Title: Alpha-Fetoprotein and APRI as Predictive Markers for Patients with Type C Hepatitis B-
Related Acute-on-Chronic Liver Failure: A Retrospective Study
Version: 3 Date: 31 Jul 2023
Reviewer's report:
In this study, a new prognostic scoring model was developed to assess 90-day survival in patients
with type C HBV-ACLF based on serological indices of the liver and noninvasive assessment of
liver fibrosis. The area under the ROC curve was 0.851 [95% CI (0.801-0.901)] and significantly
higher than other scoring models such as MELD, IMELD, MELD-Na, TACIA and COSSH-
ALF-II (all P<0.001). However, external validation is lacking.
1. Figure 1, the second text box in the line under Excluded other causes of type C ACLF suggests
adding a space, otherwise it is easy to cause misinterpretation by the readers
2. add diagnostic criteria for type C ACLF
3. Competing risk model be adopted for patients who then undergo liver transplantation?
4. WBC should be a non-normally distributed, the median should be used to represent it.
5. Regarding the statistical method, how to screen variables, the definition of p-value need to be
described in the statistical method, and finally into the multiple regression using what method
to screen variables into the final model.
6. Suggest to add the comparison of the new predictive model with other models and calculate
the p-value.
Title: Alpha-Fetoprotein and APRI as Predictive Markers for Patients with Type C Hepatitis B-
Related Acute-on-Chronic Liver Failure: A Retrospective Study
Version: 3 Date: 31 Jul 2023
Reviewer's report:
In this study, a new prognostic scoring model was developed to assess 90-day survival in patients
with type C HBV-ACLF based on serological indices of the liver and noninvasive assessment of
liver fibrosis. The area under the ROC curve was 0.851 [95% CI (0.801-0.901)] and significantly
higher than other scoring models such as MELD, IMELD, MELD-Na, TACIA and COSSH-
ALF-II (all P<0.001). However, external validation is lacking.
1. Figure 1, the second text box in the line under Excluded other causes of type C ACLF suggests
adding a space, otherwise it is easy to cause misinterpretation by the readers
2. add diagnostic criteria for type C ACLF
3. Competing risk model be adopted for patients who then undergo liver transplantation?
4. WBC should be a non-normally distributed, the median should be used to represent it.
5. Regarding the statistical method, how to screen variables, the definition of p-value need to be
described in the statistical method, and finally into the multiple regression using what method
to screen variables into the final model.
6. Suggest to add the comparison of the new predictive model with other models and calculate
the p-value.
Please review this paper.
user
Title: Alpha-Fetoprotein and APRI as Predictive Markers for Patients with Type C Hepatitis B-
Related Acute-on-Chronic Liver Failure: A Retrospective Study
Version: 3 Date: 31 Jul 2023
Reviewer's report:
In this study, a new prognostic scoring model was developed to assess 90-day survival in patients
with type C HBV-ACLF based on serological indices of the liver and noninvasive assessment of
liver fibrosis. The area under the ROC curve was 0.851 [95% CI (0.801-0.901)] and significantly
higher than other scoring models such as MELD, IMELD, MELD-Na, TACIA and COSSH-
ALF-II (all P<0.001). However, external validation is lacking.
1. Figure 1, the second text box in the line under Excluded other causes of type C ACLF suggests
adding a space, otherwise it is easy to cause misinterpretation by the readers
2. add diagnostic criteria for type C ACLF
3. Competing risk model be adopted for patients who then undergo liver transplantation?
4. WBC should be a non-normally distributed, the median should be used to represent it.
5. Regarding the statistical method, how to screen variables, the definition of p-value need to be
described in the statistical method, and finally into the multiple regression using what method
to screen variables into the final model.
6. Suggest to add the comparison of the new predictive model with other models and calculate
the p-value.
assistant