Estimating the population impact of preventive interventions from randomized trials.

Growing concern about the limited generalizability of trials of preventive interventions has led to several proposals concerning the design, reporting, and interpretation of such trials. This paper presents an epidemiologic framework that highlights three key determinants of population impact of man...

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Published in:American Journal of Preventive Medicine Vol. 40; no. 2; pp. 191 - 199
Main Authors: Koepsell TD, Zatzick DF, Rivara FP, Koepsell, Thomas D, Zatzick, Douglas F, Rivara, Frederick P
Format: research Journal Article
Published: Elsevier B.V. Feb2011
Online Access:View this record in EBSCOhost
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      dt: Feb2011
      vid: 40
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      pub: Elsevier B.V.
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        atl: Estimating the population impact of preventive interventions from randomized trials.
      aug:
        au:
          Koepsell TD
          Zatzick DF
          Rivara FP
          Koepsell, Thomas D
          Zatzick, Douglas F
          Rivara, Frederick P
        affil: Harborview Injury Prevention and Research Center, University of Washington, Seattle, WA, USA
      sug:
        subj:
          Epidemiological Research
          Preventive Health Care
          Clinical Trials
          Data Analysis, Statistical
          Human
          Models, Theoretical
      ab: Growing concern about the limited generalizability of trials of preventive interventions has led to several proposals concerning the design, reporting, and interpretation of such trials. This paper presents an epidemiologic framework that highlights three key determinants of population impact of many prevention programs: the proportion of the population at risk who would be candidates for a generic intervention in routine use, the proportion of those candidates who are actually intervened on through a specific program, and the reduction in incidence produced by that program among recipients. It then describes how the design of a prevention trial relates to estimating these quantities. Implications of the framework include the following: (1) reach is an attribute of a program, whereas external validity is an attribute of a trial, and the two should not be conflated; (2) specification of a defined target population at risk is essential in the long run and merits greater emphasis in the planning and interpretation of prevention trials; (3) with due attention to sampling frame and sampling method, the process of subject recruitment for a trial can yield key information about quantities that are important for assessing its potential population impact; and (4) exclusions during subject recruitment can be conceptually separated into intervention-driven, program-driven, and trial-design-driven exclusions, which have quite different implications for trial interpretation and for estimating population impact of the intervention studied.
      pubtype: Academic Journal
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        Journal Article
      ougenre: Article
    language: English
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