‘Likelihood to Be Diagnosed Or misdiagnosed’: Application to Meta-Analytic Data for Cognitive Screening Instruments

Abstract

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.

Keywords: :

• cognitive screening instruments
• dementia
• diagnosis
• likelihood to be diagnosed or misdiagnosed
• meta-analysis
• mild cognitive impairment

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.