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LOST to follow-up Information in Trials (LOST-IT): A protocol on the potential impact

  • Elie A. Akl
  • , Matthias Briel
  • , John J. You
  • , Francois Lamontagne
  • , Azim Gangji
  • , Tali Cukierman-Yaffe
  • , Mohamad Alshurafa
  • , Xin Sun
  • , Kara A. Nerenberg
  • , Bradley C. Johnston
  • , Claudio Vera
  • , Edward J. Mills
  • , Dirk Bassler
  • , Arturo Salazar
  • , Neera Bhatnagar
  • , Jason W. Busse
  • , Zara Khalid
  • , S. D. Walter
  • , Deborah J. Cook
  • , Holger J. Schünemann
  • Douglas G. Altman, Gordon H. Guyatt
  • SUNY Buffalo
  • McMaster University
  • University of Basel
  • Université de Sherbrooke
  • Tel Aviv University
  • Sichuan University
  • University of Alberta
  • Pontificia Universidad Católica de Chile
  • Centre for International Health and Human Rights Studies
  • University of Tübingen
  • Wayne State University
  • Institute for Work and Health
  • University of Oxford

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

Abstract

Background: Incomplete ascertainment of outcomes in randomized controlled trials (RCTs) is likely to bias final study results if reasons for unavailability of patient data are associated with the outcome of interest. The primary objective of this study is to assess the potential impact of loss to follow-up on the estimates of treatment effect. The secondary objectives are to describe, for published RCTs, (1) the reporting of loss to follow-up information, (2) the analytic methods used for handling loss to follow-up information, and (3) the extent of reported loss to follow-up. Methods: We will conduct a systematic review of reports of RCTs recently published in five top general medical journals. Eligible RCTs will demonstrate statistically significant effect estimates with respect to primary outcomes that are patient-important and expressed as binary data. Teams of 2 reviewers will independently determine eligibility and extract relevant information from each eligible trial using standardized, pre-piloted forms. To assess the potential impact of loss to follow-up on the estimates of treatment effect we will, for varying assumptions about the outcomes of participants lost to follow-up (LTFU), calculate (1) the percentage of RCTs that lose statistical significance and (2) the mean change in effect estimate across RCTs. The different assumptions we will test are the following: (1) none of the LTFU participants had the event; (2) all LTFU participants had the event; (3) all LTFU participants in the treatment group had the event; none of those in the control group had it (worst case scenario); (4) the event incidence among LTFU participants (relative to observed participants) increased, with a higher relative increase in the intervention group; and (5) the event incidence among LTFU participants (relative to observed participants) increased in the intervention group and decreased in the control group. Discussion: We aim to make our objectives and methods transparent. The results of this study may have important implications for both clinical trialists and users of the medical literature.

Original languageEnglish
Article number40
JournalCurrent Controlled Trials in Cardiovascular Medicine
Volume10
DOIs
StatePublished - Jun 11 2009

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