Title: Diagnostic performance of a new algorithm combining simple, non-invasive and
inexpensive tests for predicting the presence of advanced liver fibrosis in patients with chronic
hepatitis B.
Version: 4 Date: 30 Aug 2024
Reviewer's report:
1. The inclusion criteria for this paper are not specific, such as whether patients with previous
decompensated events have been excluded? It is very important.
2. F2 is significant fibrosis, F3 is advanced fibrosis, and there is no concept of severe fibrosis.
3. Figure 1 shows the prediction algorithm for the study population. The proportion of patients
who met the algorithm of PLT > 192 and ALT < 116 to exclude F2 was 53%, but 15% (33/217)
of patients were misclassified. Therefore, the efficiency of ruling out F2 is too low.
4. The AUC of the new algorithm predicting significant fibrosis (#F2) in the training and
validation groups were 0.83 and 0.67, respectively, with a significant decrease in AUC in the
validation cohort, indicating poor extrapolation of the new algorithm.
5. The new algorithm has not been compared with the most commonly used FIB-4 and APRI
models; There is also no comparison with LSM.
6. Except for PLT > 192 and ALT < 116, the GGT and cut-off values of these parameters in
Figure 1 are not detailed in the results section of this paper.
7. The methods section of the abstract mentions that the purpose of the new algorithm is to
predict F0-1, F2, or F3-4. In Table 1, the proportion of patients with F2 was not included in the
pathological METAVIR scoring system.
Title: Diagnostic performance of a new algorithm combining simple, non-invasive and
inexpensive tests for predicting the presence of advanced liver fibrosis in patients with chronic
hepatitis B.
Version: 4 Date: 30 Aug 2024
Reviewer's report:
1. The inclusion criteria for this paper are not specific, such as whether patients with previous
decompensated events have been excluded? It is very important.
2. F2 is significant fibrosis, F3 is advanced fibrosis, and there is no concept of severe fibrosis.
3. Figure 1 shows the prediction algorithm for the study population. The proportion of patients
who met the algorithm of PLT > 192 and ALT < 116 to exclude F2 was 53%, but 15% (33/217)
of patients were misclassified. Therefore, the efficiency of ruling out F2 is too low.
4. The AUC of the new algorithm predicting significant fibrosis (#F2) in the training and
validation groups were 0.83 and 0.67, respectively, with a significant decrease in AUC in the
validation cohort, indicating poor extrapolation of the new algorithm.
5. The new algorithm has not been compared with the most commonly used FIB-4 and APRI
models; There is also no comparison with LSM.
6. Except for PLT > 192 and ALT < 116, the GGT and cut-off values of these parameters in
Figure 1 are not detailed in the results section of this paper.
7. The methods section of the abstract mentions that the purpose of the new algorithm is to
predict F0-1, F2, or F3-4. In Table 1, the proportion of patients with F2 was not included in the
pathological METAVIR scoring system.
Please review this paper.
user
Title: Diagnostic performance of a new algorithm combining simple, non-invasive and
inexpensive tests for predicting the presence of advanced liver fibrosis in patients with chronic
hepatitis B.
Version: 4 Date: 30 Aug 2024
Reviewer's report:
1. The inclusion criteria for this paper are not specific, such as whether patients with previous
decompensated events have been excluded? It is very important.
2. F2 is significant fibrosis, F3 is advanced fibrosis, and there is no concept of severe fibrosis.
3. Figure 1 shows the prediction algorithm for the study population. The proportion of patients
who met the algorithm of PLT > 192 and ALT < 116 to exclude F2 was 53%, but 15% (33/217)
of patients were misclassified. Therefore, the efficiency of ruling out F2 is too low.
4. The AUC of the new algorithm predicting significant fibrosis (#F2) in the training and
validation groups were 0.83 and 0.67, respectively, with a significant decrease in AUC in the
validation cohort, indicating poor extrapolation of the new algorithm.
5. The new algorithm has not been compared with the most commonly used FIB-4 and APRI
models; There is also no comparison with LSM.
6. Except for PLT > 192 and ALT < 116, the GGT and cut-off values of these parameters in
Figure 1 are not detailed in the results section of this paper.
7. The methods section of the abstract mentions that the purpose of the new algorithm is to
predict F0-1, F2, or F3-4. In Table 1, the proportion of patients with F2 was not included in the
pathological METAVIR scoring system.
assistant