title: The sensitivity and specificity of markers for event times.
abstract: The statistical literature on assessing the accuracy of risk factors or disease markers as diagnostic tests deals almost exclusively with settings where the test, Y, is measured concurrently with disease status D. In practice, however, disease status may vary over time and there is often a time lag between when the marker is measured and the occurrence of disease. One example concerns the Framingham risk score (FR-score) as a marker for the future risk of cardiovascular events, events that occur after the score is ascertained. To evaluate such a marker, one needs to take the time lag into account since the predictive accuracy may be higher when the marker is measured closer to the time of disease occurrence. We therefore consider inference for sensitivity and specificity functions that are defined as functions of time. Semiparametric regression models are proposed. Data from a cohort study are used to estimate model parameters. One issue that arises in practice is that event times may be censored. In this research, we extend in several respects the work by Leisenring et al. (1997) that dealt only with parametric models for binary tests and uncensored data. We propose semiparametric models that accommodate continuous tests and censoring. Asymptotic distribution theory for parameter estimates is developed and procedures for making statistical inference are evaluated with simulation studies. We illustrate our methods with data from the Cardiovascular Health Study, relating the FR-score measured at enrollment to subsequent risk of cardiovascular events.
authors.affiliation: Department of Biostatistics, Harvard University, Boston, MA 02115, USA. tcai@hsph.harvard.edu
authors.forename: Tianxi
authors.initials: T
authors.lastname: Cai
authors.forename: Margaret Sullivan
authors.initials: MS
authors.lastname: Pepe
authors.forename: Yingye
authors.initials: Y
authors.lastname: Zheng
authors.forename: Thomas
authors.initials: T
authors.lastname: Lumley
authors.forename: Nancy Swords
authors.initials: NS
authors.lastname: Jenny
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000032:analysis*; D001699:Biometry / Q000379:methods*; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000209:etiology; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013997:Time Factors
chemical_list: D015415:Biomarkers