Work

Testing the incremental predictive accuracy of new markers

Year: 2013

Type: article

Abstract: BACKGROUND: It has become commonplace to use receiver operating curve (ROC) methodology to evaluate the incremental predictive accuracy of new markers in the presence of existing predictors. However, concerns have been raised about the validity of this practice. We have evaluated this issue in detail. RESULTS: Simulations have been used that show clearly that use of risk predictors from nested models as data in subsequent tests comparing areas under the ROC curves of the models leads to grossly invalid inferences. Careful examination of the issue reveals two major problems: (1) the data elements are strongly correlated from case to case and (2) the model that includes the additional marker has a tendency to interpret predictive contributions as positive information regardless of whether observed effect of the marker is negative or positive. Both of these phenomena lead to profound bias in the test. CONCLUSIONS: We recommend strongly against the use of ROC methods derived from risk predictors from nested regression models to test the incremental information of a new marker.

Source: Clinical Trials

DOI: 10.1177/1740774513496490

Authors: Colin B Begg, Mithat Gonen, Venkatraman E Seshan

Institution: Memorial Sloan Kettering Cancer Center

Language: English

Topic: Statistical Methods in Epidemiology

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Cancer Institute