all the variables. If these were not all the variables, then either list all of them or provide some
reason for why only these 5 are listed and not the others.
L140: Please correct use of "training groups" and "validating groups" from plural to singular.
Unless you did actually have multiple training and validation groups, the way I understood from
the methods was there was one of each only.
L241: Not clear what was meant by "enhances the provision of precise for high-risk patients"  -
believe a word is missing there. Please correct/rephrase.
Other lines with text unclear/missing a word - L247, L251.
L253: What is DEB-TACE. Please provide a definition.
Please find general study comments below:
A section that I missed from the methods was about handling of missing data - was there any
such in your data, how was it handled? Please provide this information.
On a more fundamental level, the AUC, DCA and H-L test are all sensitive to class-imbalance.
In your dataset you had a positive-class rate of 33%, whilst we know this can be very different
in other cohorts (up to 52%).
In order to have a more robust understanding of the models performance I would suggest to
incorporate a metric like the brier score, which is less sensitive to changes in prevalence.
Even-better you could consider reporting the positive-only and negative-only brier score as well,
the former being the brier score from only the records that experienced the outcome, and the
latter being the brier score from only the records that did not experience the outcome.
Conclusion does not follow naturally from research aims (investigating factors associated with
nausea and vomiting after TACE and developing a prediction model). Please include in the
conclusion what were the factors and how well the model performed.
Please review this paper.
user
Title: A risk prediction model for nausea and vomiting after TACE : a cross-sectional study
Version: 2 Date: 27 Dec 2024
Reviewer:  Tsvetan R. Yordanov
Reviewer's report:
Please find line-specific comments below :
L10: Overstated 52.5%, where in fact this was the upper bound of a range.
L17: I believe you meant to say "predictors"  instead of "prediction models". Also the sentence
is hard to read, suggest rephrasing to make clearer.
L18: You reported different AUCs in the main results (suspect you flipped train and validation
results).
L18: You refer to datasets as "train and test", whilst everywhere else they are "train and validate".
Please be consistent.
L26: Rephrase, these numbers are for 2020 only, not cumulative. Unclear right now which one
of the two interpretations you meant.
L53-54: Unclear what you meant in this sentence. Please rephrase.
L65-66: Use different word than "cases", many readers will first think you mean patients with
a positive outcome by "cases" (i.e., cases vs controls), whilst I believe you meant "patients
included in the study cohort".
L74: Not a proper sentence, please rephrase.
L77: Not clear, please provide more information if possible on how the "score" influenced
follow-up. If not available, please write as limitation.
L78: What is NCI-CTCAE 5.0? Please provide a definition for this acronym, as well as others
that were missed (I see them defined only under table caption, but should also be defined in
main body).
L93: Not clear what you meant to say here. Please rephrase this sentence. Currently I assume you
meant to say that you checked if the training and validation groups were properly randomized.
L94: Please clarify if predictor screening was done on the training set or on the whole dataset
(training + validation).
L97: Missing word "test" after "Hosmer-Lemeshow". Would useful to provide a reference for
the readers unaware of this test. The H-L test is applied to the predictions of the model, not
directly to it's fit -please correct this. Please be explicit and specify what the H-L test, the AUC,
and the DCA are measuring (is it accuracy, is it calibration etc.).
L122: Remove word "including", as you do list all five variables in the text, i.e., these were
all the variables. If these were not all the variables, then either list all of them or provide some
reason for why only these 5 are listed and not the others.
L140: Please correct use of "training groups" and "validating groups" from plural to singular.
Unless you did actually have multiple training and validation groups, the way I understood from
the methods was there was one of each only.
L241: Not clear what was meant by "enhances the provision of precise for high-risk patients"  -
believe a word is missing there. Please correct/rephrase.
Other lines with text unclear/missing a word - L247, L251.
L253: What is DEB-TACE. Please provide a definition.
Please find general study comments below:
A section that I missed from the methods was about handling of missing data - was there any
such in your data, how was it handled? Please provide this information.
On a more fundamental level, the AUC, DCA and H-L test are all sensitive to class-imbalance.
In your dataset you had a positive-class rate of 33%, whilst we know this can be very different
in other cohorts (up to 52%).
In order to have a more robust understanding of the models performance I would suggest to
incorporate a metric like the brier score, which is less sensitive to changes in prevalence.
Even-better you could consider reporting the positive-only and negative-only brier score as well,
the former being the brier score from only the records that experienced the outcome, and the
latter being the brier score from only the records that did not experience the outcome.
Conclusion does not follow naturally from research aims (investigating factors associated with
nausea and vomiting after TACE and developing a prediction model). Please include in the
conclusion what were the factors and how well the model performed.
assistant