Reviewer ’s report  
 
Title: Anthropometric and blood parameters for the prediction of NAFLD among overweight 
and obese adults  
 
Version: 1 Date: 04 May 2018  
 
Reviewer: Tung -Hung Su  
 
Reviewer's report:  
 
General comment  
Early detection of N AFLD or NASH is important to prevent its complication. At present, there is 
no good screening biomarkers for this disease. In this study, the authors aimed to assess the 
combination of anthropometric parameters and circulating biomarkers to be a screening tool for 
detection of NAFLD and steatohepatitis. They evaluated anthropometric indices and routine 
biomarkers of metabolism and liver function to predict MRI -derived NAFLD.  
They included 143 overweight patients in this study and found that age, sex, waist  
circumference, ALT, HbA1c, and HOMA -IR predicted NAFLD. The prediction is better than 
previously published indices. Overall, this is an interesting study with clinical relevant results. 
The authors proposed an easy to use markers to predict the liver fat percentage derived from 
MRI -based examination. However, a few issues need to be further clarified.  
 
Major comment  
1. The diagnosis of NAFLD in this study is based on the MRI findings of the liver fat 
percentage. The author used a cut -off value of 5.56% to  indicate the diagnosis of NAFLD. 
However, that cut -off value was derived from a study in 2005 to include general population 
using a different MRS technique. The authors should discuss this cut -off selection in more 
detail. Is there any direct comparison b etween the current multi -echo GRE technique with 
the previous MRS technique? Is there any correlation between the current methodology to 
quantify liver fat percentage and pathological findings?  
 
2. Using the MRI multi -echo GRE technique in this study, is there any patient actually had 
NASH with liver fibrosis, rather than NAFLD?  
 
3. Because waist, ALT, GGT, HbA1c, insulin, and creatinine are significantly associated with 
liver fat content, how did the authors determine their final model and take in to account of 
age, sex, waist, ALT, HbA1c and HOMA -IR? The process to select the anthropometric 
parameters for multivariable linear regression is not clear. Please show the results of 
univariate analyses as well. The authors should explain more clearly the process for model 
establishment.  
 
4. The author compared their MRI -based estimation of liver fat percentage with the liver fat 
score from Kotronen. The R -square was 41.4% with moderate correlation. The a uthor 
should discuss this point in more detail regarding to the advantage and limitation of 
individual estimation of two methods.  
 
Minor comment  
1. The authors should list a table to compare the individual fatty liver scores derived from this 
cohort  
 
2. Please indicate the P value in each of the Spearman's correlation. Are they all statistically 
significant?  
Are the methods appropriate and well described?  
If not, please specify what is required in your comments to the authors.  
 
No 
 
Does the work include the necessary controls?  
If not, please specify which controls are  required in your comments to the authors.  
 
No 
 
Are the conclusions drawn adequately supported by the data shown?  
If not, please explain in your comments to the authors.  
 
No 
 
Are you able to assess any statistics in the manuscript or would you recommend an  
additional statistical review?  
If an additional statistical review is recommended, please specify what aspects require further  
assessment in your comments to the editors.  
 
I recommend additional statistical review  
 
Quality of written English  
Please indicate the  quality of language in the manuscript:  
 
Acceptable  
 
Declaration of competing interests  
Please complete a declaration of competing interests, considering the following questions:  
 
1. Have you in the past five years received reimbursements, fees, funding, or salary from an  
organisation that may in any way gain or lose financially from the publication of this  
manuscript, either now or in the future?  
 
2. Do you hold any stocks or shares  in an organisation that may in any way gain or lose  
financially from the publication of this manuscript, either now or in the future?  
 
3. Do you hold or are you currently applying for any patents relating to the content of the  
manuscript?  
 
4. Have you recei ved reimbursements, fees, funding, or salary from an organization that 
holds  or has applied for patents relating to the content of the manuscript?  
 
5. Do you have any other financial competing interests?  
 
6. Do you have any non -financial competing interests in relation to this paper?  
 
If you can answer no to all of the above, write 'I declare that I have no competing interests' 
below.  If your reply is yes to any, please give details below.  
 
I declare that I have no competing interests.  
 
I agree to the open peer review policy of the journal. I understand that my name will be included  
on my report to the authors and, if the manuscript is accepted for publication, my named report  
including any attachments I upload will be posted on the website along with the authors ' 
responses.  I agree for my report to be made available under an Open Access Creative Commons 
CC-BY license ( http://creativecommons.org/licenses/by/4.0/ ). I understand that any comments 
which I do  not wish to be included in my named report can be included as confidential comments 
to the  editors, which will not be published.  
 
I agree to the open peer review policy of the journal  
Reviewer ’s report  
 
Title: Anthropometric and blood parameters for the prediction of NAFLD among overweight 
and obese adults  
 
Version: 1 Date: 04 May 2018  
 
Reviewer: Tung -Hung Su  
 
Reviewer's report:  
 
General comment  
Early detection of N AFLD or NASH is important to prevent its complication. At present, there is 
no good screening biomarkers for this disease. In this study, the authors aimed to assess the 
combination of anthropometric parameters and circulating biomarkers to be a screening tool for 
detection of NAFLD and steatohepatitis. They evaluated anthropometric indices and routine 
biomarkers of metabolism and liver function to predict MRI -derived NAFLD.  
They included 143 overweight patients in this study and found that age, sex, waist  
circumference, ALT, HbA1c, and HOMA -IR predicted NAFLD. The prediction is better than 
previously published indices. Overall, this is an interesting study with clinical relevant results. 
The authors proposed an easy to use markers to predict the liver fat percentage derived from 
MRI -based examination. However, a few issues need to be further clarified.  
 
Major comment  
1. The diagnosis of NAFLD in this study is based on the MRI findings of the liver fat 
percentage. The author used a cut -off value of 5.56% to  indicate the diagnosis of NAFLD. 
However, that cut -off value was derived from a study in 2005 to include general population 
using a different MRS technique. The authors should discuss this cut -off selection in more 
detail. Is there any direct comparison b etween the current multi -echo GRE technique with 
the previous MRS technique? Is there any correlation between the current methodology to 
quantify liver fat percentage and pathological findings?  
 
2. Using the MRI multi -echo GRE technique in this study, is there any patient actually had 
NASH with liver fibrosis, rather than NAFLD?  
 
3. Because waist, ALT, GGT, HbA1c, insulin, and creatinine are significantly associated with 
liver fat content, how did the authors determine their final model and take in to account of 
age, sex, waist, ALT, HbA1c and HOMA -IR? The process to select the anthropometric 
parameters for multivariable linear regression is not clear. Please show the results of 
univariate analyses as well. The authors should explain more clearly the process for model 
establishment.  
 
4. The author compared their MRI -based estimation of liver fat percentage with the liver fat 
score from Kotronen. The R -square was 41.4% with moderate correlation. The a uthor 
should discuss this point in more detail regarding to the advantage and limitation of 
individual estimation of two methods.  
 
Minor comment  
1. The authors should list a table to compare the individual fatty liver scores derived from this 
cohort  
 
2. Please indicate the P value in each of the Spearman's correlation. Are they all statistically 
significant?  
Are the methods appropriate and well described?  
If not, please specify what is required in your comments to the authors.  
 
No 
 
Does the work include the necessary controls?  
If not, please specify which controls are  required in your comments to the authors.  
 
No 
 
Are the conclusions drawn adequately supported by the data shown?  
If not, please explain in your comments to the authors.  
 
No 
 
Are you able to assess any statistics in the manuscript or would you recommend an  
additional statistical review?  
If an additional statistical review is recommended, please specify what aspects require further  
assessment in your comments to the editors.  
 
I recommend additional statistical review  
 
Quality of written English  
Please indicate the  quality of language in the manuscript:  
 
Acceptable  
 
Declaration of competing interests  
Please complete a declaration of competing interests, considering the following questions:  
 
1. Have you in the past five years received reimbursements, fees, funding, or salary from an  
organisation that may in any way gain or lose financially from the publication of this  
manuscript, either now or in the future?  
 
2. Do you hold any stocks or shares  in an organisation that may in any way gain or lose  
financially from the publication of this manuscript, either now or in the future?  
 
3. Do you hold or are you currently applying for any patents relating to the content of the  
manuscript?  
 
4. Have you recei ved reimbursements, fees, funding, or salary from an organization that 
holds  or has applied for patents relating to the content of the manuscript?  
 
5. Do you have any other financial competing interests?  
 
6. Do you have any non -financial competing interests in relation to this paper?  
 
If you can answer no to all of the above, write 'I declare that I have no competing interests' 
below.  If your reply is yes to any, please give details below.  
 
I declare that I have no competing interests.  
 
I agree to the open peer review policy of the journal. I understand that my name will be included  
on my report to the authors and, if the manuscript is accepted for publication, my named report  
including any attachments I upload will be posted on the website along with the authors ' 
responses.  I agree for my report to be made available under an Open Access Creative Commons 
CC-BY license ( http://creativecommons.org/licenses/by/4.0/ ). I understand that any comments 
which I do  not wish to be included in my named report can be included as confidential comments 
to the  editors, which will not be published.  
 
I agree to the open peer review policy of the journal  
Please review this paper.
user
Reviewer ’s report  
 
Title: Anthropometric and blood parameters for the prediction of NAFLD among overweight 
and obese adults  
 
Version: 1 Date: 04 May 2018  
 
Reviewer: Tung -Hung Su  
 
Reviewer's report:  
 
General comment  
Early detection of N AFLD or NASH is important to prevent its complication. At present, there is 
no good screening biomarkers for this disease. In this study, the authors aimed to assess the 
combination of anthropometric parameters and circulating biomarkers to be a screening tool for 
detection of NAFLD and steatohepatitis. They evaluated anthropometric indices and routine 
biomarkers of metabolism and liver function to predict MRI -derived NAFLD.  
They included 143 overweight patients in this study and found that age, sex, waist  
circumference, ALT, HbA1c, and HOMA -IR predicted NAFLD. The prediction is better than 
previously published indices. Overall, this is an interesting study with clinical relevant results. 
The authors proposed an easy to use markers to predict the liver fat percentage derived from 
MRI -based examination. However, a few issues need to be further clarified.  
 
Major comment  
1. The diagnosis of NAFLD in this study is based on the MRI findings of the liver fat 
percentage. The author used a cut -off value of 5.56% to  indicate the diagnosis of NAFLD. 
However, that cut -off value was derived from a study in 2005 to include general population 
using a different MRS technique. The authors should discuss this cut -off selection in more 
detail. Is there any direct comparison b etween the current multi -echo GRE technique with 
the previous MRS technique? Is there any correlation between the current methodology to 
quantify liver fat percentage and pathological findings?  
 
2. Using the MRI multi -echo GRE technique in this study, is there any patient actually had 
NASH with liver fibrosis, rather than NAFLD?  
 
3. Because waist, ALT, GGT, HbA1c, insulin, and creatinine are significantly associated with 
liver fat content, how did the authors determine their final model and take in to account of 
age, sex, waist, ALT, HbA1c and HOMA -IR? The process to select the anthropometric 
parameters for multivariable linear regression is not clear. Please show the results of 
univariate analyses as well. The authors should explain more clearly the process for model 
establishment.  
 
4. The author compared their MRI -based estimation of liver fat percentage with the liver fat 
score from Kotronen. The R -square was 41.4% with moderate correlation. The a uthor 
should discuss this point in more detail regarding to the advantage and limitation of 
individual estimation of two methods.  
 
Minor comment  
1. The authors should list a table to compare the individual fatty liver scores derived from this 
cohort  
 
2. Please indicate the P value in each of the Spearman's correlation. Are they all statistically 
significant?  
Are the methods appropriate and well described?  
If not, please specify what is required in your comments to the authors.  
 
No 
 
Does the work include the necessary controls?  
If not, please specify which controls are  required in your comments to the authors.  
 
No 
 
Are the conclusions drawn adequately supported by the data shown?  
If not, please explain in your comments to the authors.  
 
No 
 
Are you able to assess any statistics in the manuscript or would you recommend an  
additional statistical review?  
If an additional statistical review is recommended, please specify what aspects require further  
assessment in your comments to the editors.  
 
I recommend additional statistical review  
 
Quality of written English  
Please indicate the  quality of language in the manuscript:  
 
Acceptable  
 
Declaration of competing interests  
Please complete a declaration of competing interests, considering the following questions:  
 
1. Have you in the past five years received reimbursements, fees, funding, or salary from an  
organisation that may in any way gain or lose financially from the publication of this  
manuscript, either now or in the future?  
 
2. Do you hold any stocks or shares  in an organisation that may in any way gain or lose  
financially from the publication of this manuscript, either now or in the future?  
 
3. Do you hold or are you currently applying for any patents relating to the content of the  
manuscript?  
 
4. Have you recei ved reimbursements, fees, funding, or salary from an organization that 
holds  or has applied for patents relating to the content of the manuscript?  
 
5. Do you have any other financial competing interests?  
 
6. Do you have any non -financial competing interests in relation to this paper?  
 
If you can answer no to all of the above, write 'I declare that I have no competing interests' 
below.  If your reply is yes to any, please give details below.  
 
I declare that I have no competing interests.  
 
I agree to the open peer review policy of the journal. I understand that my name will be included  
on my report to the authors and, if the manuscript is accepted for publication, my named report  
including any attachments I upload will be posted on the website along with the authors ' 
responses.  I agree for my report to be made available under an Open Access Creative Commons 
CC-BY license ( http://creativecommons.org/licenses/by/4.0/ ). I understand that any comments 
which I do  not wish to be included in my named report can be included as confidential comments 
to the  editors, which will not be published.  
 
I agree to the open peer review policy of the journal  
assistant