Comparing the predictive values of diagnostic tests: sample size and analysis for paired study designs.
BACKGROUND
Although statistical methodology is well developed for comparing diagnostic tests in terms of their sensitivities and specificities, comparative inference about predictive values is not.


OBJECTIVE
In this paper we consider the design and analysis of studies comparing the positive and negative predictive values of two diagnostic tests that are measured on all subjects.


METHODS
We focus on comparing tests using the relative positive and negative predictive values. We discuss directly estimating these quantities from the data and derive analytic variance expressions. Sample size formulas for study design ensue.


RESULTS
We analyze data on patients with cystic fibrosis to illustrate the methodology. This approach is compared and contrasted with an existing regression framework that can also be used for similar analysis purposes and yields similar results.


CONCLUSIONS
We have developed a new approach for comparing the predictive values of two tests that gives rise to sample size formulas for study design.
Moskowitz
Chaya S
CS
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, USA. moskowc1@mskcc.org
Pepe
Margaret S
MS
D001699:Biometry / Q000379:methods; D003550:Cystic Fibrosis / Q000382:microbiology*; D003955:Diagnostic Tests, Routine; D006801:Humans; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012107:Research Design; D018401:Sample Size; D012680:Sensitivity and Specificity