Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic, Prognostic, or Screening Marker

A marker strongly associated with outcome (or disease) is often assumed to be effective for classifying persons according to their current or future outcome. However, for this assumption to be true, the associated odds ratio must be of a magnitude rarely seen in epidemiologic studies. In this paper,...

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Bibliographic Details
Published in:American journal of epidemiology 2004-05, Vol.159 (9), p.882-890
Main Authors: Pepe, Margaret Sullivan, Janes, Holly, Longton, Gary, Leisenring, Wendy, Newcomb, Polly
Format: Article
Language:English
Subjects:
Analysis. Health state
Biological and medical sciences
biological markers
Biomarkers
Case-Control Studies
Classification
Data Interpretation, Statistical
diagnostic test
Diagnostic tests
Discriminant Analysis
Epidemiologic Methods
Epidemiology
False Positive Reactions
false-positive fraction
FPF
General aspects
Humans
Logistic Models
logistic regression
Mass Screening - methods
Mass Screening - standards
Medical sciences
Medical screening
Odds Ratio
Predictive Value of Tests
Prognosis
Public health. Hygiene
Public health. Hygiene-occupational medicine
Ratios
receiver operating characteristic
Reproducibility of Results
Risk Factors
ROC
ROC Curve
screening test
TPF
true-positive fraction
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Summary:A marker strongly associated with outcome (or disease) is often assumed to be effective for classifying persons according to their current or future outcome. However, for this assumption to be true, the associated odds ratio must be of a magnitude rarely seen in epidemiologic studies. In this paper, an illustration of the relation between odds ratios and receiver operating characteristic curves shows, for example, that a marker with an odds ratio of as high as 3 is in fact a very poor classification tool. If a marker identifies 10% of controls as positive (false positives) and has an odds ratio of 3, then it will correctly identify only 25% of cases as positive (true positives). The authors illustrate that a single measure of association such as an odds ratio does not meaningfully describe a marker’s ability to classify subjects. Appropriate statistical methods for assessing and reporting the classification power of a marker are described. In addition, the serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated.
ISSN:0002-9262
1476-6256
0002-9262
DOI:10.1093/aje/kwh101