Background
The ROC curve was first used during World War II for the analysis of radar signals before it was employed in signal detection theory. Following the attack on Pearl Harbor in 1941, the United States army began new research to increase the prediction of correctly detected Japanese aircraft from their radar signals. In medicine, ROC analysis has been extensively used in the evaluation of diagnostic tests. ROC curves are also used extensively in epidemiology and medical research and are frequently mentioned in conjunction with evidence-based medicine.
Clinical use
We tested the accuracy of this Physiological Severity Score/PSS using Receiver Operating Characteristics/ROC analysis in 700 mine- and war injured patients in Iraq and Cambodia, a patient population that had a mean prehospital transit time of 5.5 hours. The study question was: how accurate is PSS in predicting risk of trauma death? We found that the accuracy of PSS in that actual population was high (area under ROC curve 0.93). Interestingly we found that one single risk indicator, respiratory rate after in-field pain relief/RR2, predicted trauma death as well as the comprehensive PSS calculator.
Where the ROC curve comes closest to the upper-left corner is the optimal cut-off for that variable. The graph demonstrates that respiratory rate remaining > 25/minute after pain relief is a critical sign.
Sources and useful sites¶