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Updated: Nov 15, 2025

Preparation, Procedures and Evaluation of Platelet-Rich Plasma Injection in the Treatment of Knee Osteoarthritis
Published on: January 4, 2019
The Statistical Fragility of Platelet-Rich Plasma in Rotator Cuff Surgery: A Systematic Review and Meta-analysis
Robert L Parisien1, Cooper Ehlers2, Antonio Cusano3
1Harvard Medical School, Boston, Massachusetts, USA.
Background:
The practice of evidence-based medicine relies on objective data to guide clinical decision-making with specific statistical thresholds conveying study significance.
Purpose:
To determine the utility of applying the fragility index (FI) and the fragility quotient (FQ) analysis to randomized controlled trials (RCTs) evaluating the utilization of platelet-rich plasma (PRP) in rotator cuff repairs (RCRs).
Study Design:
Systematic review and meta-analysis.
Methods:
RCTs pertaining to the utilization of PRP in surgical RCRs published in 13 peer-reviewed journals from 2000 to 2020 were evaluated. The FI was determined by manipulating each reported outcome event until a reversal of significance was appreciated. The associated FQ was determined by dividing the FI by the sample size.
Results:
Of the 9746 studies screened, 19 RCTs were ultimately included for analysis. The overall FI incorporating all 19 RCTs was only 4, suggesting that the reversal of only 4 events is required to change study significance. The associated FQ was determined as 0.092. Of the 43 outcome events reporting lost to follow-up data, 13 (30.2%) represented lost to follow-up >4.
Conclusion:
Our analysis suggests that RCTs evaluating PRP for surgical RCRs may lack statistical stability with only a few outcome events required to alter trial significance. Therefore, we recommend the reporting of an FI and an FQ in conjunction with P value analysis to carefully interpret the integrity of statistical stability in future comparative trials.
Clinical Relevance:
Clinical decisions are often informed by statistically significant results. Thus, a true understanding of the robustness of the statistical findings informing clinical decision-making is of critical importance.
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