Optimal cutoff score of the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) for detecting major depressive disorder: A meta-analysis

Abstract

Background and purposeThe Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) is a useful inventory for screening major depressive disorder (MDD) in people with epilepsy (PWE). The cutoff score for detecting MDD has been reported with the range of >11 to >16. The aim of this study was to find optimal cutoff score of the NDDI-E for MDD detection by combining the raw data from previous studies. MethodsWe searched MEDLINE, EMBASE, Cochrane Library, Web of Science, and SCOPUS to identify proper studies. Original researches, which tested the accuracy of NDDI-E for MDD detection in adult PWE, were recruited. We included the studies in which MDD was diagnosed by a gold standard structural interview, the Mini International Neuropsychiatric Interview (MINI). In addition, we included only the studies providing enough information for meta-analysis: number of PWE with MDD, number of total PWE, and sensitivity (Se) and specificity (Spe) for each cutoff score. After collecting data from included studies, we performed a diagnostic test accuracy (DTA) meta-analysis using bivariate model. ResultsWe identified 13 validation studies conducted in outpatient epilepsy clinic setting. As summary estimates of test accuracy measures, the Se, Spe, and diagnostic odds ratio (DOR) of NDDI-E for MDD detection were 0.81, 0.84, and 22.48, respectively. The analysis using the multiple thresholds model showed that the NDDI-E score of 13.2 was the best fit for MDD detection. When analyzing only with the seven data sets of the cutoff score >13, the Se, Spe, and DOR were 0.87, 0.80, and 25.72, respectively. ConclusionsThe optimal NDDI-E cutoff score for MDD detection is >13. The information provided by this DTA meta-analysis will be a useful reference for applying NDDI-E in geographic areas where no NDDI-E validation studies have been conducted for their languages.