Affirmative Actions
- 1 February 1991
- journal article
- Published by SAGE Publications in Medical Decision Making
- Vol. 11 (1) , 48-56
- https://doi.org/10.1177/0272989x9101100109
Abstract
Clinical estimates of test efficacy can be distorted by the differential referral of positive and negative test responders for outcome verification. Accordingly, a series of computer simu lations was performed to quantify the effects of various degrees of this selection bias on the observed true-positive rate, false-positive rate, and discriminant accuracy of a hypothetical test. The error in observed true- and false-positive rates was positive with respect to diag nosis, and negative with respect to prognosis. The magnitude of error was highly correlated with the magnitude of bias associated with the test response (primary selection bias), but not with the magnitude of bias associated with additional independent factors (secondary selection bias). Mathematical correction for preferential referral based on the test response using a previously published algorithm completely removed the correlation with primary selection bias for both diagnosis and prognosis. Although a significant correlation with sec ondary selection bias persisted at intermediate base rates, its magnitude was small. Dis criminant accuracy was assessed in terms of area under a receiver operating characteristic (ROC) curve. Biased values of true- and false-positive rates were distributed along the curve defined by the actual true- and false-positive rates of the test for both diagnosis and prognosis. As a result, the areas under ROC curves calculated from biased true- and false-positive rates were within 2% of the areas calculated from the actual rates. Only when the primary and secondary observations were independent with respect to one outcome and dependent with respect to the other outcome did a systematic error appear in ROC area. These data indicate that: 1) selection bias significantly distorts the determination of diagnostic and prog nostic test accuracy in directionally opposite ways; 2) the distortion can be partially offset by a previously published mathematical algorithm; and 3) the area under an ROC curve is insensitive both to the primary bias associated with the test response itself and to the secondary bias associated with concomitant clinical information under a variety of circum stances. Key words: diagnosis; prognosis; referral bias; ROC curves; sensitivity; specificity; verification bias; workup bias. (Med Decis Making 1991;11:48-56)Keywords
This publication has 17 references indexed in Scilit:
- Effect of exercise level on the ability of thallium-201 tomographic imaging in detecting coronary artery disease: Analysis of 461 patientsJournal of the American College of Cardiology, 1989
- Comparative accuracy of clinical tests for diagnosis and prognosis of coronary artery diseaseThe American Journal of Cardiology, 1988
- ROC SteadyMedical Decision Making, 1987
- Response to ROC SteadyMedical Decision Making, 1987
- Sensitivity and specificity of tests: Can the “silent majority” speak?The American Journal of Cardiology, 1987
- The Effects of Disease Verification and Referral on the Relationship Between Symptoms and DiseasesMedical Decision Making, 1987
- Reverend Bayes' silent majorityThe American Journal of Cardiology, 1986
- A model for assessing the sensitivity and specificity of tests subject to selection biasJournal of Chronic Diseases, 1986
- The Declining Specificity of Exercise Radionuclide VentriculographyNew England Journal of Medicine, 1983
- Problems of Spectrum and Bias in Evaluating the Efficacy of Diagnostic TestsNew England Journal of Medicine, 1978