A systematic review finds variable use of the intention-to-treat principle in musculoskeletal randomized controlled trials with missing data

J Clin Epidemiol. 2015 Jan;68(1):15-24. doi: 10.1016/j.jclinepi.2014.09.002. Epub 2014 Oct 7.


Objectives: In randomized trials, the primary analysis should be consistent with the intention-to-treat (ITT) principle and should address missing data appropriately to draw valid inferences. This review focuses on current practices relating to the ITT principle and methods to handle missing data in the major musculoskeletal journals.

Study design and setting: A systematic review of randomized trials published in 2010 and 2011 in five musculoskeletal journals was performed.

Results: We reviewed 91 trials: 38% performed a full ITT analysis (analyzing outcome data for all randomized participants) and 31% performed a partial ITT analysis (excluding participants with no follow-up data). The overall median dropout was 12%; 60% of trials had more than 10% dropouts, and 32% of trials had more than 20% dropouts. Among those that performed an ITT analysis, the majority adopted a form of single imputation; last observation carried forward was the designated approach in most cases. Mixed models for repeated measures and/or multiple imputations were limited to eight trials.

Conclusion: It appears that many trials reporting missing data are inappropriately analyzed and may therefore be prone to biased estimates and invalid inferences.

Keywords: Dropout; Intention-to-treat; Missing data; Musculoskeletal conditions; Randomized controlled trial; Sensitivity analysis; Systematic review.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Data Interpretation, Statistical
  • Humans
  • Intention to Treat Analysis / methods*
  • Intention to Treat Analysis / statistics & numerical data
  • Musculoskeletal Diseases / therapy
  • Patient Dropouts / statistics & numerical data*
  • Publications / standards
  • Randomized Controlled Trials as Topic / methods*
  • Randomized Controlled Trials as Topic / statistics & numerical data