Title: Evaluating future risk of NAFLD in adolescents: a prediction and decision curve analysis
Version: 2 Date: 04 Apr 2022
Reviewer's report:
The authors revealed that insulin resistance was the best predictor of NAFL in all adolescents,
central adiposity was the best predictor in overweight/obese group, and BMI was the best
predictor of NAFLD fibrosis in all adolescents. Thereover, it was revealed that  “routine clinical
measures” model had the greatest net benefit, but the benefit is small, for increased NAFLD
fibrosis detection in overweight/obese adolescent participants, using decision curve analysis.
These findings are interested, but there are some concerns.
1. Why was the decision curve analysis performed only for the participant with overweight/
obese at the age of 17 year?
2. Specifically, how does the RCM model predict NAFLD fibrosis? What is the impact of each
factor that makes up the model?
Title: Evaluating future risk of NAFLD in adolescents: a prediction and decision curve analysis
Version: 2 Date: 04 Apr 2022
Reviewer's report:
The authors revealed that insulin resistance was the best predictor of NAFL in all adolescents,
central adiposity was the best predictor in overweight/obese group, and BMI was the best
predictor of NAFLD fibrosis in all adolescents. Thereover, it was revealed that  “routine clinical
measures” model had the greatest net benefit, but the benefit is small, for increased NAFLD
fibrosis detection in overweight/obese adolescent participants, using decision curve analysis.
These findings are interested, but there are some concerns.
1. Why was the decision curve analysis performed only for the participant with overweight/
obese at the age of 17 year?
2. Specifically, how does the RCM model predict NAFLD fibrosis? What is the impact of each
factor that makes up the model?
Please review this paper.
user
Title: Evaluating future risk of NAFLD in adolescents: a prediction and decision curve analysis
Version: 2 Date: 04 Apr 2022
Reviewer's report:
The authors revealed that insulin resistance was the best predictor of NAFL in all adolescents,
central adiposity was the best predictor in overweight/obese group, and BMI was the best
predictor of NAFLD fibrosis in all adolescents. Thereover, it was revealed that  “routine clinical
measures” model had the greatest net benefit, but the benefit is small, for increased NAFLD
fibrosis detection in overweight/obese adolescent participants, using decision curve analysis.
These findings are interested, but there are some concerns.
1. Why was the decision curve analysis performed only for the participant with overweight/
obese at the age of 17 year?
2. Specifically, how does the RCM model predict NAFLD fibrosis? What is the impact of each
factor that makes up the model?
assistant