title: Misclassification of outcome in case-control studies: Methods for sensitivity analysis.
abstract: Case-control studies are potentially open to misclassification of disease outcome which may be unrelated to risk factor exposure (non-differential), thus underestimating associations, or related to risk factor exposure (differential), thus causing more serious bias.We conducted a systematic literature review for methods of adjusting for outcome misclassification in case-control studies. We also applied methods to simulated data with known outcome misclassification to assess performance of these methods. Finally, real data from the Prostate Testing for Cancer and Treatment (ProtecT) randomised controlled trial gauged the usefulness of these methods.Adjustment methods range from recalculating cell frequencies to probabilistic sensitivity modelling and Bayesian models, which incorporate uncertainty in sensitivity and specificity estimates. Simulated data indicated that substantial bias in either direction resulted from differential misclassification. More sophisticated methods, incorporating uncertainty into estimates of misclassification, provided appropriately wide confidence intervals for corrected estimates of risk factor-disease association.Method choice depends on whether the objective is to assess if an observed association can be explained by bias, or to provide a 'corrected' estimate for the primary analysis. Accurate estimation of the degree of misclassification is important for the latter; otherwise further bias may be introduced.
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK Becky.Gilbert@bristol.ac.uk.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Gilbert
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Richard M
authors.initials: RM
authors.lastname: Martin
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Jenny
authors.initials: J
authors.lastname: Donovan
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: J Athene
authors.initials: JA
authors.lastname: Lane
authors.affiliation: Nuffield Department of Surgery, University of Oxford, Oxford, UK.
authors.forename: Freddie
authors.initials: F
authors.lastname: Hamdy
authors.affiliation: Department of Oncology, University of Cambridge, Cambridge, UK.
authors.forename: David E
authors.initials: DE
authors.lastname: Neal
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Metcalfe
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D016022:Case-Control Studies; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis; D012307:Risk Factors; D012680:Sensitivity and Specificity; D035501:Uncertainty
keywords: case–control study; misclassification of outcome; risk factors for prostate cancer