GIRADS: método de clasificación de masas anexiales, revisión sistemática y metanálisis. 10 años de experiencia

Abstract

Objective: to evaluate the experience of using GIRADS method to classify adnexal masses ten years after its publication. Method: A search was carried out for studies reporting on the use of the GIRADS system in the Medline (Pubmed), Google Scholar and Web of Science databases, from January 2009 to December 2019. Pooled sensitivity and specificity, Likelihood ratio (LR) (+) and LR (-) and Diagnostic Odds ratio (DOR) were calculated. The quality of the studies was assessed by QUADAS-2. Results: 15 studies were identified, and 13 of them were included with 4473 masses, of which 878 were malignant. The mean prevalence of ovarian malignancy was 23% and the prevalence pooled. of 19.6%. The risk of bias was high in four studies for the domain 'patient selection' and low for all studies for the domains 'index test' and 'reference test'. The sensitivity, specificity, pooled LR (+) and LR (-) and the DOR of the GIRADS system to classify adnexal masses were 96.8% (95% confidence interval [CI] = 94%-98%), 91.2 % (95% CI = 85%-94%), 11.0 (95% CI = 6.9-13.4) and 0.035 (95% CI = 0.02-0.09), and 209 (95% CI = 99-444), respectively. Heterogeneity was high for both sensitivity and specificity. According to meta-regression, this heterogeneity was explained by the prevalence of malignancy, the use of multiple observers, and the absence of histopathological diagnosis for all cases included in a given study. Conclusion: the GIRADS system has a good diagnostic performance to classify adnexal masses.

Curva de aprendizaje para el diagnóstico ecográfico específico de masas anexiales

“…La disponibilidad de expertos es de utilidad para emitir un informe adecuado que mejore la comunicación con los médicos tratantes, como muy recientemente se ha reportado en un metanálisis de GIRADS 47 .…”

Sensitivity and Specificity of Ultrasonography Using Ovarian-Adnexal Reporting and Data System Classification Versus Pathology Findings for Ovarian Cancer

“…First proposed in 2018 by the ACR, the Ovarian-Adnexal Reporting and Data System (O-RADS) is a method for categorizing ovarian masses, mainly by ultrasound [ 4 ]. Although systems such as the International Ovarian Tumor Analysis (IOTA) and GI-RADS have already targeted this goal, recent studies show that O-RADS has higher sensitivity (96.8%) and specificity (92.8%) [ 4 , 5 ].…”