Reviewer's report
Title:Non-Invasive Index of Liver Fibrosis Generated by Alcohol, Thioacetamide
and Schistosomal Infection in Mice
Version: 2Date:9 November 2009
Reviewer: James Fung
Reviewer's report:
Given the invasive nature of liver biopsy, non-invasive markers of liver fibrosis is
a much welcomed method for both clinicians and patients. The current study
reports the use of total proteins, bilirubin, GGT and GSH in a logarithmic model
to predict fibrosis in mice.
Minor Essential Revisions
(1) 1st paragraph in background
a. “Advanced liver fibrosis results in cirrhosis” is not a true statement – although
advanced liver firbosis can progress to cirrhosis
b. Sampling is mentioned twice
(2)1st paragraph under methods-animal grouping
a. “The study was carried out on 240 albino mice… “ – this is confusing as the
study appears to have been carried out on 310 mice (70 controls)
b.Define TAA abbreviation (1st use)
(3) 1st paragraph under methods-histological and non-invasive scoring of liver
fibrosis
a. “F0=no fibrosis, S1=portal fibrosis”: should keep to the commonly accepted
F0-F4 system
Major Compulsory Revisions
(4)The abstract needs to be re-written to provide more results, especially with
regards to the accuracy of the non-invasive markers and the cut-off values used
a.Need to be more specific with regards to the ethics/animal care comiitee – eg:
the name of the review board and the name of the institution/committee granting
approval for the study
(5) Under Results-Biochemical panel section-modeling of hepatic fibrosis marker
a. The authors stated that the most useful markers were bilirubin, total protein,
GGT and GSH – how was these 4 parameters derived, and what were the other
biochemical variables that were assessed and the results of their correlation
b. How was the logarithmic formula derived – was it by linear regression? The
statement ”In the above equation both Bilc, GGTc, TPt, and GSHt are replaced
with the corresponding levels measured in health mice mg.dL ….” does not make
sense.
(6) The cut-off values of 0.4, 1.12, and 1.79 were determined for stages 0/1,1/2,
and 2/3 respectively. The cut-off values derived form ROC curves usually is
calculated for a range of fibrosis rather than specific stages eg. F2 or less, F3 or
less, F4. Can the authors clarify this.
a. Also the AUROC should be given for the ROC
b.The sensitivities and specificities should be provided for each of the optimal
cut-off values
(7) Can the authors explains why the correlation was much less in the S.mansoni
group
(8) Did the authors compare their non-invasive model with other readily models
(such as the APRI) for comparison – as this will further support the accuracy of
the model – if not, then this should be discussed
(9)In their study population of mice, none had F4 (cirrhosis) – so the diagnosis of
early cirrhosis is not possible using the current model. However this is a clinically
important group especially for potential screening for portal hypertension and
hepatocellular carcinoma. Validating non-invasive models of fibrosis should be
performed on a group where all stages of fibrosis are present This aspect should
be included in the discussion
(10) Was there any correlation with the histological grades and the index given
that this information was available on histology. The graphs in figure 3 showed
that the grade of inflammation perhaps is also closely related to the score.
Multivariate analysis should be performed to see if this is the case, and whether
fibrosis is the only independent factor correlating with the model.
(11)A box-whisker plot of the stages of fibrosis vs the score would illustrate the
trend and the degree of overlap between each of the fibrosis stage (in addition to
figure 3)
(12)The distribution of fibrosis and inflammation stages for the validation group
should be provided
a.The authors stated a high correlation between stage and grade in the validation
group (figure 5) – but no other data is provided – eg: correlation, significance,
AUROC of the validation set for each of the fibrosis stages
b.The sensitivity, specificity, positive predictive value and negative predictive
value should be provided for the validation set
(13)There are spelling and grammatical errors throughout the manuscript which
will need to be addressed
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Needs some language corrections before being
published
Statistical review: No, the manuscript does not need to be seen by a
statistician.
Declaration of competing interests:
I declare that I have no competing interests
Reviewer's report
Title:Non-Invasive Index of Liver Fibrosis Generated by Alcohol, Thioacetamide
and Schistosomal Infection in Mice
Version: 2Date:9 November 2009
Reviewer: James Fung
Reviewer's report:
Given the invasive nature of liver biopsy, non-invasive markers of liver fibrosis is
a much welcomed method for both clinicians and patients. The current study
reports the use of total proteins, bilirubin, GGT and GSH in a logarithmic model
to predict fibrosis in mice.
Minor Essential Revisions
(1) 1st paragraph in background
a. “Advanced liver fibrosis results in cirrhosis” is not a true statement – although
advanced liver firbosis can progress to cirrhosis
b. Sampling is mentioned twice
(2)1st paragraph under methods-animal grouping
a. “The study was carried out on 240 albino mice… “ – this is confusing as the
study appears to have been carried out on 310 mice (70 controls)
b.Define TAA abbreviation (1st use)
(3) 1st paragraph under methods-histological and non-invasive scoring of liver
fibrosis
a. “F0=no fibrosis, S1=portal fibrosis”: should keep to the commonly accepted
F0-F4 system
Major Compulsory Revisions
(4)The abstract needs to be re-written to provide more results, especially with
regards to the accuracy of the non-invasive markers and the cut-off values used
a.Need to be more specific with regards to the ethics/animal care comiitee – eg:
the name of the review board and the name of the institution/committee granting
approval for the study
(5) Under Results-Biochemical panel section-modeling of hepatic fibrosis marker
a. The authors stated that the most useful markers were bilirubin, total protein,
GGT and GSH – how was these 4 parameters derived, and what were the other
biochemical variables that were assessed and the results of their correlation
b. How was the logarithmic formula derived – was it by linear regression? The
statement ”In the above equation both Bilc, GGTc, TPt, and GSHt are replaced
with the corresponding levels measured in health mice mg.dL ….” does not make
sense.
(6) The cut-off values of 0.4, 1.12, and 1.79 were determined for stages 0/1,1/2,
and 2/3 respectively. The cut-off values derived form ROC curves usually is
calculated for a range of fibrosis rather than specific stages eg. F2 or less, F3 or
less, F4. Can the authors clarify this.
a. Also the AUROC should be given for the ROC
b.The sensitivities and specificities should be provided for each of the optimal
cut-off values
(7) Can the authors explains why the correlation was much less in the S.mansoni
group
(8) Did the authors compare their non-invasive model with other readily models
(such as the APRI) for comparison – as this will further support the accuracy of
the model – if not, then this should be discussed
(9)In their study population of mice, none had F4 (cirrhosis) – so the diagnosis of
early cirrhosis is not possible using the current model. However this is a clinically
important group especially for potential screening for portal hypertension and
hepatocellular carcinoma. Validating non-invasive models of fibrosis should be
performed on a group where all stages of fibrosis are present This aspect should
be included in the discussion
(10) Was there any correlation with the histological grades and the index given
that this information was available on histology. The graphs in figure 3 showed
that the grade of inflammation perhaps is also closely related to the score.
Multivariate analysis should be performed to see if this is the case, and whether
fibrosis is the only independent factor correlating with the model.
(11)A box-whisker plot of the stages of fibrosis vs the score would illustrate the
trend and the degree of overlap between each of the fibrosis stage (in addition to
figure 3)
(12)The distribution of fibrosis and inflammation stages for the validation group
should be provided
a.The authors stated a high correlation between stage and grade in the validation
group (figure 5) – but no other data is provided – eg: correlation, significance,
AUROC of the validation set for each of the fibrosis stages
b.The sensitivity, specificity, positive predictive value and negative predictive
value should be provided for the validation set
(13)There are spelling and grammatical errors throughout the manuscript which
will need to be addressed
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Needs some language corrections before being
published
Statistical review: No, the manuscript does not need to be seen by a
statistician.
Declaration of competing interests:
I declare that I have no competing interests
Please review this paper.
user
Reviewer's report
Title:Non-Invasive Index of Liver Fibrosis Generated by Alcohol, Thioacetamide
and Schistosomal Infection in Mice
Version: 2Date:9 November 2009
Reviewer: James Fung
Reviewer's report:
Given the invasive nature of liver biopsy, non-invasive markers of liver fibrosis is
a much welcomed method for both clinicians and patients. The current study
reports the use of total proteins, bilirubin, GGT and GSH in a logarithmic model
to predict fibrosis in mice.
Minor Essential Revisions
(1) 1st paragraph in background
a. “Advanced liver fibrosis results in cirrhosis” is not a true statement – although
advanced liver firbosis can progress to cirrhosis
b. Sampling is mentioned twice
(2)1st paragraph under methods-animal grouping
a. “The study was carried out on 240 albino mice… “ – this is confusing as the
study appears to have been carried out on 310 mice (70 controls)
b.Define TAA abbreviation (1st use)
(3) 1st paragraph under methods-histological and non-invasive scoring of liver
fibrosis
a. “F0=no fibrosis, S1=portal fibrosis”: should keep to the commonly accepted
F0-F4 system
Major Compulsory Revisions
(4)The abstract needs to be re-written to provide more results, especially with
regards to the accuracy of the non-invasive markers and the cut-off values used
a.Need to be more specific with regards to the ethics/animal care comiitee – eg:
the name of the review board and the name of the institution/committee granting
approval for the study
(5) Under Results-Biochemical panel section-modeling of hepatic fibrosis marker
a. The authors stated that the most useful markers were bilirubin, total protein,
GGT and GSH – how was these 4 parameters derived, and what were the other
biochemical variables that were assessed and the results of their correlation
b. How was the logarithmic formula derived – was it by linear regression? The
statement ”In the above equation both Bilc, GGTc, TPt, and GSHt are replaced
with the corresponding levels measured in health mice mg.dL ….” does not make
sense.
(6) The cut-off values of 0.4, 1.12, and 1.79 were determined for stages 0/1,1/2,
and 2/3 respectively. The cut-off values derived form ROC curves usually is
calculated for a range of fibrosis rather than specific stages eg. F2 or less, F3 or
less, F4. Can the authors clarify this.
a. Also the AUROC should be given for the ROC
b.The sensitivities and specificities should be provided for each of the optimal
cut-off values
(7) Can the authors explains why the correlation was much less in the S.mansoni
group
(8) Did the authors compare their non-invasive model with other readily models
(such as the APRI) for comparison – as this will further support the accuracy of
the model – if not, then this should be discussed
(9)In their study population of mice, none had F4 (cirrhosis) – so the diagnosis of
early cirrhosis is not possible using the current model. However this is a clinically
important group especially for potential screening for portal hypertension and
hepatocellular carcinoma. Validating non-invasive models of fibrosis should be
performed on a group where all stages of fibrosis are present This aspect should
be included in the discussion
(10) Was there any correlation with the histological grades and the index given
that this information was available on histology. The graphs in figure 3 showed
that the grade of inflammation perhaps is also closely related to the score.
Multivariate analysis should be performed to see if this is the case, and whether
fibrosis is the only independent factor correlating with the model.
(11)A box-whisker plot of the stages of fibrosis vs the score would illustrate the
trend and the degree of overlap between each of the fibrosis stage (in addition to
figure 3)
(12)The distribution of fibrosis and inflammation stages for the validation group
should be provided
a.The authors stated a high correlation between stage and grade in the validation
group (figure 5) – but no other data is provided – eg: correlation, significance,
AUROC of the validation set for each of the fibrosis stages
b.The sensitivity, specificity, positive predictive value and negative predictive
value should be provided for the validation set
(13)There are spelling and grammatical errors throughout the manuscript which
will need to be addressed
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Needs some language corrections before being
published
Statistical review: No, the manuscript does not need to be seen by a
statistician.
Declaration of competing interests:
I declare that I have no competing interests
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