Title: Metabolic Dysfunction, Cirrhosis, and HCV Genotype 3a Drive Type 2 Diabetes Risk in
Chronic Hepatitis C: A Southern Chinese Cohort Study
Version: 2 Date: 11 May 2025
Reviewer's report:
This manuscript addresses a clinically relevant topic by exploring the risk factors associated with
the development of type 2 diabetes mellitus (T2DM) in patients with chronic hepatitis C virus
(CHC) infection in a Chinese cohort. The authors performed a retrospective cohort analysis of
442 patients and used logistic regression and ROC analyses to identify independent predictors
of T2DM. The study found that age, metabolic parameters (fasting glucose, insulin, HOMA-
IR), GGT, hypertension, and cirrhosis were significant risk factors, and that HCV genotype
3a was more prevalent in diabetic patients. While the study offers important region-specific
data and attempts to stratify risk by genotype, there are notable methodological, analytical, and
interpretive concerns that limit the current scientific merit and validity of its conclusions.
Major Concerns:
The study’s retrospective design is acknowledged, but the methodology section lacks sufficient
detail regarding patient selection, particularly how patients were matched for gender, age,
and BMI. The matching process is stated but not statistically verified, raising concerns
about potential selection bias. Furthermore, the HCV genotyping was performed only on a
subset (n=286/442), disproportionately excluding diabetic inpatients (only outpatients were
genotyped), which severely limits the generalizability and strength of the genotype-related
conclusions. The regression analysis presents contradictory findings, such as HOMA-IR being
protective in multivariate analysis (OR<1) despite being elevated in diabetic patients. This
indicates a possible multicollinearity issue or model overfitting that has not been addressed or
tested. Similarly, the role of ALT and AST was not clarified in the final model, and several
variables that were significant in univariate analysis disappeared from the multivariate results
without explanation. The clinical interpretation of the AUC values in ROC analysis, while
statistically significant, does not provide additional clinical decision-making value as fasting
glucose is already a diagnostic criterion for diabetes. This makes the claim of predictive
utility somewhat tautological. Finally, the discussion section reiterates known findings without
offering novel mechanistic insights or linking them back effectively to the regional genotype
findings, which remain speculative due to small sample size and underpowered subgroup
analysis.
Minor Concerns:
There are substantial issues with grammar, syntax, and style throughout the manuscript.
Numerous sentences are overly long, poorly structured, and contain tense shifts or awkward
phrasing that hinder readability. Examples include the abstract (“Early screening for glucose
intolerance and genotype-specific interventions are critical…”) which implies interventional
data not provided, and phrases such as “CHC may present different clinical characteristics”
which should be revised for precision. The manuscript also has inconsistencies in terminology
(e.g., “HCH” used instead of “CHC” in several instances) and the abbreviation list is overly long
and includes terms not used in the manuscript. References are generally adequate, though some
key papers discussing HCV-induced metabolic disruption (e.g., recent reviews on genotype 3
and steatosis) are missing. The tables are informative but overly dense; some simplification or
visual emphasis (e.g., bolding significant results) would enhance clarity. The genotyping method
is well-described, but more emphasis should be placed on why only outpatients were genotyped
and how this impacts validity.
Title: Metabolic Dysfunction, Cirrhosis, and HCV Genotype 3a Drive Type 2 Diabetes Risk in
Chronic Hepatitis C: A Southern Chinese Cohort Study
Version: 2 Date: 11 May 2025
Reviewer's report:
This manuscript addresses a clinically relevant topic by exploring the risk factors associated with
the development of type 2 diabetes mellitus (T2DM) in patients with chronic hepatitis C virus
(CHC) infection in a Chinese cohort. The authors performed a retrospective cohort analysis of
442 patients and used logistic regression and ROC analyses to identify independent predictors
of T2DM. The study found that age, metabolic parameters (fasting glucose, insulin, HOMA-
IR), GGT, hypertension, and cirrhosis were significant risk factors, and that HCV genotype
3a was more prevalent in diabetic patients. While the study offers important region-specific
data and attempts to stratify risk by genotype, there are notable methodological, analytical, and
interpretive concerns that limit the current scientific merit and validity of its conclusions.
Major Concerns:
The study’s retrospective design is acknowledged, but the methodology section lacks sufficient
detail regarding patient selection, particularly how patients were matched for gender, age,
and BMI. The matching process is stated but not statistically verified, raising concerns
about potential selection bias. Furthermore, the HCV genotyping was performed only on a
subset (n=286/442), disproportionately excluding diabetic inpatients (only outpatients were
genotyped), which severely limits the generalizability and strength of the genotype-related
conclusions. The regression analysis presents contradictory findings, such as HOMA-IR being
protective in multivariate analysis (OR<1) despite being elevated in diabetic patients. This
indicates a possible multicollinearity issue or model overfitting that has not been addressed or
tested. Similarly, the role of ALT and AST was not clarified in the final model, and several
variables that were significant in univariate analysis disappeared from the multivariate results
without explanation. The clinical interpretation of the AUC values in ROC analysis, while
statistically significant, does not provide additional clinical decision-making value as fasting
glucose is already a diagnostic criterion for diabetes. This makes the claim of predictive
utility somewhat tautological. Finally, the discussion section reiterates known findings without
offering novel mechanistic insights or linking them back effectively to the regional genotype
findings, which remain speculative due to small sample size and underpowered subgroup
analysis.
Minor Concerns:
There are substantial issues with grammar, syntax, and style throughout the manuscript.
Numerous sentences are overly long, poorly structured, and contain tense shifts or awkward
phrasing that hinder readability. Examples include the abstract (“Early screening for glucose
intolerance and genotype-specific interventions are critical…”) which implies interventional
data not provided, and phrases such as “CHC may present different clinical characteristics”
which should be revised for precision. The manuscript also has inconsistencies in terminology
(e.g., “HCH” used instead of “CHC” in several instances) and the abbreviation list is overly long
and includes terms not used in the manuscript. References are generally adequate, though some
key papers discussing HCV-induced metabolic disruption (e.g., recent reviews on genotype 3
and steatosis) are missing. The tables are informative but overly dense; some simplification or
visual emphasis (e.g., bolding significant results) would enhance clarity. The genotyping method
is well-described, but more emphasis should be placed on why only outpatients were genotyped
and how this impacts validity.
Please review this paper.
user
Title: Metabolic Dysfunction, Cirrhosis, and HCV Genotype 3a Drive Type 2 Diabetes Risk in
Chronic Hepatitis C: A Southern Chinese Cohort Study
Version: 2 Date: 11 May 2025
Reviewer's report:
This manuscript addresses a clinically relevant topic by exploring the risk factors associated with
the development of type 2 diabetes mellitus (T2DM) in patients with chronic hepatitis C virus
(CHC) infection in a Chinese cohort. The authors performed a retrospective cohort analysis of
442 patients and used logistic regression and ROC analyses to identify independent predictors
of T2DM. The study found that age, metabolic parameters (fasting glucose, insulin, HOMA-
IR), GGT, hypertension, and cirrhosis were significant risk factors, and that HCV genotype
3a was more prevalent in diabetic patients. While the study offers important region-specific
data and attempts to stratify risk by genotype, there are notable methodological, analytical, and
interpretive concerns that limit the current scientific merit and validity of its conclusions.
Major Concerns:
The study’s retrospective design is acknowledged, but the methodology section lacks sufficient
detail regarding patient selection, particularly how patients were matched for gender, age,
and BMI. The matching process is stated but not statistically verified, raising concerns
about potential selection bias. Furthermore, the HCV genotyping was performed only on a
subset (n=286/442), disproportionately excluding diabetic inpatients (only outpatients were
genotyped), which severely limits the generalizability and strength of the genotype-related
conclusions. The regression analysis presents contradictory findings, such as HOMA-IR being
protective in multivariate analysis (OR<1) despite being elevated in diabetic patients. This
indicates a possible multicollinearity issue or model overfitting that has not been addressed or
tested. Similarly, the role of ALT and AST was not clarified in the final model, and several
variables that were significant in univariate analysis disappeared from the multivariate results
without explanation. The clinical interpretation of the AUC values in ROC analysis, while
statistically significant, does not provide additional clinical decision-making value as fasting
glucose is already a diagnostic criterion for diabetes. This makes the claim of predictive
utility somewhat tautological. Finally, the discussion section reiterates known findings without
offering novel mechanistic insights or linking them back effectively to the regional genotype
findings, which remain speculative due to small sample size and underpowered subgroup
analysis.
Minor Concerns:
There are substantial issues with grammar, syntax, and style throughout the manuscript.
Numerous sentences are overly long, poorly structured, and contain tense shifts or awkward
phrasing that hinder readability. Examples include the abstract (“Early screening for glucose
intolerance and genotype-specific interventions are critical…”) which implies interventional
data not provided, and phrases such as “CHC may present different clinical characteristics”
which should be revised for precision. The manuscript also has inconsistencies in terminology
(e.g., “HCH” used instead of “CHC” in several instances) and the abbreviation list is overly long
and includes terms not used in the manuscript. References are generally adequate, though some
key papers discussing HCV-induced metabolic disruption (e.g., recent reviews on genotype 3
and steatosis) are missing. The tables are informative but overly dense; some simplification or
visual emphasis (e.g., bolding significant results) would enhance clarity. The genotyping method
is well-described, but more emphasis should be placed on why only outpatients were genotyped
and how this impacts validity.
assistant