title: New models for large prospective studies: is there a risk of throwing out the baby with the bathwater?
abstract: Manolio et al. (Am J Epidemiol. 2012;175:859-866) proposed that large cohort studies adopt novel models using "temporary assessment centers" to enroll up to a million participants to answer research questions about rare diseases and "harmonize" clinical endpoints collected from administrative records. Extreme selection bias, we are told, will not harm internal validity, and "process expertise to maximize efficiency of high-throughput operations is as important as scientific rigor" (p. 861). In this article, we describe serious deficiencies in this model as applied to the United States. Key points include: 1) the need for more, not less, specification of disease endpoints; 2) the limited utility of data collected from existing administrative and clinical databases; and 3) the value of university-based centers in providing scientific expertise and achieving high recruitment and retention rates through community and healthcare provider engagement. Careful definition of sampling frames and high response rates are crucial to avoid bias and ensure inclusion of important subpopulations, especially the medically underserved. Prospective hypotheses are essential to refine study design, determine sample size, develop pertinent data collection protocols, and achieve alliances with participants and communities. It is premature to reject the strengths of large national cohort studies in favor of a new model for which evidence of efficiency is insufficient.
authors.affiliation: Center for Perinatal, Pediatric and Environmental Epidemiology, Yale University School of Public Health, One Church Street, 6th Floor, New Haven, CT 06510, USA. michael.bracken@yale.edu
authors.forename: Michael B
authors.initials: MB
authors.lastname: Bracken
authors.forename: Dean
authors.initials: D
authors.lastname: Baker
authors.forename: Jane A
authors.initials: JA
authors.lastname: Cauley
authors.forename: Christina
authors.initials: C
authors.lastname: Chambers
authors.forename: Jennifer
authors.initials: J
authors.lastname: Culhane
authors.forename: Dana
authors.initials: D
authors.lastname: Dabelea
authors.forename: Dorr
authors.initials: D
authors.lastname: Dearborn
authors.forename: Carolyn D
authors.initials: CD
authors.lastname: Drews-Botsch
authors.forename: Donald J
authors.initials: DJ
authors.lastname: Dudley
authors.forename: Maureen
authors.initials: M
authors.lastname: Durkin
authors.forename: Barbara
authors.initials: B
authors.lastname: Entwisle
authors.forename: Louise
authors.initials: L
authors.lastname: Flick
authors.forename: Daniel
authors.initials: D
authors.lastname: Hale
authors.forename: Jane
authors.initials: J
authors.lastname: Holl
authors.forename: Melbourne
authors.initials: M
authors.lastname: Hovell
authors.forename: Mark
authors.initials: M
authors.lastname: Hudak
authors.forename: Nigel
authors.initials: N
authors.lastname: Paneth
authors.forename: Bonny
authors.initials: B
authors.lastname: Specker
authors.forename: Mari
authors.initials: M
authors.lastname: Wilhelm
authors.forename: Sharon
authors.initials: S
authors.lastname: Wyatt
mesh_terms: D006801:Humans; D011446:Prospective Studies