Title: Validation of the diagnostic accuracy of the acFibroMASH index for at-risk MASH in
patients with metabolic dysfunction-associated steatotic liver disease
Version: 1 Date: 04 Feb 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The introduction includes a detailed description of the diagnostic criteria for MASLD, but it
could benefit from a clearer delineation between MASLD and MASH. While the metabolic
risk factors for MASLD are listed, a brief explanation of how these factors contribute to the
progression to MASH and at-risk MASH would strengthen the narrative.
-The introduction introduces the acFibroMASH index briefly but could do more to explain its
specific value in identifying at-risk MASH patients compared to other models. The mention of
previous studies and the index's efficacy in detecting at-risk MASH is a good start, but more
detailed context about why this model is promising compared to existing alternatives would help
the reader better appreciate its clinical potential.
-While the biopsy procedure is described, more detail could be provided on the specifics of
the histological analysis. For example, how were the fibrosis stages (F0-F4) and NAFLD
activity scores (NAS) determined? Were there any inter-rater reliability measures in place for
the pathologists interpreting the biopsies? This would strengthen the confidence in the biopsy-
based reference standard.
-While the formulas for calculating the acFibroMASH index and other diagnostic scores are
presented, some explanation of how the individual components (e.g., LSM, acMASH) are
weighted or how the acFibroMASH model was developed would be helpful. For instance, why
were liver stiffness (LSM), AST/Creatinine ratio, and other specific biomarkers chosen for this
index? Additional explanation of the underlying rationale for these variables could enhance the
reader's understanding of how this model was designed and its potential clinical utility.
-While the inclusion of significant fibrosis is clear (NAFLD activity score #4 and fibrosis stage
#2), it might be helpful to clarify how the NAS score is calculated in this context. Specifically,
is the NAS score used as a continuous variable or as a categorical cutoff in this study? This
would provide more transparency about how NAS and fibrosis staging interact in defining at-
risk MASH.
-While the discussion highlights that the acFibroMASH index outperforms FIB-4, NFS, and
APRI, it could benefit from a deeper comparison of these models, particularly in terms of
practical applicability. For example, the authors could elaborate on why FIB-4 and NFS (which
are widely used for fibrosis assessment) may not perform well in the early stages of MASH or at-
risk MASH, offering a clearer rationale for the superiority of acFibroMASH in these contexts.
-Additionally, further discussion on the limitations of FAST in comparison to acFibroMASH,
especially regarding its reliance on CAP and LSM (which may be more expensive or less
accessible in some settings), would provide a more balanced comparison.
-The study mentions false-positive and false-negative results but doesn’t delve into the clinical
consequences of these errors. For instance, in the context of false-negative results, how might
missing a true at-risk MASH case impact long-term patient outcomes or treatment? Similarly,
what is the clinical significance of false-positive results, especially in a primary care setting
where diagnostic resources are limited? A more detailed analysis of the potential harms or
benefits of these errors would enrich the discussion.
-While the authors mention the need for prospective cohort studies, it would be beneficial to
provide more detail about how a larger and more diverse cohort would improve the robustness
of the findings. Specifically, how would the inclusion of patients with different comorbidities,
from different geographic areas, and with varying stages of fibrosis further strengthen the
generalizability and predictive accuracy of the acFibroMASH index?
Title: Validation of the diagnostic accuracy of the acFibroMASH index for at-risk MASH in
patients with metabolic dysfunction-associated steatotic liver disease
Version: 1 Date: 04 Feb 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The introduction includes a detailed description of the diagnostic criteria for MASLD, but it
could benefit from a clearer delineation between MASLD and MASH. While the metabolic
risk factors for MASLD are listed, a brief explanation of how these factors contribute to the
progression to MASH and at-risk MASH would strengthen the narrative.
-The introduction introduces the acFibroMASH index briefly but could do more to explain its
specific value in identifying at-risk MASH patients compared to other models. The mention of
previous studies and the index's efficacy in detecting at-risk MASH is a good start, but more
detailed context about why this model is promising compared to existing alternatives would help
the reader better appreciate its clinical potential.
-While the biopsy procedure is described, more detail could be provided on the specifics of
the histological analysis. For example, how were the fibrosis stages (F0-F4) and NAFLD
activity scores (NAS) determined? Were there any inter-rater reliability measures in place for
the pathologists interpreting the biopsies? This would strengthen the confidence in the biopsy-
based reference standard.
-While the formulas for calculating the acFibroMASH index and other diagnostic scores are
presented, some explanation of how the individual components (e.g., LSM, acMASH) are
weighted or how the acFibroMASH model was developed would be helpful. For instance, why
were liver stiffness (LSM), AST/Creatinine ratio, and other specific biomarkers chosen for this
index? Additional explanation of the underlying rationale for these variables could enhance the
reader's understanding of how this model was designed and its potential clinical utility.
-While the inclusion of significant fibrosis is clear (NAFLD activity score #4 and fibrosis stage
#2), it might be helpful to clarify how the NAS score is calculated in this context. Specifically,
is the NAS score used as a continuous variable or as a categorical cutoff in this study? This
would provide more transparency about how NAS and fibrosis staging interact in defining at-
risk MASH.
-While the discussion highlights that the acFibroMASH index outperforms FIB-4, NFS, and
APRI, it could benefit from a deeper comparison of these models, particularly in terms of
practical applicability. For example, the authors could elaborate on why FIB-4 and NFS (which
are widely used for fibrosis assessment) may not perform well in the early stages of MASH or at-
risk MASH, offering a clearer rationale for the superiority of acFibroMASH in these contexts.
-Additionally, further discussion on the limitations of FAST in comparison to acFibroMASH,
especially regarding its reliance on CAP and LSM (which may be more expensive or less
accessible in some settings), would provide a more balanced comparison.
-The study mentions false-positive and false-negative results but doesn’t delve into the clinical
consequences of these errors. For instance, in the context of false-negative results, how might
missing a true at-risk MASH case impact long-term patient outcomes or treatment? Similarly,
what is the clinical significance of false-positive results, especially in a primary care setting
where diagnostic resources are limited? A more detailed analysis of the potential harms or
benefits of these errors would enrich the discussion.
-While the authors mention the need for prospective cohort studies, it would be beneficial to
provide more detail about how a larger and more diverse cohort would improve the robustness
of the findings. Specifically, how would the inclusion of patients with different comorbidities,
from different geographic areas, and with varying stages of fibrosis further strengthen the
generalizability and predictive accuracy of the acFibroMASH index?
Please review this paper.
user
Title: Validation of the diagnostic accuracy of the acFibroMASH index for at-risk MASH in
patients with metabolic dysfunction-associated steatotic liver disease
Version: 1 Date: 04 Feb 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The introduction includes a detailed description of the diagnostic criteria for MASLD, but it
could benefit from a clearer delineation between MASLD and MASH. While the metabolic
risk factors for MASLD are listed, a brief explanation of how these factors contribute to the
progression to MASH and at-risk MASH would strengthen the narrative.
-The introduction introduces the acFibroMASH index briefly but could do more to explain its
specific value in identifying at-risk MASH patients compared to other models. The mention of
previous studies and the index's efficacy in detecting at-risk MASH is a good start, but more
detailed context about why this model is promising compared to existing alternatives would help
the reader better appreciate its clinical potential.
-While the biopsy procedure is described, more detail could be provided on the specifics of
the histological analysis. For example, how were the fibrosis stages (F0-F4) and NAFLD
activity scores (NAS) determined? Were there any inter-rater reliability measures in place for
the pathologists interpreting the biopsies? This would strengthen the confidence in the biopsy-
based reference standard.
-While the formulas for calculating the acFibroMASH index and other diagnostic scores are
presented, some explanation of how the individual components (e.g., LSM, acMASH) are
weighted or how the acFibroMASH model was developed would be helpful. For instance, why
were liver stiffness (LSM), AST/Creatinine ratio, and other specific biomarkers chosen for this
index? Additional explanation of the underlying rationale for these variables could enhance the
reader's understanding of how this model was designed and its potential clinical utility.
-While the inclusion of significant fibrosis is clear (NAFLD activity score #4 and fibrosis stage
#2), it might be helpful to clarify how the NAS score is calculated in this context. Specifically,
is the NAS score used as a continuous variable or as a categorical cutoff in this study? This
would provide more transparency about how NAS and fibrosis staging interact in defining at-
risk MASH.
-While the discussion highlights that the acFibroMASH index outperforms FIB-4, NFS, and
APRI, it could benefit from a deeper comparison of these models, particularly in terms of
practical applicability. For example, the authors could elaborate on why FIB-4 and NFS (which
are widely used for fibrosis assessment) may not perform well in the early stages of MASH or at-
risk MASH, offering a clearer rationale for the superiority of acFibroMASH in these contexts.
-Additionally, further discussion on the limitations of FAST in comparison to acFibroMASH,
especially regarding its reliance on CAP and LSM (which may be more expensive or less
accessible in some settings), would provide a more balanced comparison.
-The study mentions false-positive and false-negative results but doesn’t delve into the clinical
consequences of these errors. For instance, in the context of false-negative results, how might
missing a true at-risk MASH case impact long-term patient outcomes or treatment? Similarly,
what is the clinical significance of false-positive results, especially in a primary care setting
where diagnostic resources are limited? A more detailed analysis of the potential harms or
benefits of these errors would enrich the discussion.
-While the authors mention the need for prospective cohort studies, it would be beneficial to
provide more detail about how a larger and more diverse cohort would improve the robustness
of the findings. Specifically, how would the inclusion of patients with different comorbidities,
from different geographic areas, and with varying stages of fibrosis further strengthen the
generalizability and predictive accuracy of the acFibroMASH index?
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