IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v64y2023i4d10.1007_s00362-023-01433-0.html
   My bibliography  Save this article

New insights into adaptive enrichment designs

Author

Listed:
  • Alessandro Baldi Antognini

    (University of Bologna)

  • Rosamarie Frieri

    (University of Bologna)

  • Maroussa Zagoraiou

    (University of Bologna)

Abstract

The transition towards personalized medicine is happening and the new experimental framework is raising several challenges, from a clinical, ethical, logistical, regulatory, and statistical perspective. To face these challenges, innovative study designs with increasing complexity have been proposed. In particular, adaptive enrichment designs are becoming more attractive for their flexibility. However, these procedures rely on an increasing number of parameters that are unknown at the planning stage of the clinical trial, so the study design requires particular care. This review is dedicated to adaptive enrichment studies with a focus on design aspects. While many papers deal with methods for the analysis, the sample size determination and the optimal allocation problem have been overlooked. We discuss the multiple aspects involved in adaptive enrichment designs that contribute to their advantages and disadvantages. The decision-making process of whether or not it is worth enriching should be driven by clinical and ethical considerations as well as scientific and statistical concerns.

Suggested Citation

  • Alessandro Baldi Antognini & Rosamarie Frieri & Maroussa Zagoraiou, 2023. "New insights into adaptive enrichment designs," Statistical Papers, Springer, vol. 64(4), pages 1305-1328, August.
    • Handle: RePEc:spr:stpapr:v:64:y:2023:i:4:d:10.1007_s00362-023-01433-0
    DOI: 10.1007/s00362-023-01433-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-023-01433-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00362-023-01433-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nigel Stallard, 2023. "Rejoinder to discussion on “Adaptive enrichment designs with a continuous biomarker”," Biometrics, The International Biometric Society, vol. 79(1), pages 36-38, March.
    2. Sergey Tarima & Nancy Flournoy, 2022. "Most powerful test sequences with early stopping options," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(4), pages 491-513, May.
    3. M. Rosenblum & M. J. van der Laan, 2011. "Optimizing randomized trial designs to distinguish which subpopulations benefit from treatment," Biometrika, Biometrika Trust, vol. 98(4), pages 845-860.
    4. Michael Rosenblum & Ethan X. Fang & Han Liu, 2020. "Optimal, two‐stage, adaptive enrichment designs for randomized trials, using sparse linear programming," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 749-772, July.
    5. Nigel Stallard, 2023. "Adaptive enrichment designs with a continuous biomarker," Biometrics, The International Biometric Society, vol. 79(1), pages 9-19, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nigel Stallard, 2023. "Rejoinder to discussion on “Adaptive enrichment designs with a continuous biomarker”," Biometrics, The International Biometric Society, vol. 79(1), pages 36-38, March.
    2. Rachael V. Phillips & Mark J. van der Laan, 2023. "Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard," Biometrics, The International Biometric Society, vol. 79(1), pages 20-22, March.
    3. Christopher Jennison, 2023. "Discussion on “Adaptive enrichment designs with a continuous biomarker” by N. Stallard," Biometrics, The International Biometric Society, vol. 79(1), pages 26-30, March.
    4. Sergey Tarima & Nancy Flournoy, 2023. "Group sequential tests: beyond exponential family models," Statistical Papers, Springer, vol. 64(4), pages 1361-1372, August.
    5. Michael Rosenblum & Ethan X. Fang & Han Liu, 2020. "Optimal, two‐stage, adaptive enrichment designs for randomized trials, using sparse linear programming," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 749-772, July.
    6. Susan Athey & Guido Imbens, 2015. "Recursive Partitioning for Heterogeneous Causal Effects," Papers 1504.01132, arXiv.org, revised Dec 2015.
    7. Rui Tang & Xiaoye Ma & Hui Yang & Michael Wolf, 2018. "Biomarker-Defined Subgroup Selection Adaptive Design for Phase III Confirmatory Trial with Time-to-Event Data: Comparing Group Sequential and Various Adaptive Enrichment Designs," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(2), pages 371-404, August.
    8. Zhiwei Zhang & Meijuan Li & Min Lin & Guoxing Soon & Tom Greene & Changyu Shen, 2017. "Subgroup selection in adaptive signature designs of confirmatory clinical trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 345-361, February.
    9. Nigel Stallard, 2023. "Adaptive enrichment designs with a continuous biomarker," Biometrics, The International Biometric Society, vol. 79(1), pages 9-19, March.
    10. Ke Sun & Linglong Kong & Hongtu Zhu & Chengchun Shi, 2024. "Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Time Series Experiments," Papers 2408.05342, arXiv.org, revised Oct 2024.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stpapr:v:64:y:2023:i:4:d:10.1007_s00362-023-01433-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.