Diagnostic uncertainty: dichotomies are not the answer

Abstract

Over two decades ago, Alvan Feinstein, a leading figure in the development and evaluation of diagnostic research methods, argued that the binary ‘positive–negative’ framework used in test accuracy research is not representative of diagnostic decision making in clinical practice.1 In particular, he called for a move away from the dichotomisation of quantitative test scales (tests that are on a continuous or ordinal scale) and advocated an approach that allows for the explicit recognition of an ‘uncertain’ diagnostic outcome. Twenty years on and little progress has been made on this issue; reporting the accuracy of quantitative tests based on a single ‘optimal’ threshold continues to be common practice. Here we present how improving the methods for evaluating quantitative tests would be of greatest benefit to GPs, providing them with a better evidence-based toolkit of strategies for recognising and handling diagnostic uncertainty head-on. Summerton reported that failures relating to diagnosis account for nearly one-third of GP complaints.2 Diagnostic uncertainty is particularly rife in general practice due to a number of obstacles intrinsic to the clinical setting.3 First, the prevalence of serious disease is typically low in a community population, weakening the overall predictive value of diagnostic tests. Secondly, the majority of disease presenting in general practice is commonly in its early stages, when many ‘red flag’ symptoms are yet to evolve and departures from physiological normality are slight. Furthermore, many of the tests used are not disease-specific; they are typically predictive of a symptom that …