Biostatistics 3:477-492 (2002)
© 2002 Oxford University Press
Prospective studies of diagnostic test accuracy when disease prevalence is low
Department of Biostatistics and Epidemiology, Wb4, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA nobuchow{at}bio.ri.ccf.org
Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, RG 4101, 1050 Wishard Blvd, Indianapolis, IN 46202, USA
*To whom correspondence should be addressed
Prospective studies of diagnostic test accuracy have important advantages over retrospective designs. Yet, when the disease being detected by the diagnostic test(s) has a low prevalence rate, a prospective design can require an enormous sample of patients. We consider two strategies to reduce the costs of prospective studies of binary diagnostic tests: stratification and two-phase sampling. Utilizing neither, one, or both of these strategies provides us with four study design options: (1) the conventional design involving a simple random sample (SRS) of patients from the clinical population; (2) a stratified design where patients from higher-prevalence subpopulations are more heavily sampled; (3) a simple two-phase design using a SRS in the first phase and selection for the second phase based on the test results from the first; and (4) a two-phase design with stratification in the first phase. We describe estimators for sensitivity and specificity and their variances for each design, along with sample size estimation. We offer some recommendations for choosing among the various designs. We illustrate the study designs with two examples.
Keywords: Diagnostic tests; Prospective; Sample size; Sensitivity; Specificity; Stratification; Two-phase sampling