The Value of Consecutive Enrollment in Prospective Cohort Studies
Did Participating Patients Present a Diagnostic Dilemma?
Gold Standard Adequacy
Dr. Lisa Calder October 2012
When interpreting likelihood ratios, make sure you not only have a clear sense of how large or small a number will significantly alter your pre-test probability, but also carefully look at the 95%CI to ensure that the lower limits are still within this range of significance.
For diagnostic tests, LR+ increases the post-test probability of a diagnosis and LR- decreases the post-test probability. LR values generally have this impact:
Receiver-Operating Characteristic (ROC) Curves:
ROC curves are used to evaluate diagnostic data by plotting sensitivity versus 1-specificity, with higher areas under the curve (AUC) indicating better ability of the test to discriminate between patients with and without the condition. In this paper, the authors claimed than AUCs of 0.95 (which are very high) meant that the assays were very accurate in identifying MI. Unfortunately, ROC curves are not very usefulness to clinicians and particularly in the ED where we are usually focused on sensitivity or the ability of a test to rule-out a condition (SnOut).
Selection Bias in Prospective Cohort Studies
Screening Tests in the ED
Diagnostic tests in the ED are often used to screen many patients for the possibility of severe illness, e.g. ACS in chest pain, SAH in headache, dementia in the elderly. We typically wish to rule-out a condition and such testing must be highly sensitive (SnOut) but will have false positives, e.g Troponin, CT Head, 3DY. In contrast, specialty services may be more interested in ruling in a condition definitively using tests that are highly specific (SpIn), e.g. coronary angiography, CT angiography of the brain, a battery of cognitive tests.