The Effect of Study Design Biases on the Diagnostic Accuracy of Magnetic Resonance Imaging for Detecting Silicone Breast Implant Ruptures: A Meta-Analysis

Abstract

Background: 

The U.S. Food and Drug Administration has recommended that all silicone breast implant recipients undergo serial screening to detect implant rupture with magnetic resonance imaging. The authors performed a systematic review and meta-analysis to examine the effect of study design biases on the estimation of magnetic resonance imaging diagnostic accuracy measures.

Methods: 

Studies were identified using the MEDLINE, EMBASE, ISI Web of Science, and Cochrane library databases. Two reviewers independently screened potential studies for inclusion and extracted data. Study design biases were assessed using the Quality of Diagnostic Accuracy Studies tool and the Standards for Reporting of Diagnostic Accuracy Studies checklist. Meta-analyses estimated the influence of biases on diagnostic odds ratios.

Results: 

Among 1175 identified articles, 21 met the inclusion criteria. Most studies using magnetic resonance imaging (10 of 16) and ultrasound (10 of 13) examined symptomatic subjects. Magnetic resonance imaging studies evaluating symptomatic subjects had 14-fold higher diagnostic accuracy estimates compared with studies using an asymptomatic sample (relative diagnostic odds ratio, 13.8; 95 percent confidence interval, 1.83 to 104.6) and 2-fold higher diagnostic accuracy estimates compared with studies using a screening sample (relative diagnostic odds ratio, 1.89; 95 percent confidence interval, 0.05 to 75.7).

Conclusions: 

Many of the published studies using magnetic resonance imaging or ultrasound to detect silicone breast implant rupture are flawed with methodologic biases. These methodologic shortcomings may result in overestimated magnetic resonance imaging diagnostic accuracy measures and should be interpreted with caution when applying the data to a screening population.