title: Feasibility of reusing time-matched controls in an overlapping cohort.
abstract: The methods developed for secondary analysis of nested case-control data have been illustrated only in simplified settings in a common cohort and have not found their way into biostatistical practice. This paper demonstrates the feasibility of reusing prior nested case-control data in a realistic setting where a new outcome is available in an overlapping cohort where no new controls were gathered and where all data have been anonymised. Using basic information about the background cohort and sampling criteria, the new cases and prior data are "aligned" to identify the common underlying study base. With this study base, a Kaplan-Meier table of the prior outcome extracts the risk sets required to calculate the weights to assign to the controls to remove the sampling bias. A weighted Cox regression, implemented in standard statistical software, provides unbiased hazard ratios. Using the method to compare cases of contralateral breast cancer to available controls from a prior study of metastases, we identified a multifocal tumor as a risk factor that has not been reported previously. We examine the sensitivity of the method to an imperfect weighting scheme and discuss its merits and pitfalls to provide guidance for its use in medical research studies.
authors.affiliation: 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Bénédicte
authors.initials: B
authors.lastname: Delcoigne
authors.affiliation: 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Niels
authors.initials: N
authors.lastname: Hagenbuch
authors.affiliation: 2 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Maria Ec
authors.initials: ME
authors.lastname: Schelin
authors.affiliation: 3 Department of Mathematics and Statistics, La Trobe University, Victoria, Australia.
authors.forename: Agus
authors.initials: A
authors.lastname: Salim
authors.affiliation: 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.|4 Department of Surgery, University of California, San Francisco, CA, USA.
authors.forename: Linda S
authors.initials: LS
authors.lastname: Lindström
authors.affiliation: 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Jonas
authors.initials: J
authors.lastname: Bergh
authors.affiliation: 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Kamila
authors.initials: K
authors.lastname: Czene
authors.affiliation: 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Marie
authors.initials: M
authors.lastname: Reilly
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000188:drug therapy / Q000473:pathology; D016022:Case-Control Studies; D015331:Cohort Studies; D000078332:Data Analysis; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008875:Middle Aged; D016016:Proportional Hazards Models
keywords: GLM weights; Kaplan–Meier type weights; Nested case-control; cost-efficiency; secondary analysis; weighted Cox regression