Migraine Disability Improvement during Treatment with Galcanezumab in Patients with Chronic and High Frequency Episodic Migraine
Round 1
Reviewer 1 Report (Previous Reviewer 1)
Thankyou for addressing the comments. The manuscript has improved dramatically.
Author Response
Thank you. I am pleased to know you appreciated the new version of my work.
Kind regards
Reviewer 2 Report (Previous Reviewer 2)
-
Author Response
I appreciate your evaluations.
Kind regards
Reviewer 3 Report (Previous Reviewer 3)
No futher comments.
Author Response
I here upload the new version with 3800 words and >50 references.
Author Response File: 
Author Response.docx
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
Intro and discussion is much improved.
still not clear how allodynia was assessed
figure has not been changed. Labels A,B,C and D should be replaced with the actual measure.
some places where references are missing.
Author Response
Dear reviewer,
Thanks for your comments.
Regarding the 2 still open issues:
- I had modified figure 1 but uploaded it separately, I have now included it in the main text.
- regarding allodynina we just asked patients whether they had symptoms compatible with it
I'll double check for missing references.
Reviewer 2 Report
Neurolint-1982596v2
Review: Migraine Disability Improvement During Treatment with Gal-2 canezumab in Patients with Chronic and High Episodic Mi-3 graine
Proposed: major revision
Dear editor,
The authors did a very nice job. They revised almost everything in a correct way. However, the statistical analyses is still not yet of good quality. To test and present the data optimal, linear mixed modelling (LMM) is needed. As stated in my former comment: Thereby, it would have been better when LMM were performed in which the MHDs/MMDs will be the dependent values and time, PROMs and time*PROMs (interactions) will be the independent values in this model. Than more insight will be gained from the analyses in this study. Additionally, there will be more insight in the difference between HFEM and CM in this study by adding this as an independent value to the LMM analyses.
The authors wrote in their letter that they had performed linear regression, however, LMM is a more sophisticated regression analyses. So I think we are not talking about the same analyses.
So please perform LMM analyses in this study, replacing both ANOVA and correlations.
Author Response
Dear reviewer,
I have performed a LLM.
As you asked I put MMDs and MHDs as dependent variables, time and PROMS as independent variables and diagnoses as cofactors.
Both intercept and time were significant with p < 0.0001. All estimates of covariance were significant.
I have put both ANOVA/correlations and the LLM models in the results section for the time being as I am not sure if I have reported it correctly.
Reviewer 3 Report
L41: forgot to delete "consecutive"
Author Response
Deleted now!
Sorry about that!
Thanks for your comments!
Round 2
Reviewer 2 Report
Neurolint-1982596v3
Review: Migraine Disability Improvement During Treatment with Gal-2 canezumab in Patients with Chronic and High Episodic Mi-3 graine
Proposed: major revision
Dear editor,
At first your reaction to the reviewers is not of good quality.
To the authors of this paper: Please make in future a document with the question of the reviewer, your answer, and add information what you have changed in the manuscript with the literally text and page+lines.
You state that you have performed linear mixed modelling (LMM), however, information about this is missing in the statistical analyses. What kind of LMM did you use? Based on what did you choose this model?
See also: https://stats.oarc.ucla.edu/other/mult-pkg/introduction-to-linear-mixed-models/#:~:text=Linear%20mixed%20models%20are%20an,or%20patients%20from%20within%20doctors.
https://books.google.nl/books?hl=nl&lr=&id=VT147cq9-7gC&oi=fnd&pg=PR7&dq=linear+mixed+models+basics&ots=RXbquj2S2j&sig=E7r2yc1PcnURaNvtJygKiqcTsMs#v=onepage&q=linear%20mixed%20models%20basics&f=false
https://books.google.nl/books?hl=nl&lr=&id=GcGrySpkXRMC&oi=fnd&pg=PP1&dq=linear+mixed+models+basics&ots=jW-QvvdfZX&sig=M-LhT2qhaAGhL_qCFf5qliSoXAs#v=onepage&q=linear%20mixed%20models%20basics&f=false
etc.
Thereby, the information in the Results section is insufficient.
From this information it is not clear which formula (and it’s Bettaas) is the result from your analyses. For example MHDs=βMIDAS*(βMIDAS*Time)*βSex*βage*βetc.
You have n=54 participants, so 5 items can be added in your analyses. Thereby, it has to be clear from the introduction why you choose these items in your model.
Thereby, it has to be stated what your fixed effects and what your random effects in the model are.
By using these analyses, your ANOVAs and correlations are not of any value any more. See also: https://www.mdpi.com/2306-5729/5/1/6
Based on the rewritten Results section (appropriate describing the results from LMM and deleted ANOVA and correlation findings), the Discussion has also to be revised.
