Au SCL. Pearls of meta-analyses and systematic review in scientific evidence. World J Clin Cases 2024; 12(16): 2701-2703 [PMID: 38899305 DOI: 10.12998/wjcc.v12.i16.2701]
Corresponding Author of This Article
Sunny Chi Lik Au, MBChB, Chief Doctor, Surgeon, Department of Ophthalmology, Tung Wah Eastern Hospital, 9/F, MO Office, Lo Ka Chow Memorial Ophthalmic Centre, 19 Eastern Hospital Road, Causeway Bay, Hong Kong, China. kilihcua@gmail.com
Research Domain of This Article
Medicine, Research & Experimental
Article-Type of This Article
Editorial
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Jun 6, 2024; 12(16): 2701-2703 Published online Jun 6, 2024. doi: 10.12998/wjcc.v12.i16.2701
Pearls of meta-analyses and systematic review in scientific evidence
Sunny Chi Lik Au
Sunny Chi Lik Au, Department of Ophthalmology, Tung Wah Eastern Hospital, Hong Kong, China
Author contributions: Au SCL conceptualized the editorial, acquired and analyzed the data, and wrote the manuscript. All authors have read and approve the final manuscript.
Conflict-of-interest statement: All authors have disclosed no conflicts of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Sunny Chi Lik Au, MBChB, Chief Doctor, Surgeon, Department of Ophthalmology, Tung Wah Eastern Hospital, 9/F, MO Office, Lo Ka Chow Memorial Ophthalmic Centre, 19 Eastern Hospital Road, Causeway Bay, Hong Kong, China. kilihcua@gmail.com
Received: March 3, 2024 Revised: April 10, 2024 Accepted: April 23, 2024 Published online: June 6, 2024 Processing time: 87 Days and 2.7 Hours
Abstract
Scientific evidence develops bit by bit from case reports, case series; to larger case-control, case-cohort; and further escalate to randomized controlled trials. This echoed the importance of continue publishing World journal of Clinical Cases, where novel and advancing discoveries start from a single case. In contrast, at the other end of the realm of evidence synthesis, systematic review and meta-analysis represent distinct yet interconnected processes. Butorphanol in epidural labor analgesia has long been studied since 1989, and with 70 publications from MEDLINE searches. However, there was no meta-analysis, nor any systematic review published so far. The latest in-press article published by Tang et al. on the protocol for the systematic review and meta-analysis on the safety and effectiveness of butorphanol in epidural labor analgesia is encouraging. We believe the findings of this study will be valuable for clinical practice as well as for future research.
Core Tip: Scientific evidence evolves from case reports to randomized controlled trials. Systematic reviews and meta-analyses are crucial but can be flawed due to limited information, the so called: “Garbage in, Garbage out”. In running the meta-analysis, mathematical pooling can be invalidated by study heterogeneity, poor study quality, and publication bias. Remedial measures include exploring heterogeneity, restricting meta-analysis to systematic review in case of insufficient information, and addressing different types of bias. Remember, the pearl of meta-analyses relies on quality over quantity in evidence synthesis.
