Search PubMedSearch

PubMed · 7539300

Evaluating multiple diagnostic tests with partial verification.

Abstract

To evaluate diagnostic tests, one would ideally like to verify, for example, with a biopsy, the disease state of all subjects in a study. Often, however, no all subjects are verified. Previous methods for evaluation assume that the decision to verify depends only on recorded variables. Sometimes, particularly if the disease process is not well understood, the decision to verify may also depend on unrecorded variables related to disease. We propose a method to estimate the true- and false-positive rates of multiple tests while adjusting for the effect, on the decision to verify, of unrecorded variables related to disease. To put the estimates into a more usable form, we develop a simple algorithm for creating a receiver-operating curve which maximizes the true-positive rate, given the false-positive rate. We apply the methodology to data on the early detection of prostate cancer using ultrasonography, digital rectal exam, and prostate specific antigen.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

S G Baker. 1995. Evaluating multiple diagnostic tests with partial verification.. https://pubmed.ncbi.nlm.nih.gov/7539300/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Biostatistical concepts and methods in the legal setting.

Biostatistical concepts and methods apply to various problems arising in actual U.S. legal cases. These involve: measures of association, assessing the potential effect of omitted variables and the Peters-Belson approach to regression. In particular, we present the inapplicability of Fisher's exact test in the case where the process determining the marginal sample sizes is not independent of the hypothesis under study by the 2 x 2 table. We adapt Cornfield's procedure to assess whether the omission of another factor could have contributed to a non-significant finding of the effect of the major factor under investigation. Finally, we demonstrate the relevance and utility of the Peters-Belson regression methodology to equal pay and promotion cases.

Biometry