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

Authors

Elie A. Akl, State University of New York at BuffaloFollow
Matthias Briel, McMaster UniversityFollow
John J. You, McMaster UniversityFollow
Francois Lamontagne, McMaster UniversityFollow
Azim Gangji, McMaster UniversityFollow
Tali Cukierman-Yaffe, Gertner Institute for Epidemiology & Health Policy Research, Sheba Medical Center, Sackler School of Medicine, Tel -Aviv UniversityFollow
Mohamad Alshurafa, McMaster UniversityFollow
Xin Sun, McMaster UniversityFollow
Kara A. Nerenberg, McMaster UniversityFollow
Bradley C. Johnston, University of AlbertaFollow
Claudio Vera, Pontificia Universidad Católica de ChileFollow
Edward J. Mills, Centre for International Health and Human Rights StudiesFollow
Dirk Bassler, University Children's Hospital TuebingenFollow
Arturo Salazar, Wayne State UniversityFollow
Neera Bhatnagar, Health Sciences Library, McMaster UniversityFollow
Jason W. Busse, McMaster UniversityFollow
Zara Khalid, McMaster UniversityFollow
SD Walter, McMaster UniversityFollow
Deborah J. Cook, McMaster UniversityFollow
Holger J. Schünemann, McMaster UniversityFollow
Douglas G. Altman, Centre for Statistics in Medicine, University of OxfordFollow
Gordon H. Guyatt, McMaster UniversityFollow

Document Type

Article

Abstract

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.

Recommended Citation

Akl et al. Trials 2009, 10:40
doi:10.1186/1745-6215-10-40