Likelihood ratios for continuous test results--making the clinicians' job easier or harder?

Clinicians' paradigms for considering diagnostic test results require decisions based on the actual test value. However, when the test result is reported on a continuous scale each possible outcome may not result in unique actions. To simplify decision making, clinicians often break down the continuous scale into dichotomous or ordered outcomes. Likelihood ratios, reported with the test outcome, help summarize the impact of diagnostic tests. Although commonly applied to dichotomous outcomes, likelihood ratios can also be applied to ordinal or continuous results. This application allows investigators to consider the effect of clinically simplifying continuous data into dichotomous or ordinal categories. The parameters of a simple logistic regression equation summarize continuous likelihood ratios, evaluate covariates, generate likelihood ratio lines, and help assess the statistical significance of more complex models. Having visually inspected likelihood ratio lines and considered statistical differences, the investigator should choose the test report format that best accounts the realities driving clinical decisions.

Duke Scholars

Author David Lee Simel Medicine, General Internal Medicine

Author David Bruce Matchar Medicine, General Internal Medicine