We need to do better: A systematic review and meta-analysis of diagnostic test accuracy of restless legs syndrome screening instruments. (August 2021) - Fulda, Stephany; Allen, Richard P.; Earley, Christopher J.; Högl, Birgit; Garcia-Borreguero, Diego; Inoue, Yuichi; Ondo, William; Walters, Arthur S.; Williams, Anne-Marie; Winkelman, John W.
Summary: This systematic review and meta-analysis evaluated the diagnostic accuracy of screening instruments for restless legs syndrome (RLS) and reports sensitivity, specificity, positive (PPV) and negative predictive values (NPV). Searches for primary studies were conducted in electronic databases. Of the 1541 citations identified, 52 were included in the meta-analysis. The methodological quality of each study was evaluated using QUADAS-2. Only 14 studies assessed the reference standard in all participants or in all screen-positives and a selection of screen-negatives. Bivariate meta-analysis of these 14 studies estimated median sensitivity to be 0.88 (0.72–0.96) and specificity 0.90 (0.84–0.93); based on a population prevalence of 5%, the calculated PPV was 0.31 (0.27–0.34). For all 52 studies, with either full or partial verification of RLS status, we constructed best-case scenario sensitivities and specificities at pre-defined levels of prevalence: across all samples, when prevalence is 5%, the median best-case scenario PPV is 0.48 with significant between-study heterogeneity. No RLS screening instruments can currently be recommended for use without an expert clinical interview in epidemiological studies. For conditions with statistically low prevalence such as RLS, the specificity, not the sensitivity, of a screening instrument determines true prevalence. Therefore, future instruments should maximize specificity. We provide guidelines on RLS ascertainment in epidemiological studies that requires a two-step process with clinical interview following a screening test, and given the poor reporting quality of many RLS epidemiological studies, we include an RLS reporting checklist.