Estimands: improving inference in randomized controlled trials in clinical nutrition in the presence of missing values

Abstract

For randomized controlled trials, the impact of the amount and handling of missing data on the interpretation of the treatment effect has been unclear. The current use of intention to treat, per protocol, and complete-case analysis has shortcomings. The use of estimands may lead to improved estimation of treatment effects through more precise characterizations of the fate of treatments after dropout or other post-randomization events. A perspective on current and future developments with a view toward clinical nutrition is provided.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1

References

  1. 1.

    International Conference on Harmonisation (ICH). E9(R1): Statistical principles for clinical trials: Addendum Estimands and Sensitivity Analyses in Clinical Trials; 2017.

  2. 2.

    Mallinckrodt CH. Preventing and treating missing in longitudinal clinical trials. Cambridge: Cambridge University Press; 2013.

  3. 3.

    Leuchs A-K, Zinserling J, Brandt A, Wirtz D, Benda N. Choosing appropriate estimands in clinicals. Ther Innov Regul Sci. 2015;49:584–92.

    PubMed  Google Scholar 

  4. 4.

    Helms RW. Precise definitions of some terminology for longitudinal clinical trials: subjects, patient populations, analysis sets, intention to treat, and related terms. Pharm Stat. 2016;15:471–85.

    Article  Google Scholar 

  5. 5.

    Carpenter JR, Roger JH, Kenward MG. Analysis of longitudinal trials with protocol deviation: a framework for relevant, accessible assumptions, and inference via multiple imputation. J Biopharm Stat. 2013;23:1352–71.

    Article  Google Scholar 

  6. 6.

    Permutt T. A taxonomy of estimands for regulatory clinical trials with discontinuations. Stat Med. 2016;35:2865–75.

    Article  Google Scholar 

  7. 7.

    Mallinckrodt CH, Molenberghs G, Rathmann S. Choosing estimands in clinical trials with missing data. Pharm Stat. 2017;16:29–36.

    Article  Google Scholar 

  8. 8.

    Geiker NRW, Ritz C, Pedersen SD, Larsen TM, Hill JO, Astrup A. A weight-loss program adapted to the menstrual cycle increases weight loss in healthy, overweight, premenopausal women: a 6-mo randomized controlled trial. Am J Clin Nutr. 2016;104:15–20.

    CAS  Article  Google Scholar 

  9. 9.

    White IR, Carpenter J, Horton NJ. Including all individuals is not enough: lessons for intention-to-treat analysis. Clin Trials. 2012;9:396–407.

    Article  Google Scholar 

  10. 10.

    Olsen MF, Abdissa A, Kæstel P, Tesfaye M, Yilma D, Girma T, et al. Nutrient supplements improve weight gain, lean mass, grip strength and immune recovery in HIV-patients initiating antiretroviral treatment: a randomised controlled trial in Ethiopia. BMJ. 2014;348:g3187.

    Article  Google Scholar 

  11. 11.

    Perkin MR, Logan K, Tseng A, Raji B, Ayis S, Peacock J, et al. Randomized trial of introduction of allergenic foods in breast-fed infants. New Engl J Med. 2016;374:1733–43.

    CAS  Article  Google Scholar 

  12. 12.

    Leuchs A-K, Brandt A, Zinserling J, Benda N. Disentangling estimands and the intention-to-treat principle. Pharm Stat. 2017;16:12–19.

    Article  Google Scholar 

  13. 13.

    Johnston BC, Guyatt GH. Best (but oft-forgotten) practices: intention-to-treat, treatment adherence, and missing participant outcome data in the nutrition literature. Am J Clin Nutr. 2016;104:1197–201.

    CAS  Article  Google Scholar 

  14. 14.

    Lu K. An analytic method for the placebo-based pattern-mixture model. Stat Med. 2014;33:1134–45.

    Article  Google Scholar 

  15. 15.

    Holzhauer B, Akacha M, Bermann G. Choice of estimand and analysis methods in diabetes trials with rescue medication. Pharm Stat. 2015;14:433–47.

    Article  Google Scholar 

  16. 16.

    Little R, Kang S. Intention-to-treat analysis with treatment discontinuation and missing data in clinical trials. Stat Med. 2015;34:2381–90.

    Article  Google Scholar 

  17. 17.

    Akacha M, Bretz F, Ruberg S. Estimands in clinical trials – broadening the perspective. Stat Med. 2017;36:5–19.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Christian Ritz.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ritz, C., Rønn, B. Estimands: improving inference in randomized controlled trials in clinical nutrition in the presence of missing values. Eur J Clin Nutr 72, 1291–1295 (2018). https://doi.org/10.1038/s41430-018-0207-x

Download citation

Further reading

Search