Title: Evaluation of Post-market Adverse Events of Lubiprostone: A Real-World Adverse Event
Analysis from the FAERS Database
Version: 3 Date: 26 Feb 2025
Reviewer:  Sheza Malik
Reviewer's report:
Review of the Manuscript: Evaluation of Post-market Adverse Events of Lubiprostone: A Real-
World Adverse Event Analysis from the FAERS Database
General Comments
The manuscript presents a comprehensive post-market safety evaluation of lubiprostone
using FAERS data spanning from 2006 to 2023. The study effectively utilizes various
disproportionality analysis methods (ROR, PRR, BCPNN, and MGPS) to detect potential
adverse drug events (ADEs). The findings provide valuable insights into both known and
previously unreported adverse events, including gastrointestinal, metabolic, and systemic
complications.
Overall, the study is well-structured, and the methodology is sound. The statistical approaches
used for ADE signal detection appear appropriate, and the manuscript does a good job of
interpreting results within the scope of post-marketing surveillance. However, I have identified
areas where the manuscript could be improved for clarity, accuracy, and completeness.
1. Clarity and Transparency in Methodology
Data Extraction and Processing
The authors mention using MySQL and Navicat for data extraction but do not explicitly state
the criteria for including adverse event reports (e.g., how cases were selected from FAERS).
It is unclear whether only primary suspect drug cases were analyzed or if concomitant drugs
were considered in a sensitivity analysis to assess potential confounding effects.
The decision to exclude duplicate cases based on the most recent entry is appropriate, but
more details should be provided on how duplicate entries were handled across different FAERS
reporting quarters.
Signal Detection Thresholds
The manuscript should specify predefined thresholds used for signal detection (e.g., ROR > 1,
PRR > 1, IC025 > 0, EBGM05 > 1).
A sensitivity analysis for different signal thresholds could strengthen confidence in the results.
Causality Considerations
FAERS data relies on spontaneous reporting and lacks denominator data for true incidence
calculation. The authors should explicitly acknowledge the risk of reporting bias and
underreporting of ADEs, particularly for rare events.
The manuscript would benefit from a discussion on causality assessment methods (e.g., WHO-
UMC criteria or Naranjo scale), even if not formally applied in the study.
2. Accuracy and Interpretation of Results
Adverse Events Not in the Drug Label
The identification of gastric fistula and ischemic colitis as potential new ADEs is noteworthy.
However, given the small sample size (n = 5 and n = 19, respectively), the statistical robustness
of these signals should be interpreted cautiously.
The authors should discuss whether these events have been reported in clinical trials or case
reports outside of FAERS to support their clinical relevance.
Systemic Adverse Events and Biological Plausibility
The detection of metabolic alkalosis, blood disorders, and reproductive system disorders is
intriguing but requires stronger mechanistic reasoning.
The discussion on lubiprostone’s systemic effects should be expanded. While the study mentions
CFTR modulation in respiratory epithelial cells, other potential pathways (e.g., prostaglandin-
mediated effects on renal function) should be considered.
3. Data Presentation and Statistical Reporting
Demographic Data
The study reports a higher percentage of ADEs in females (65.39% vs. 21.10% males) but does
not provide age-stratified sex differences.
Given the known sex differences in drug metabolism and adverse event susceptibility, age- and
sex-adjusted analysis could provide additional insights.
Title: Evaluation of Post-market Adverse Events of Lubiprostone: A Real-World Adverse Event
Analysis from the FAERS Database
Version: 3 Date: 26 Feb 2025
Reviewer:  Sheza Malik
Reviewer's report:
Review of the Manuscript: Evaluation of Post-market Adverse Events of Lubiprostone: A Real-
World Adverse Event Analysis from the FAERS Database
General Comments
The manuscript presents a comprehensive post-market safety evaluation of lubiprostone
using FAERS data spanning from 2006 to 2023. The study effectively utilizes various
disproportionality analysis methods (ROR, PRR, BCPNN, and MGPS) to detect potential
adverse drug events (ADEs). The findings provide valuable insights into both known and
previously unreported adverse events, including gastrointestinal, metabolic, and systemic
complications.
Overall, the study is well-structured, and the methodology is sound. The statistical approaches
used for ADE signal detection appear appropriate, and the manuscript does a good job of
interpreting results within the scope of post-marketing surveillance. However, I have identified
areas where the manuscript could be improved for clarity, accuracy, and completeness.
1. Clarity and Transparency in Methodology
Data Extraction and Processing
The authors mention using MySQL and Navicat for data extraction but do not explicitly state
the criteria for including adverse event reports (e.g., how cases were selected from FAERS).
It is unclear whether only primary suspect drug cases were analyzed or if concomitant drugs
were considered in a sensitivity analysis to assess potential confounding effects.
The decision to exclude duplicate cases based on the most recent entry is appropriate, but
more details should be provided on how duplicate entries were handled across different FAERS
reporting quarters.
Signal Detection Thresholds
The manuscript should specify predefined thresholds used for signal detection (e.g., ROR > 1,
PRR > 1, IC025 > 0, EBGM05 > 1).
A sensitivity analysis for different signal thresholds could strengthen confidence in the results.
Causality Considerations
FAERS data relies on spontaneous reporting and lacks denominator data for true incidence
calculation. The authors should explicitly acknowledge the risk of reporting bias and
underreporting of ADEs, particularly for rare events.
The manuscript would benefit from a discussion on causality assessment methods (e.g., WHO-
UMC criteria or Naranjo scale), even if not formally applied in the study.
2. Accuracy and Interpretation of Results
Adverse Events Not in the Drug Label
The identification of gastric fistula and ischemic colitis as potential new ADEs is noteworthy.
However, given the small sample size (n = 5 and n = 19, respectively), the statistical robustness
of these signals should be interpreted cautiously.
The authors should discuss whether these events have been reported in clinical trials or case
reports outside of FAERS to support their clinical relevance.
Systemic Adverse Events and Biological Plausibility
The detection of metabolic alkalosis, blood disorders, and reproductive system disorders is
intriguing but requires stronger mechanistic reasoning.
The discussion on lubiprostone’s systemic effects should be expanded. While the study mentions
CFTR modulation in respiratory epithelial cells, other potential pathways (e.g., prostaglandin-
mediated effects on renal function) should be considered.
3. Data Presentation and Statistical Reporting
Demographic Data
The study reports a higher percentage of ADEs in females (65.39% vs. 21.10% males) but does
not provide age-stratified sex differences.
Given the known sex differences in drug metabolism and adverse event susceptibility, age- and
sex-adjusted analysis could provide additional insights.
Please review this paper.
user
Title: Evaluation of Post-market Adverse Events of Lubiprostone: A Real-World Adverse Event
Analysis from the FAERS Database
Version: 3 Date: 26 Feb 2025
Reviewer:  Sheza Malik
Reviewer's report:
Review of the Manuscript: Evaluation of Post-market Adverse Events of Lubiprostone: A Real-
World Adverse Event Analysis from the FAERS Database
General Comments
The manuscript presents a comprehensive post-market safety evaluation of lubiprostone
using FAERS data spanning from 2006 to 2023. The study effectively utilizes various
disproportionality analysis methods (ROR, PRR, BCPNN, and MGPS) to detect potential
adverse drug events (ADEs). The findings provide valuable insights into both known and
previously unreported adverse events, including gastrointestinal, metabolic, and systemic
complications.
Overall, the study is well-structured, and the methodology is sound. The statistical approaches
used for ADE signal detection appear appropriate, and the manuscript does a good job of
interpreting results within the scope of post-marketing surveillance. However, I have identified
areas where the manuscript could be improved for clarity, accuracy, and completeness.
1. Clarity and Transparency in Methodology
Data Extraction and Processing
The authors mention using MySQL and Navicat for data extraction but do not explicitly state
the criteria for including adverse event reports (e.g., how cases were selected from FAERS).
It is unclear whether only primary suspect drug cases were analyzed or if concomitant drugs
were considered in a sensitivity analysis to assess potential confounding effects.
The decision to exclude duplicate cases based on the most recent entry is appropriate, but
more details should be provided on how duplicate entries were handled across different FAERS
reporting quarters.
Signal Detection Thresholds
The manuscript should specify predefined thresholds used for signal detection (e.g., ROR > 1,
PRR > 1, IC025 > 0, EBGM05 > 1).
A sensitivity analysis for different signal thresholds could strengthen confidence in the results.
Causality Considerations
FAERS data relies on spontaneous reporting and lacks denominator data for true incidence
calculation. The authors should explicitly acknowledge the risk of reporting bias and
underreporting of ADEs, particularly for rare events.
The manuscript would benefit from a discussion on causality assessment methods (e.g., WHO-
UMC criteria or Naranjo scale), even if not formally applied in the study.
2. Accuracy and Interpretation of Results
Adverse Events Not in the Drug Label
The identification of gastric fistula and ischemic colitis as potential new ADEs is noteworthy.
However, given the small sample size (n = 5 and n = 19, respectively), the statistical robustness
of these signals should be interpreted cautiously.
The authors should discuss whether these events have been reported in clinical trials or case
reports outside of FAERS to support their clinical relevance.
Systemic Adverse Events and Biological Plausibility
The detection of metabolic alkalosis, blood disorders, and reproductive system disorders is
intriguing but requires stronger mechanistic reasoning.
The discussion on lubiprostone’s systemic effects should be expanded. While the study mentions
CFTR modulation in respiratory epithelial cells, other potential pathways (e.g., prostaglandin-
mediated effects on renal function) should be considered.
3. Data Presentation and Statistical Reporting
Demographic Data
The study reports a higher percentage of ADEs in females (65.39% vs. 21.10% males) but does
not provide age-stratified sex differences.
Given the known sex differences in drug metabolism and adverse event susceptibility, age- and
sex-adjusted analysis could provide additional insights.
assistant