Meta-Analysis of Traditional Chinese Medicine for Postoperative Ovarian Cancer, 2018-2025

A systematic review and meta-analysis of 22 randomized controlled trials (n=1719) evaluating Traditional Chinese Medicine as an adjunct to postoperative chemotherapy for ovarian cancer. The study, authored by Yuyang Mi and published on figshare in 2026, synthesized data from six databases to assess toxicity reduction and immune cell recovery. It reports pooled effect sizes for adverse events, T-cell subsets, and performance status scores.

Use Cases

• Evaluating the efficacy of adjunctive Traditional Chinese Medicine for reducing chemotherapy-related adverse events based on the reported risk ratios.
• Analyzing the impact of integrative therapy on immune cell subsets (CD3+, CD4+, CD4+/CD8+ ratio) based on the reported mean differences.
• Assessing changes in patient performance status using Karnofsky Performance Status (KPS) scores from the meta-analysis results.
• Conducting secondary research on the quality and heterogeneity of clinical trials in integrative oncology based on the review's methodology.

Strengths

• The analysis is based on 22 randomized controlled trials involving 1719 patients, providing a substantial evidence base.
• Specific quantitative results are reported, including risk ratios for adverse events (RR=0.35) and mean differences for immune markers (e.g., CD3+ MD=11.74).
• The study protocol was pre-registered with PROSPERO (CRD420251242407), indicating a structured methodological approach.

Limitations

• The primary data file is a 237.8 KB DOCX document, which is a small text file containing the review manuscript, not a raw dataset for direct analysis.
• Column-level documentation for any underlying trial data is absent; field semantics must be inferred from the manuscript text.
• The temporal coverage (2018-2025) includes future dates, which may indicate a planned or ongoing review rather than a completed historical analysis.

Provenance

Source

figshare

Collection Method

Systematic literature search across six databases (CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library) and meta-analysis of selected RCTs.

Time Range

January 2018 to June 2025

Freshness

Last updated 2026-04-30 05:25:02