Evidence Based Emergency Medicine Part 2: Positive and negative predictive values of diagnostic tests

Introduction: n volume 3, number 2, pages 48-49, we explained some screening characteristics of a diagnostic test in an educational manuscript entitled “Simple definition and calculation of accuracy, sensitivity and specificity" (1). The present article was aimed to review other screening performance characteristics including positive and negative predictive values (PPV and NPV). PPV and NPV are true positive and true negative results of a diagnostic test, respectively (2). In other words, if a subject receives a certain diagnosis by a test, predictive values describe how likely it is for the diagnosis to be correct Definitions: Patient: positive for disease Healthy: negative for disease True positive (TP)= the number of cases correctly identified as patient False positive (FP) = the number of cases incorrectly identified as patient True negative (TN) = the number of cases correctly identified as healthy False negative (FN) = the number of cases incorrectly identified as healthy Positive predictive value: Positive predictive value is the proportion of cases giving positive test results who are already patients (3). It is the ratio of patients truly diagnosed as positive to all those who had positive test results (including healthy subjects who were incorrectly diagnosed as patient). This characteristic can predict how likely it is for someone to truly be patient, in case of a positive test result.