Title: Clinical implications and molecular mechanisms of Cyclin-dependent kinases 4 for
patients with hepatocellular carcinoma
Version: 4 Date: 12 Nov 2021
Reviewer's report:
Overall, the statistical analysis seems to be appropriately conducted. However, I have a few
comments that need to be addressed.
Are the following results correct (the p-values suggest statistical significance whereas the text
does not)?
Lines 249-151: ROC curve analysis suggested that CDK4 had a statistically better predictive
value (Figure9E, AUC = 0.744, P < 0.001), but CDK1 was not (Figure9B, AUC = 0.702, P <
0.001).
There is mention in the results of a validation cohort – but what this is is not clear. Is it for
example lines 74-76: “A total of 58 pairs of tumor and adjacent normal liver tissues (>3 cm
margin from tumor) of patients pathologically diagnosed as HCC in The First Affiliated Hospital
of Guangxi Medical…”
The results of the survival analysis are much weaker in the validation cohort – particularly
for CDK1 which is not significant (p=0.075) in the (unadjusted) log-rank test (lines 252-254).
This is not highlighted in either the abstract (no description of the p-values or HR’s) or the
main text (discussion section only mentions this in lines 327-329). Given that the validation
cohort is the real test for predictive power, what is the take-home message in regard to each
gene-expression type? Should CDK1 be disregarded as an independent predictor? Indeed, if a
correction for multiple comparisons was performed in the validation cohort, neither CDK1 nor
CDK4 (p=0.042) would be statistically significant, perhaps inferring that whilst the 2 training
cohorts are hypothesis generating, the results cannot be confirmed in a separate cohort.
Similarly, did the authors perform a similar interaction analysis to assess if the joint-effects
observed in the 2 training cohorts could be repeated in the validation cohort?
Title: Clinical implications and molecular mechanisms of Cyclin-dependent kinases 4 for
patients with hepatocellular carcinoma
Version: 4 Date: 12 Nov 2021
Reviewer's report:
Overall, the statistical analysis seems to be appropriately conducted. However, I have a few
comments that need to be addressed.
Are the following results correct (the p-values suggest statistical significance whereas the text
does not)?
Lines 249-151: ROC curve analysis suggested that CDK4 had a statistically better predictive
value (Figure9E, AUC = 0.744, P < 0.001), but CDK1 was not (Figure9B, AUC = 0.702, P <
0.001).
There is mention in the results of a validation cohort – but what this is is not clear. Is it for
example lines 74-76: “A total of 58 pairs of tumor and adjacent normal liver tissues (>3 cm
margin from tumor) of patients pathologically diagnosed as HCC in The First Affiliated Hospital
of Guangxi Medical…”
The results of the survival analysis are much weaker in the validation cohort – particularly
for CDK1 which is not significant (p=0.075) in the (unadjusted) log-rank test (lines 252-254).
This is not highlighted in either the abstract (no description of the p-values or HR’s) or the
main text (discussion section only mentions this in lines 327-329). Given that the validation
cohort is the real test for predictive power, what is the take-home message in regard to each
gene-expression type? Should CDK1 be disregarded as an independent predictor? Indeed, if a
correction for multiple comparisons was performed in the validation cohort, neither CDK1 nor
CDK4 (p=0.042) would be statistically significant, perhaps inferring that whilst the 2 training
cohorts are hypothesis generating, the results cannot be confirmed in a separate cohort.
Similarly, did the authors perform a similar interaction analysis to assess if the joint-effects
observed in the 2 training cohorts could be repeated in the validation cohort?
Please review this paper.
user
Title: Clinical implications and molecular mechanisms of Cyclin-dependent kinases 4 for
patients with hepatocellular carcinoma
Version: 4 Date: 12 Nov 2021
Reviewer's report:
Overall, the statistical analysis seems to be appropriately conducted. However, I have a few
comments that need to be addressed.
Are the following results correct (the p-values suggest statistical significance whereas the text
does not)?
Lines 249-151: ROC curve analysis suggested that CDK4 had a statistically better predictive
value (Figure9E, AUC = 0.744, P < 0.001), but CDK1 was not (Figure9B, AUC = 0.702, P <
0.001).
There is mention in the results of a validation cohort – but what this is is not clear. Is it for
example lines 74-76: “A total of 58 pairs of tumor and adjacent normal liver tissues (>3 cm
margin from tumor) of patients pathologically diagnosed as HCC in The First Affiliated Hospital
of Guangxi Medical…”
The results of the survival analysis are much weaker in the validation cohort – particularly
for CDK1 which is not significant (p=0.075) in the (unadjusted) log-rank test (lines 252-254).
This is not highlighted in either the abstract (no description of the p-values or HR’s) or the
main text (discussion section only mentions this in lines 327-329). Given that the validation
cohort is the real test for predictive power, what is the take-home message in regard to each
gene-expression type? Should CDK1 be disregarded as an independent predictor? Indeed, if a
correction for multiple comparisons was performed in the validation cohort, neither CDK1 nor
CDK4 (p=0.042) would be statistically significant, perhaps inferring that whilst the 2 training
cohorts are hypothesis generating, the results cannot be confirmed in a separate cohort.
Similarly, did the authors perform a similar interaction analysis to assess if the joint-effects
observed in the 2 training cohorts could be repeated in the validation cohort?
assistant