Between a ROC and a hard place: Teaching prevalence plots to understand real world biomarker performance in the clinic.
Pharm Stat
; 18(6): 632-635, 2019 11.
Article
in En
| MEDLINE
| ID: mdl-31231892
ABSTRACT
The Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) of the ROC curve are widely used in discovery to compare the performance of diagnostic and prognostic assays. The ROC curve has the advantage that it is independent of disease prevalence. However, in this note, we remind scientists and clinicians that the performance of an assay upon translation to the clinic is critically dependent upon that very same prevalence. Without an understanding of prevalence in the test population, even robust bioassays with excellent ROC characteristics may perform poorly in the clinic. While the exact prevalence in the target population is not always known, simple plots of candidate assay performance as a function of prevalence rate give a better understanding of the likely real-world performance and a greater understanding of the likely impact of variation in that prevalence on translation to the clinic.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Biological Assay
/
Biomarkers
/
Diagnostic Tests, Routine
Type of study:
Prevalence_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Pharm Stat
Journal subject:
FARMACOLOGIA
Year:
2019
Type:
Article
Affiliation country:
United kingdom