The precision: recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases
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The precision : recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases. / Ozenne, Brice; Subtil, Fabien; Maucort-Boulch, Delphine.
I: Journal of Clinical Epidemiology, Bind 68, Nr. 8, 08.2015, s. 855-859.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - The precision
T2 - recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases
AU - Ozenne, Brice
AU - Subtil, Fabien
AU - Maucort-Boulch, Delphine
N1 - Copyright © 2015 Elsevier Inc. All rights reserved.
PY - 2015/8
Y1 - 2015/8
N2 - 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.
AB - 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.
KW - Area Under Curve
KW - Biomarkers
KW - Humans
KW - Predictive Value of Tests
KW - Prevalence
KW - ROC Curve
KW - Rare Diseases
KW - Sensitivity and Specificity
KW - Journal Article
U2 - 10.1016/j.jclinepi.2015.02.010
DO - 10.1016/j.jclinepi.2015.02.010
M3 - Journal article
C2 - 25881487
VL - 68
SP - 855
EP - 859
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
SN - 0895-4356
IS - 8
ER -
ID: 167853237