Potential impact on estimated treatment effects of information lost to follow-up in randomised controlled trials (LOST-IT): systematic review
Open accessAbstract
OBJECTIVE: To assess the reporting, extent, and handling of loss to follow-up and its potential impact on the estimates of the effect of treatment in randomised controlled trials. DESIGN: Systematic review. We calculated the percentage of trials for which the relative risk would no longer be significant under a number of assumptions about the outcomes of participants lost to follow-up. DATA SOURCES: Medline search of five top general medical journals, 2005-07. ELIGIBILITY CRITERIA: Randomised controlled trials that reported a significant binary primary patient important outcome. RESULTS: Of the 235 eligible reports identified, 31 (13%) did not report whether or not loss to follow-up occurred. In reports that did give the relevant information, the median percentage of participants lost to follow-up was 6% (interquartile range 2-14%). The method by which loss to follow-up was handled was unclear in 37 studies (19%); the most commonly used method was survival analysis (66, 35%). When we varied assumptions about loss to follow-up, results of 19% of trials were no longer significant if we assumed no participants lost to follow-up had the event of interest, 17% if we assumed that all participants lost to follow-up had the event, and 58% if we assumed a worst case scenario (all participants lost to follow-up in the treatment group and none of those in the control group had the event). Under more plausible assumptions, in which the incidence of events in those lost to follow-up relative to those followed-up is higher in the intervention than control group, results of 0% to 33% trials were no longer significant. CONCLUSION: Plausible assumptions regarding outcomes of patients lost to follow-up could change the interpretation of results of randomised controlled trials published in top medical journals.
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Most randomised trials encounter some degree of missing outcome and covariate data.
“Most randomised trials encounter some degree of missing outcome and covariate data.422 426”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [426]
Missing data negatively affect trials by reducing statistical power and introducing potential bias.
“Missing data negatively affect trials by reducing statistical power and introducing potential bias.426”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [426]
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- Authors
- Akl, E. A., Briel, M., You, J. J., Sun, X., Johnston, B. C., Busse, J. W., Mulla, S., Lamontagne, F., Bassler, D., Vera, C., Alshurafa, M., Katsios, C. M., Zhou, Q., Cukierman-Yaffe, T., Gangji, A., Mills, E. J., Walter, S. D., Cook, D. J., Schunemann, H. J., Altman, D. G., & Guyatt, G. H.
- Affiliations
- University at Buffalo, State University of New York (US)
- University of Basel (CH)
- McMaster University (CA)
- Kaiser Permanente (US)
- Hospital for Sick Children (CA)
- Institute for Work & Health (CA)
- Université de Sherbrooke (CA)
- University Children's Hospital Tübingen (DE)
- Pontificia Universidad Católica de Chile (CL)
- University of Ottawa (CA)
- University of Oxford (GB)
- Corresponding author
- Akl, E. A.
- ORCID
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2012-05-18
- Volume
- 344
- Issue
- may18 1
- Pages
- e2809-e2809
- ISSN
- 1756-1833 (ISSN-L)
- OpenAlex
- W1973748105
- Cited by
- 350
- References
- 40
- Citations by year
- 2026: 16 · 2025: 33 · 2024: 24 · 2023: 23 · 2022: 31 · 2021: 32 · 2020: 39 · 2019: 25 · 2018: 23 · 2017: 24 · 2016: 24 · 2015: 26 · 2014: 13 · 2013: 13 · 2012: 4
- FWCI
- 2.74
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- BMJ (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Pfizer
- Canadian Society of Nephrology
- Kidney Foundation of Canada
- Ontario Ministry of Health and Long-Term Care
- Cancer Research UK
- National Natural Science Foundation of China
- Hospital for Sick Children
- Canadian Institutes of Health Research
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- loss to follow-up, randomized controlled trials, treatment effect estimation, survival analysis, relative risk, binary outcomes
- MeSH terms
- Data Interpretation, Statistical, Follow-Up Studies, Humans, Patient Dropouts, Risk, Survival Analysis, Randomized Controlled Trials as Topic, Treatment Outcome, Lost to Follow-Up
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