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Reliability of Bayesian probability analysis for predicting coronary artery disease in a veterans hospital.

Abstract：

:To assess the accuracy of Bayesian probability analysis for the prediction of coronary artery disease, post-test probabilities were generated by the application of three Bayesian algorithms to the clinical and noninvasive test results of 199 patients undergoing angiography in a veterans' hospital. All assumed conditional independence but each used different pre-test and conditional probabilities. Two statistical approaches were employed: (1) Sorting of patients in ascending deciles of probability and comparing expected and observed probabilities in each decile. (2) Calculation of normally distributed reliability statistics which do not depend on probability subsets and the comparison of resulting probability distributions using these statistics. Both statistical approaches revealed that the Bayesian algorithms overestimated disease probability when it was high and underestimated it when low. Though all three algorithms were frequently incorrect, they differed significantly in their accuracies, suggesting that errors in Bayesian analysis are caused by factors other than the assumption of independence. The errors may be due to differences in sensitivity and specificity of tests applied in different institutions.

journal_name

J Clin Epidemiol

journal_title

Journal of clinical epidemiology

authors

Detrano R,Guppy KH,Abbassi N,Janosi A,Sandhu S,Froelicher V

doi

10.1016/0895-4356(88)90065-0

subject

Has Abstract

pub_date

1988-01-01 00:00:00

pages

599-605

issue

6

eissn

0895-4356

issn

1878-5921

pii

0895-4356(88)90065-0

journal_volume

41

pub_type

杂志文章

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