Title: Circulating microRNAs as predictors of response to Sofosbuvir + Daclatasvir + Ribavirin
in in HCV genotype-4 Egyptian patients.
Version: 1 Date: 05 Mar 2022
Reviewer's report:
The authors assessed the clinical utility of microRNA in HCV-4 patients receiving SOF plus
DCV and RBV in Egyptian. The found that various microRNA levels were predictive of
treatment response to HCV
1. The title did not correspond to the main findings in the current study. The authors should
specify HCV genotype 4, rather than HCV patients. Moreover, not only microRNA 196 but other
microRNAs also were also predictive of treatment response. The use of direct-acting antivirals
was also confusing and should specify sofosbuvir plus daclatasvir and ribavirin.
2. Since the number of patients who failed to achieve SVR was small, the AUROC and logistic
regression model may not be precisely predicted.
3. The four microRNA levels showed statistical significance in univariate analysis. Why did
only two factors enter multivariate analysis?
4. The condition of logistic regression model was not clearly stated. How was the potential factor
in univariate analysis entering multivariate analysis?
5. How about the other known predictors such as fibrosis stage (such as FborScan, FIB-4 etc…)
and various demographic data, in the predictive model? It should be shown to prove if microRNA
would add additional benefit in predicting treatment responses
6. The flow of results were not shown and presented in order. Please reorganize the presentation.
7. Numerous writing errors were present in the manuscript.
Title: Circulating microRNAs as predictors of response to Sofosbuvir + Daclatasvir + Ribavirin
in in HCV genotype-4 Egyptian patients.
Version: 1 Date: 05 Mar 2022
Reviewer's report:
The authors assessed the clinical utility of microRNA in HCV-4 patients receiving SOF plus
DCV and RBV in Egyptian. The found that various microRNA levels were predictive of
treatment response to HCV
1. The title did not correspond to the main findings in the current study. The authors should
specify HCV genotype 4, rather than HCV patients. Moreover, not only microRNA 196 but other
microRNAs also were also predictive of treatment response. The use of direct-acting antivirals
was also confusing and should specify sofosbuvir plus daclatasvir and ribavirin.
2. Since the number of patients who failed to achieve SVR was small, the AUROC and logistic
regression model may not be precisely predicted.
3. The four microRNA levels showed statistical significance in univariate analysis. Why did
only two factors enter multivariate analysis?
4. The condition of logistic regression model was not clearly stated. How was the potential factor
in univariate analysis entering multivariate analysis?
5. How about the other known predictors such as fibrosis stage (such as FborScan, FIB-4 etc…)
and various demographic data, in the predictive model? It should be shown to prove if microRNA
would add additional benefit in predicting treatment responses
6. The flow of results were not shown and presented in order. Please reorganize the presentation.
7. Numerous writing errors were present in the manuscript.
Please review this paper.
user
Title: Circulating microRNAs as predictors of response to Sofosbuvir + Daclatasvir + Ribavirin
in in HCV genotype-4 Egyptian patients.
Version: 1 Date: 05 Mar 2022
Reviewer's report:
The authors assessed the clinical utility of microRNA in HCV-4 patients receiving SOF plus
DCV and RBV in Egyptian. The found that various microRNA levels were predictive of
treatment response to HCV
1. The title did not correspond to the main findings in the current study. The authors should
specify HCV genotype 4, rather than HCV patients. Moreover, not only microRNA 196 but other
microRNAs also were also predictive of treatment response. The use of direct-acting antivirals
was also confusing and should specify sofosbuvir plus daclatasvir and ribavirin.
2. Since the number of patients who failed to achieve SVR was small, the AUROC and logistic
regression model may not be precisely predicted.
3. The four microRNA levels showed statistical significance in univariate analysis. Why did
only two factors enter multivariate analysis?
4. The condition of logistic regression model was not clearly stated. How was the potential factor
in univariate analysis entering multivariate analysis?
5. How about the other known predictors such as fibrosis stage (such as FborScan, FIB-4 etc…)
and various demographic data, in the predictive model? It should be shown to prove if microRNA
would add additional benefit in predicting treatment responses
6. The flow of results were not shown and presented in order. Please reorganize the presentation.
7. Numerous writing errors were present in the manuscript.
assistant