The precision–recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases

B Ozenne, F Subtil, D Maucort-Boulch - Journal of clinical epidemiology, 2015 - Elsevier
B Ozenne, F Subtil, D Maucort-Boulch
Journal of clinical epidemiology, 2015Elsevier
Objectives Compare the area under the receiver operating characteristic curve (AUC) vs. the
area under the precision–recall curve (AUPRC) in summarizing the performance of a
diagnostic biomarker according to the disease prevalence. Study Design and Setting A
simulation study was performed considering different sizes of diseased and nondiseased
groups. Values of a biomarker were sampled with various variances and differences in
mean values between the two groups. The AUCs and the AUPRCs were examined …
Objectives
Compare the area under the receiver operating characteristic curve (AUC) vs. the area under the precision–recall curve (AUPRC) in summarizing the performance of a diagnostic biomarker according to the disease prevalence.
Study Design and Setting
A simulation study was performed considering different sizes of diseased and nondiseased groups. Values of a biomarker were sampled with various variances and differences in mean values between the two groups. The AUCs and the AUPRCs were examined regarding their agreement and vs. the positive predictive value (PPV) and the negative predictive value (NPV) of the biomarker.
Results
With a disease prevalence of 50%, the AUC and the AUPRC showed high correlations with the PPV and the NPV (ρ > 0.95). With a prevalence of 1%, small PPV and AUPRC values (<0.2) but high AUC values (>0.9) were found. The AUPRC reflected better than the AUC the discriminant ability of the biomarker; it had a higher correlation with the PPV (ρ = 0.995 vs. 0.724; P < 0.001).
Conclusion
In uncommon and rare diseases, the AUPRC should be preferred to the AUC because it summarizes better the performance of a biomarker.
Elsevier
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