A study examines the role of different biomarkers in the early diagnosis of acute coronary syndrome. The following receiver-operating characteristic (ROC) curves were obtained for different biomarkers upon participants' initial symptom presentation in the emergency department (the X marks the 99th percentile cutoff point for the corresponding biomarker). Based on the study results and assuming the differences are statistically significant, which of the following 99th percentile cutoff points can best exclude acute coronary syndrome during initial symptom presentation in the emergency department?
A)Biomarker 1
B)Biomarker 2
C)Biomarker 3
D)Biomarker 4

Question

A study examines the role of different biomarkers in the early diagnosis of acute coronary syndrome.  The following receiver-operating characteristic (ROC) curves were obtained for different biomarkers upon participants' initial symptom presentation in the emergency department (the X marks the 99th percentile cutoff point for the corresponding biomarker).  Based on the study results and assuming the differences are statistically significant, which of the following 99th percentile cutoff points can best exclude acute coronary syndrome during initial symptom presentation in the emergency department?
A)Biomarker 1 
B)Biomarker 2 
C)Biomarker 3 
D)Biomarker 4

Quizplus · Accepted Answer

Explanation: Receiver-operating characteristic (ROC) curves plot sensitivity as a function of (1 - specificity) at various cutoff points for a given test; they help determine thresholds given acceptable false positive and false negative fractions. There is a trade-off between sensitivity and specificity at any particular cutoff point. The biomarker 2 cutoff appears to offer the highest sensitivity (highest point on the y-axis). Sensitivity refers to the proportion of patients with the disease who test positive on a given test. It is proportional to true positive rates, so a negative result on a highly sensitive test helps to rule out a disease. Biomarker 2 also appears to have the highest diagnostic accuracy given that the corresponding area under the curve is the largest. Educational objective: Receiver-operating characteristic (ROC) curves plot sensitivity as a function of (1 - specificity) at various cutoff points for a test. A negative result on a highly sensitive test helps to rule out a disease. References: Diagnostic accuracy measures (http://www.ncbi.nlm.nih.gov/pubmed/24135733)

A Study Examines the Role of Different Biomarkers in the Early