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. 2018 Jul 27;40(4):409-413.
doi: 10.1093/ejo/cjx084.

Intention to Treat (ITT) Analysis as Reported in Orthodontic Randomized Controlled Trials-Evaluations of Methodology and Recommendations for the Accurate Use of ITT Analysis and Handling Dropouts

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Intention to Treat (ITT) Analysis as Reported in Orthodontic Randomized Controlled Trials-Evaluations of Methodology and Recommendations for the Accurate Use of ITT Analysis and Handling Dropouts

Lars Bondemark et al. Eur J Orthod. .

Abstract

Objective: To systematically evaluate in five orthodontic journals how many randomized controlled trials (RCTs) use intention to treat (ITT) analysis and to assess the methodological quality of the ITT analysis, and finally, to demonstrate in an academic way how outcomes can be affected when not implementing the ITT analysis.

Material and methods: A search of the database, Medline, was performed via PubMed for publication type 'randomized controlled trial' published for each journal between 1 January 2013 and 30 April 2017. The five orthodontic journals assessed were the American Journal of Orthodontics and Dentofacial Orthopedics, Angle Orthodontics, European Journal of Orthodontics, Journal of Orthodontics, and Orthodontics and Craniofacial Research. Two independent reviewers assessed each RCT to determine whether the trial reported an ITT or not or if a per-protocol analysis was accomplished.

Results: The initial search generated 137 possible trials. After applying the inclusion and exclusion criteria, 90 RCTs were included and assessed. Seventeen out of 90 RCTs (18.9%) either reported an ITT analysis in the text and/or supported the ITT by flow diagrams or tables. However, six RCTs applied and reported the ITT analysis correctly, while the majority performed a per-protocol analysis instead.

Conclusions: Nearly all the trials that applied the ITT analysis incorrectly analysed the results using a per-protocol analysis, and thus, overestimating the results and/or having a reduced sample size which then could produce a diminished statistical power.

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