Meta-Analyses in Plastic Surgery: Can We Trust Their Results?
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Updated: Jan 21, 2026

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Published on: October 20, 2022
Connor McGuire1, Osama A Samargandi1, Joseph Corkum1
1From the Faculty of Medicine and the Division of Plastic and Reconstructive Surgery, Dalhousie University; the Division of Plastic and Reconstructive Surgery, University of Toronto; and the Division of Plastic and Reconstructive Surgery, Department of Surgery, King Abdulaziz University.
Background:
Meta-analyses are common in the plastic surgery literature, but studies concerning their quality are lacking. The authors assessed the overall quality of meta-analyses in plastic surgery, and attempted to identify variables associated with scientific quality.
Methods:
A systematic review of meta-analyses published in seven plastic surgery journals between 2007 and 2017 was undertaken. Publication descriptors and methodologic details were extracted. Articles were assessed using the following two instruments: A Measurement Tool to Assess Systematic Reviews (AMSTAR) and AMSTAR 2.
Results:
Seventy-four studies were included. The number of meta-analyses per year increased. Most meta-analyses assessed a single intervention (59.5 percent), and pooled a mean of 20.9 studies (range, two to 134), including a mean of 2463 patients (range, 44 to 14,884). Most meta-analyses were published in Plastic and Reconstructive Surgery (44.6 percent) and included midlevel evidence (II to IV) primary studies. Only 16.2 percent of meta-analyses included randomized controlled trials. Meta-analyses generally reported positive (81.1 percent) and significant results (77.0 percent). Median AMSTAR score was 7 of 11 (interquartile range, 5 to 8). Higher AMSTAR scores correlated with more recent meta-analyses that provided a rationale for statistical pooling, and appropriately managed methodologic heterogeneity (r = 0.66; p < 0.01).
Conclusions:
Despite an increase in number and quality, meta-analyses are at high risk of bias because of the low level of evidence of included primary studies and heterogeneity within and between primary studies. Plastic surgeons should be aware of the pitfalls of conducting and interpreting meta-analyses.
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