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Estimands for Repeated Continuous Outcomes

Author
Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry
Published
Mon 18 Dec 2023
Episode Link
https://podcastae8fac.podigee.io/326-new-episode

Interview with Oliver Keene

  • Discussion on Oliver's Career

  • Estimates for Repeated Continuous Outcomes

  • Response to Ting's Article

  • Defining Estimates

  • Discussion on Treatment Policy

  • Treatment Policy and Intent-to-Treat Analysis

  • Hypothetical Strategy

  • Communication Challenges:

  • One Patient, One Vote Concept

  • Last Observation Analysis

  • Communication of Statistical Approaches


We invite statisticians to reflect on the evolving landscape of estimands, encouraging thoughtful consideration of estimation techniques and a deeper exploration of causal inference in clinical trials. The journey through this nuanced statistical terrain unfolds, offering valuable insights for both seasoned professionals and newcomers to the field.


Reference:
Wright et al 2023 Response to Ting


Role play reference:




  1. Keene ON, Ruberg S, Schacht A, Akacha M, Lawrance R, Berglind A, Wright D. What matters most? Different stakeholder perspectives on estimands for an invented case study in COPD. Pharmaceutical Statistics. 2020 Jul;19(4):370-87.
    https://pubmed.ncbi.nlm.nih.gov/31919979/




Other references:




  1. Naitee Ting (2023) Emerging insights and commentaries – MMRM vs LOCF, Journal of Biopharmaceutical Statistics, 33:2, 253-255, DOI: 10.1080/10543406.2023.2184828




  2. https://www.tandfonline.com/doi/abs/10.1080/10543406.2023.2184828




  3. Wright D, Bratton DJ, Drury T, Keene ON, Rehal S, White IR. Response to Comment on” Emerging insights and commentaries–MMRM vs LOCF by Naitee Ting”. Journal of Biopharmaceutical Statistics. 2023 Sep 23:1-3.






  1. Keene ON. Adherence, per-protocol effects, and the estimands framework. Pharmaceutical Statistics. 2023;1‐4. doi:10.1002/pst.232




  2. Keene ON. Intent-to-treat analysis in the presence of off-treatment or missing data. Pharmaceutical Statistics 2011, 10:191–195, doi: 10.1002/pst.421.




  3. Keene ON, Wright D, Phillips A, Wright M. Why ITT analysis is not always the answer for estimating treatment effects in clinical trials. Contemporary Clinical Trials. 2021 Sep 1;108:106494.




  4. Keene ON, Lynggaard H, Englert S, Lanius V, Wright D. Why estimands are needed to define treatment effects in clinical trials. BMC Medicine. 2023 Jul 27;21(1):276.



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