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Methods for Assessing Improvement in Specificity when a Biomarker is Combined with a Standard Screening Test
Pamela A Shaw1, Margaret S Pepe, Todd A Alonzo
1Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892.
Statistics in Biopharmaceutical Research
|January 8, 2010
Summary
New methods evaluate combination diagnostic tests using relative true and false positive rates. This approach enhances specificity for screening tests, reducing false positives in biomarker discovery for diseases like breast and prostate cancer.
Area of Science:
- Biostatistics
- Diagnostic Test Evaluation
- Biomarker Research
Background:
- High demand exists for biomarkers to improve established screening tests by reducing false positive rates.
- Combination tests require positivity on both a biomarker and a standard screening test.
Purpose of the Study:
- To present methods for evaluating the diagnostic performance of combination tests.
- To measure the impact of adding a biomarker test on sensitivity and specificity compared to standard tests.
Main Methods:
- Utilizing relative true and false positive rates, interpreted as conditional probabilities.
- Introducing the relative receiver operating characteristic (rROC) curve for continuous biomarker tests.
- Applying existing ROC methodology for inference on rROC curves.
Main Results:
- The methods allow for the evaluation of diagnostic performance of combined biomarker and screening tests.
- The rROC curve effectively visualizes the trade-off between sensitivity and specificity as biomarker thresholds vary.
- Demonstrated utility in breast and prostate cancer biomarker studies.
Conclusions:
- The proposed statistical methods provide a robust framework for assessing combination diagnostic tests.
- The rROC curve is a valuable tool for understanding continuous biomarker performance in conjunction with screening tests.
- These methods can aid in the development of more accurate and specific disease screening protocols.
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