IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i18p3965-d1242621.html
   My bibliography  Save this article

Adaptive Multiple Testing Procedure for Clinical Trials with Urn Allocation

Author

Listed:
  • Hanan Hammouri

    (Department of Mathematics and Statistics, Faculty of Science and Art, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan)

  • Mohammed Ali

    (Department of Mathematics and Statistics, Faculty of Science and Art, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan)

  • Marwan Alquran

    (Department of Mathematics and Statistics, Faculty of Science and Art, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan)

  • Areen Alquran

    (Department of Statistics, Yarmouk University, Irbid 21163, Jordan)

  • Ruwa Abdel Muhsen

    (Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM 88001, USA)

  • Belal Alomari

    (Department of Mathematics and Statistics, Faculty of Science and Art, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan)

Abstract

This work combines the Urn allocation and O’Brien and Fleming multiple testing procedure to compare two treatments in clinical trials in a novel way. It is shown that this approach overcomes the constraints that previously made it challenging to apply the original adaptive design to clinical trials. The method provides unique flexibility, enabling trials to be stopped early if one treatment shows it is superior without compromising the efficiency of the original multiple testing procedure in terms of type I error rate and power. Experimental data and simulated case examples are used to illustrate the efficacy and robustness of this original approach and its potential for usage in a variety of clinical settings.

Suggested Citation

  • Hanan Hammouri & Mohammed Ali & Marwan Alquran & Areen Alquran & Ruwa Abdel Muhsen & Belal Alomari, 2023. "Adaptive Multiple Testing Procedure for Clinical Trials with Urn Allocation," Mathematics, MDPI, vol. 11(18), pages 1-20, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3965-:d:1242621
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/18/3965/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/18/3965/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lu Chi & H. M. James Hung & Sue-Jane Wang, 1999. "Modification of Sample Size in Group Sequential Clinical Trials," Biometrics, The International Biometric Society, vol. 55(3), pages 853-857, September.
    2. Walter Lehmacher & Gernot Wassmer, 1999. "Adaptive Sample Size Calculations in Group Sequential Trials," Biometrics, The International Biometric Society, vol. 55(4), pages 1286-1290, December.
    3. Madhu Mazumdar, 2004. "Group Sequential Design for Comparative Diagnostic Accuracy Studies: Implications and Guidelines for Practitioners," Medical Decision Making, , vol. 24(5), pages 525-533, October.
    4. Hanan Hammouri & Marwan Alquran & Ruwa Abdel Muhsen & Jaser Altahat, 2022. "Optimal Weighted Multiple-Testing Procedure for Clinical Trials," Mathematics, MDPI, vol. 10(12), pages 1-19, June.
    5. Xikui Wang & Daryl Pullman, 2001. "Play-the-winner rule and adaptive designs of clinical trials," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 27, pages 1-8, January.
    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. Jingjing Chen, 2019. "A Note of Adaptive Design in Clinical Trials," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(5), pages 107-111, August.
    2. Lingyun Liu & Sam Hsiao & Cyrus R. Mehta, 2018. "Efficiency Considerations for Group Sequential Designs with Adaptive Unblinded Sample Size Re-assessment," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(2), pages 405-419, August.
    3. Guosheng Yin & Yu Shen, 2005. "Adaptive Design and Estimation in Randomized Clinical Trials with Correlated Observations," Biometrics, The International Biometric Society, vol. 61(2), pages 362-369, June.
    4. René Schmidt & Andreas Faldum & Joachim Gerß, 2015. "Adaptive designs with arbitrary dependence structure based on Fisher’s combination test," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 427-447, September.
    5. P. Bauer, 2006. "Discussions," Biometrics, The International Biometric Society, vol. 62(3), pages 676-678, September.
    6. Jin Wang, 2022. "Sample Size Re-estimation with the Com-Nougue Method to Evaluate Treatment Effect," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(1), pages 90-103, April.
    7. Hanan Hammouri & Marwan Alquran & Ruwa Abdel Muhsen & Jaser Altahat, 2022. "Optimal Weighted Multiple-Testing Procedure for Clinical Trials," Mathematics, MDPI, vol. 10(12), pages 1-19, June.
    8. 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.
    9. Martin Posch & Peter Bauer, 2000. "Interim Analysis and Sample Size Reassessment," Biometrics, The International Biometric Society, vol. 56(4), pages 1170-1176, December.
    10. Georg Gutjahr & Werner Brannath & Peter Bauer, 2011. "An Approach to the Conditional Error Rate Principle with Nuisance Parameters," Biometrics, The International Biometric Society, vol. 67(3), pages 1039-1046, September.
    11. Hans-Helge Müller & Helmut Schäfer, 2001. "Adaptive Group Sequential Designs for Clinical Trials: Combining the Advantages of Adaptive and of Classical Group Sequential Approaches," Biometrics, The International Biometric Society, vol. 57(3), pages 886-891, September.
    12. Sebastian Irle & Helmut Schäfer, 2012. "Interim Design Modifications in Time-to-Event Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 341-348, March.
    13. 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.
    14. Michael A. Proschan, 2006. "Discussions," Biometrics, The International Biometric Society, vol. 62(3), pages 674-676, September.
    15. Zhiwei Jiang & Ling Wang & Chanjuan Li & Jielai Xia & Hongxia Jia, 2012. "A Practical Simulation Method to Calculate Sample Size of Group Sequential Trials for Time-to-Event Data under Exponential and Weibull Distribution," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-12, September.
    16. Werner Brannath & Peter Bauer, 2004. "Optimal Conditional Error Functions for the Control of Conditional Power," Biometrics, The International Biometric Society, vol. 60(3), pages 715-723, September.
    17. W. Brannath & P. Bauer & W. Maurer & M. Posch, 2003. "Sequential Tests for Noninferiority and Superiority," Biometrics, The International Biometric Society, vol. 59(1), pages 106-114, March.
    18. Gregory P. Levin & Sarah C. Emerson & Scott S. Emerson, 2014. "An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size," Biometrics, The International Biometric Society, vol. 70(3), pages 556-567, September.
    19. repec:jss:jstsof:28:i07 is not listed on IDEAS
    20. 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.
    21. Yeonhee Park & Suyu Liu & Peter F. Thall & Ying Yuan, 2022. "Bayesian group sequential enrichment designs based on adaptive regression of response and survival time on baseline biomarkers," Biometrics, The International Biometric Society, vol. 78(1), pages 60-71, March.

    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:gam:jmathe:v:11:y:2023:i:18:p:3965-:d:1242621. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.