Title: Big Data Analysis of Influenza Vaccination and Liver Cancer Risk in Hypertensive
Patients: Insights from a Nationwide Population-Based Cohort Study
Version: 1 Date: 09 Jul 2024
Reviewer's report:
This study presents an intriguing finding, demonstrating that an increased frequency of influenza
vaccination in hypertensive patients correlates with a reduced risk of liver cancer. However, I
have noted several points for improvement. Please revise the manuscript as much as possible
based on the following suggestions.
Abstract:
The statistical analysis methods mentioned in the Results section should be moved to the
Methods section.
Methods:
2. The data usage period spans from 2001 to 2012. Could more recent data not be utilized? Given
that the medical environment has advanced significantly in the past 10 to 20 years, I believe it
would be better to use newer data.
3. You have designated the year 2000 as a washout period; does this mean that patients who were
prescribed antihypertensive drugs were excluded? If so, please extend the data usage period to
2000–2012 and include this in the exclusion criteria.
4. To clarify the study design, please create a timeline diagram of the study.
5. Indicate the number of patients meeting the inclusion and exclusion criteria in the Results
section.
6. Regarding the definitions of the comorbidities and medications used as covariates: for
diseases, please define them using ICD-9-CM. For medications, please define them using the
WHO-ATC classification.
7. Provide a rationale or add references for selecting statins, metformin, and aspirin as covariates.
Additionally, if you categorized the concurrent medications based on the number of prescription
days during the observation period, please state this as well.
8. The description of propensity score matching is insufficient. Please specify the caliper setting,
whether the sampling was done with or without replacement, and what percentage balance you
aimed to achieve between the two groups using the absolute standardized difference.
9. Is the follow-up start date the day the hypertensive patient last received the influenza
vaccination?
10. Given that the vaccination is free, consider adding cardiovascular disease, renal disease,
compromised immunity, and a body mass index of 30 or greater as confounding factors, as they
are not currently included.
11. Since this study evaluates the incidence of primary liver cancer in hypertensive patients,
death from causes other than primary liver cancer should be considered a competing risk. For
prognostic prediction considering competing risks, the Fine & Gray subdistribution hazard
model is more appropriate than the Cox proportional hazards model. Please consider changing
the main analysis.
Results:
12. In Fig1, indicate the number of patients excluded based on the two criteria for “Definite
Diagnosis of hypertension.” Also, state the number of patients in each group before and after
matching starting from “Included in the Study Cohort.”
13. In Table 1, for “Sex,” specify whether they are male or female. For “Diabetes” and
“Hyperlipidemia,” provide results only for “Yes.”
14. For Tables 2 and 3, if you present the results in the Results section, please describe the
detailed statistical analysis methods used in the Methods section.
15. In Table 2, there are two explanations for † in the footnote; which one is correct?
16. Correct the following:
“…, 15,697 were vaccinated (42.39%) and …” #“…, 15,697 were vaccinated (42.4%) and …”
Title: Big Data Analysis of Influenza Vaccination and Liver Cancer Risk in Hypertensive
Patients: Insights from a Nationwide Population-Based Cohort Study
Version: 1 Date: 09 Jul 2024
Reviewer's report:
This study presents an intriguing finding, demonstrating that an increased frequency of influenza
vaccination in hypertensive patients correlates with a reduced risk of liver cancer. However, I
have noted several points for improvement. Please revise the manuscript as much as possible
based on the following suggestions.
Abstract:
The statistical analysis methods mentioned in the Results section should be moved to the
Methods section.
Methods:
2. The data usage period spans from 2001 to 2012. Could more recent data not be utilized? Given
that the medical environment has advanced significantly in the past 10 to 20 years, I believe it
would be better to use newer data.
3. You have designated the year 2000 as a washout period; does this mean that patients who were
prescribed antihypertensive drugs were excluded? If so, please extend the data usage period to
2000–2012 and include this in the exclusion criteria.
4. To clarify the study design, please create a timeline diagram of the study.
5. Indicate the number of patients meeting the inclusion and exclusion criteria in the Results
section.
6. Regarding the definitions of the comorbidities and medications used as covariates: for
diseases, please define them using ICD-9-CM. For medications, please define them using the
WHO-ATC classification.
7. Provide a rationale or add references for selecting statins, metformin, and aspirin as covariates.
Additionally, if you categorized the concurrent medications based on the number of prescription
days during the observation period, please state this as well.
8. The description of propensity score matching is insufficient. Please specify the caliper setting,
whether the sampling was done with or without replacement, and what percentage balance you
aimed to achieve between the two groups using the absolute standardized difference.
9. Is the follow-up start date the day the hypertensive patient last received the influenza
vaccination?
10. Given that the vaccination is free, consider adding cardiovascular disease, renal disease,
compromised immunity, and a body mass index of 30 or greater as confounding factors, as they
are not currently included.
11. Since this study evaluates the incidence of primary liver cancer in hypertensive patients,
death from causes other than primary liver cancer should be considered a competing risk. For
prognostic prediction considering competing risks, the Fine & Gray subdistribution hazard
model is more appropriate than the Cox proportional hazards model. Please consider changing
the main analysis.
Results:
12. In Fig1, indicate the number of patients excluded based on the two criteria for “Definite
Diagnosis of hypertension.” Also, state the number of patients in each group before and after
matching starting from “Included in the Study Cohort.”
13. In Table 1, for “Sex,” specify whether they are male or female. For “Diabetes” and
“Hyperlipidemia,” provide results only for “Yes.”
14. For Tables 2 and 3, if you present the results in the Results section, please describe the
detailed statistical analysis methods used in the Methods section.
15. In Table 2, there are two explanations for † in the footnote; which one is correct?
16. Correct the following:
“…, 15,697 were vaccinated (42.39%) and …” #“…, 15,697 were vaccinated (42.4%) and …”
Please review this paper.
user
Title: Big Data Analysis of Influenza Vaccination and Liver Cancer Risk in Hypertensive
Patients: Insights from a Nationwide Population-Based Cohort Study
Version: 1 Date: 09 Jul 2024
Reviewer's report:
This study presents an intriguing finding, demonstrating that an increased frequency of influenza
vaccination in hypertensive patients correlates with a reduced risk of liver cancer. However, I
have noted several points for improvement. Please revise the manuscript as much as possible
based on the following suggestions.
Abstract:
The statistical analysis methods mentioned in the Results section should be moved to the
Methods section.
Methods:
2. The data usage period spans from 2001 to 2012. Could more recent data not be utilized? Given
that the medical environment has advanced significantly in the past 10 to 20 years, I believe it
would be better to use newer data.
3. You have designated the year 2000 as a washout period; does this mean that patients who were
prescribed antihypertensive drugs were excluded? If so, please extend the data usage period to
2000–2012 and include this in the exclusion criteria.
4. To clarify the study design, please create a timeline diagram of the study.
5. Indicate the number of patients meeting the inclusion and exclusion criteria in the Results
section.
6. Regarding the definitions of the comorbidities and medications used as covariates: for
diseases, please define them using ICD-9-CM. For medications, please define them using the
WHO-ATC classification.
7. Provide a rationale or add references for selecting statins, metformin, and aspirin as covariates.
Additionally, if you categorized the concurrent medications based on the number of prescription
days during the observation period, please state this as well.
8. The description of propensity score matching is insufficient. Please specify the caliper setting,
whether the sampling was done with or without replacement, and what percentage balance you
aimed to achieve between the two groups using the absolute standardized difference.
9. Is the follow-up start date the day the hypertensive patient last received the influenza
vaccination?
10. Given that the vaccination is free, consider adding cardiovascular disease, renal disease,
compromised immunity, and a body mass index of 30 or greater as confounding factors, as they
are not currently included.
11. Since this study evaluates the incidence of primary liver cancer in hypertensive patients,
death from causes other than primary liver cancer should be considered a competing risk. For
prognostic prediction considering competing risks, the Fine & Gray subdistribution hazard
model is more appropriate than the Cox proportional hazards model. Please consider changing
the main analysis.
Results:
12. In Fig1, indicate the number of patients excluded based on the two criteria for “Definite
Diagnosis of hypertension.” Also, state the number of patients in each group before and after
matching starting from “Included in the Study Cohort.”
13. In Table 1, for “Sex,” specify whether they are male or female. For “Diabetes” and
“Hyperlipidemia,” provide results only for “Yes.”
14. For Tables 2 and 3, if you present the results in the Results section, please describe the
detailed statistical analysis methods used in the Methods section.
15. In Table 2, there are two explanations for † in the footnote; which one is correct?
16. Correct the following:
“…, 15,697 were vaccinated (42.39%) and …” #“…, 15,697 were vaccinated (42.4%) and …”
assistant