Review for 10.1186/s12876-025-03872-5 (2025)

Title: Risk factors for unplanned 31-day readmission after surgery for colorectal cancer Patients:
a meta-analysis
Version: 3 Date: 19 Mar 2025
Reviewer's report:
Strengths of the Study
Comprehensive Meta-Analysis: The study follows PRISMA guidelines and includes a detailed
search strategy across multiple databases, ensuring a thorough review of the literature.
Quality Assessment: The use of the Newcastle-Ottawa Scale for bias assessment enhances the
credibility of the included studies.
Subgroup and Sensitivity Analyses: Various analyses strengthen the validity of the results and
address sources of heterogeneity.
Statistical Rigor: The appropriate use of statistical models, including fixed and random-effects
models, enhances the reliability of the findings.
Clinical Relevance: The study identifies significant predictors of postoperative readmissions,
providing practical insights for improving surgical and postoperative care.
Methodological Issues and Recommendations for Improvement
Study Selection and Inclusion Criteria
The eligibility criteria are well-defined, but the study does not clearly specify the date range for
inclusion. Since medical guidelines and practices evolve, it would be beneficial to justify the
chosen time frame.
It is not clear whether preprints, conference abstracts, or unpublished studies were considered.
Clarifying this would improve transparency.
Data Extraction and Quality Control
The manuscript does not specify how disagreements between reviewers were resolved.
A statement on whether an independent reviewer adjudicated conflicts would enhance
methodological transparency.
Including a flowchart of the study selection process would help visualize how many studies were
screened, excluded, and ultimately included.
Risk of Bias and Publication Bias
The study uses Egger’s test to assess publication bias, and results indicate no significant bias.
However, a funnel plot should be included in the main manuscript for better visualization.
Heterogeneity and Sensitivity Analysis
Several variables show high heterogeneity, such as postoperative complications, tumor site,
stoma creation, and complicated diabetes. Although subgroup analyses were performed, the
study could consider meta-regression to further investigate heterogeneity.
Scientific Issues and Suggested Revisions
Interpretation of Findings
The study reports that female gender is a protective factor against unplanned readmission.
However, a biological rationale for this finding is not provided. Adding an explanation would
strengthen the discussion.
The impact of the Charlson Comorbidity Index on readmission risk is significant, but the study
does not discuss potential confounders, such as preoperative optimization strategies.
Clinical Implications
The discussion should highlight specific interventions that can be implemented in high-risk
patients to reduce readmission rates.
The findings should be compared to current guidelines, such as those from the American College
of Surgeons National Surgical Quality Improvement Program, to provide context and relevance.
Feedback for the Authors
Recommendation: Major Revisions Required
This meta-analysis provides an important contribution to understanding the risk of postoperative
readmission in colorectal cancer patients. However, the manuscript requires improvements in
methodological transparency, bias assessment, and clinical interpretation before acceptance.
Key Revisions Needed
Clarify Study Selection Criteria
Provide a clear time frame for inclusion criteria and justify the decision.
Explain whether preprints, conference abstracts, or unpublished studies were included or
excluded.
Strengthen Bias Assessment
Add a funnel plot to visually demonstrate publication bias.
Clearly state how reviewer disagreements were resolved.
Improve Heterogeneity Analysis
Consider meta-regression as an additional tool to address high heterogeneity in several risk
factors.
Enhance Discussion and Clinical Implications
Provide a biological explanation for gender differences in readmission risk.
Suggest targeted interventions based on the findings to help reduce readmission rates.
Ensure Consistency in Statistical Reporting
Justify the choice of statistical models.
Ensure that the selection of fixed versus random effects models is consistently applied across
all analyses.
Once these revisions are made, the manuscript will be significantly improved and better aligned
with best practices in meta-analysis and evidence-based research.
Supporting Documents for Review
PRISMA checklist
Search strategy details
Risk of bias assessment using the Newcastle-Ottawa Scale
Statistical analyses, including forest plots and Egger’s test results
The authors should submit a revised manuscript along with a detailed response to the reviewer
comments.
Best regards,