'Likelihood to be diagnosed or misdiagnosed': application to meta-analytic data for cognitive screening instruments

Aim: To extend use of the recently described 'likelihood to be diagnosed or misdiagnosed' (LDM) metric for test accuracy studies through application to recent meta-analytic data of commonly used cognitive screening instruments. Methods: Raw data (true positives and negatives, false positives and negatives) were extracted from meta-analyses (minimum 5 studies or 1000 patients), from which LDM was calculated. LDM values were compared with those previously reported for single test accuracy studies. Results: LDM values for diagnosis of dementia ranged from around two to seven, and for diagnosis of mild cognitive impairment from two to three. LDM values based on meta-analytic data were larger than those reported for individual studies. Conclusion: LDM is an easily calculated and potentially useful unitary, global metric for test accuracy studies.