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Twisk JW, Rijnhart JJ, Hoekstra T, et al. Intention-to-treat analysis when only a baseline value is available. Contemp Clin Trials Commun. 2020;20:100684doi: 10.1016/j.conctc.2020.100684.
Twisk, J. W., Rijnhart, J. J., Hoekstra, T., Schuster, N. A., Ter Wee, M. M., & Heymans, M. W. (2020). Intention-to-treat analysis when only a baseline value is available. Contemporary clinical trials communications, 20100684. https://doi.org/10.1016/j.conctc.2020.100684
Twisk, Jos Wr, et al. "Intention-to-treat analysis when only a baseline value is available." Contemporary clinical trials communications vol. 20 (2020): 100684. doi: https://doi.org/10.1016/j.conctc.2020.100684
Twisk JW, Rijnhart JJ, Hoekstra T, Schuster NA, Ter Wee MM, Heymans MW. Intention-to-treat analysis when only a baseline value is available. Contemp Clin Trials Commun. 2020 Nov 26;20:100684. doi: 10.1016/j.conctc.2020.100684. eCollection 2020 Dec. PMID: 33319119; PMCID: PMC7726664.
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Contemp Clin Trials Commun. 2020 Nov 26;20:100684. doi: 10.1016/j.conctc.2020.100684. eCollection 2020 Dec.

Intention-to-treat analysis when only a baseline value is available.

Contemporary clinical trials communications

Jos Wr Twisk, Judith Jm Rijnhart, Trynke Hoekstra, Noah A Schuster, Marieke M Ter Wee, Martijn W Heymans

Affiliations

  1. Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, UMC Amsterdam, the Netherlands.
  2. Department of Health Science, Amsterdam Public Health Research Institute, Faculty of Science, VU University, Amsterdam, the Netherlands.

PMID: 33319119 PMCID: PMC7726664 DOI: 10.1016/j.conctc.2020.100684

Abstract

OBJECTIVES: How to perform an intention to treat (ITT) analysis when a patient has a baseline value but no follow-up measurements is problematic. The purpose of this study was to compare different methods that deal with this problem, i.e. no imputation (standard and alternative mixed model analysis), single imputation (i.e. baseline value carried forward), and multiple imputation (selective and non-selective).

STUDY DESIGN AND SETTING: We used a simulation study with different scenarios regarding 1) the association between missingness and the baseline value, 2) whether the patients did or did not receive the treatment, and 3) the percentage of missing data, and two real life data sets.

RESULTS: Bias and coverage were comparable between the two mixed model analyses and multiple imputation in most situations including the real life data examples. Only in the situation when the patients in the treatment group were simulated not to have received the treatment, selective imputation using this information outperformed all other methods.

CONCLUSIONS: In most situations a standard mixed model analysis without imputation is appropriate as ITT analysis. However, when patients with missing follow-up data allocated to the treatment group did not received treatment, it is advised to use selective imputation, using this information, although the results should be interpreted with caution.

© 2020 The Authors. Published by Elsevier Inc.

Keywords: Intention to treat analysis; Mixed model analysis; Multiple imputation; Randomised controlled trial; Selective imputation; Single imputation

Conflict of interest statement

None.

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