Number Needed to Diagnose, Predict, or Misdiagnose: Useful Metrics for Non-Canonical Signs of Cognitive Status?

Abstract

Background/Aims: “Number needed to” metrics may hold more intuitive appeal for clinicians than standard diagnostic accuracy measures. The aim of this study was to calculate “number needed to diagnose” (NND), “number needed to predict” (NNP), and “number needed to misdiagnose” (NNM) for neurological signs of possible value in assessing cognitive status. Methods: Data sets from pragmatic diagnostic accuracy studies examining easily observed and dichotomised neurological signs (“attended alone” sign, “attended with” sign, head turning sign, applause sign, la maladie du petit papier) were analysed to calculate the NND, NNP, and NNM. Results: All measures of discrimination showed broad ranges. The range of NND and NNP suggested that these signs were, with a single exception, of value for correctly diagnosing or predicting cognitive status (presence or absence of cognitive impairment) when between 2 and 4 patients were examined. However, NNM showed similar values (range 1–5 patients) suggesting risk of misdiagnosis. Conclusion: NND, NNP, and NNM may be useful, intuitive, metrics in assessing the utility of diagnostic tests in day-to-day clinical practice. A ratio of NNM to either NND or NNP, termed the likelihood to diagnose or misdiagnose, may clarify the utility or inutility of diagnostic tests.