IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v79y2023i3p2565-2576.html
   My bibliography  Save this article

Design considerations for two‐stage enrichment clinical trials

Author

Listed:
  • Rosamarie Frieri
  • William Fisher Rosenberger
  • Nancy Flournoy
  • Zhantao Lin

Abstract

When there is a predictive biomarker, enrichment can focus the clinical trial on a benefiting subpopulation. We describe a two‐stage enrichment design, in which the first stage is designed to efficiently estimate a threshold and the second stage is a “phase III‐like” trial on the enriched population. The goal of this paper is to explore design issues: sample size in Stages 1 and 2, and re‐estimation of the Stage 2 sample size following Stage 1. By treating these as separate trials, we can gain insight into how the predictive nature of the biomarker specifically impacts the sample size. We also show that failure to adequately estimate the threshold can have disastrous consequences in the second stage. While any bivariate model could be used, we assume a continuous outcome and continuous biomarker, described by a bivariate normal model. The correlation coefficient between the outcome and biomarker is the key to understanding the behavior of the design, both for predictive and prognostic biomarkers. Through a series of simulations we illustrate the impact of model misspecification, consequences of poor threshold estimation, and requisite sample sizes that depend on the predictive nature of the biomarker. Such insight should be helpful in understanding and designing enrichment trials.

Suggested Citation

  • Rosamarie Frieri & William Fisher Rosenberger & Nancy Flournoy & Zhantao Lin, 2023. "Design considerations for two‐stage enrichment clinical trials," Biometrics, The International Biometric Society, vol. 79(3), pages 2565-2576, September.
  • Handle: RePEc:bla:biomet:v:79:y:2023:i:3:p:2565-2576
    DOI: 10.1111/biom.13805
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/biom.13805
    Download Restriction: no

    File URL: https://libkey.io/10.1111/biom.13805?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
    ---><---

    References listed on IDEAS

    as
    1. Ying‐Qi Zhao & Michael L. LeBlanc, 2020. "Designing precision medicine trials to yield a greater population impact," Biometrics, The International Biometric Society, vol. 76(2), pages 643-653, June.
    2. Horrace, William C., 2005. "Some results on the multivariate truncated normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 209-221, May.
    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. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    2. Denisa Banulescu-Radu & Christophe Hurlin & Jérémy Leymarie & Olivier Scaillet, 2021. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Management Science, INFORMS, vol. 67(9), pages 5730-5754, September.
    3. Yue, Chen & Chen, Shaojie & Sair, Haris I. & Airan, Raag & Caffo, Brian S., 2015. "Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 126-133.
    4. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    5. Badía, F.G. & Sangüesa, C. & Cha, J.H., 2014. "Stochastic comparison of multivariate conditionally dependent mixtures," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 82-94.
    6. Arismendi, J.C., 2013. "Multivariate truncated moments," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 41-75.
    7. Centorrino, Samuele & Pérez-Urdiales, María, 2023. "Maximum likelihood estimation of stochastic frontier models with endogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 82-105.
    8. Reinaldo B. Arellano-Valle & Adelchi Azzalini, 2022. "Some properties of the unified skew-normal distribution," Statistical Papers, Springer, vol. 63(2), pages 461-487, April.
    9. Cruz Lopez, Jorge A. & Harris, Jeffrey H. & Hurlin, Christophe & Pérignon, Christophe, 2017. "CoMargin," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(5), pages 2183-2215, October.
      • Jorge A. Cruz Lopez & Jeffrey H. Harris & Christophe Hurlin & Christophe Pérignon, 2015. "CoMargin," Working Papers halshs-00979440, HAL.
      • Jorge Cruz Lopez & Jeffrey Harris & Christophe Hurlin & Christophe Pérignon, 2017. "CoMargin," Post-Print hal-03579309, HAL.
    10. Ravi Kashyap, 2016. "The Perfect Marriage and Much More: Combining Dimension Reduction, Distance Measures and Covariance," Papers 1603.09060, arXiv.org, revised Jul 2019.
    11. P. Economou & S. Malefaki & C. Caroni, 2015. "Bayesian Threshold Regression Model with Random Effects for Recurrent Events," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 871-898, December.
    12. Kashyap, Ravi, 2019. "The perfect marriage and much more: Combining dimension reduction, distance measures and covariance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    13. Jamie Crandell & Corrine Voils & YunKyung Chang & Margarete Sandelowski, 2011. "Bayesian data augmentation methods for the synthesis of qualitative and quantitative research findings," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(3), pages 653-669, April.
    14. Camba-Méndez, Gonzalo & Rodriguez-Palenzuela, Diego & Carbó-Valverde, Santiago, 2014. "Financial reputation, market interventions and debt issuance by banks: a truncated two-part model approach," Working Paper Series 1741, European Central Bank.
    15. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    16. C. Adcock, 2010. "Asset pricing and portfolio selection based on the multivariate extended skew-Student-t distribution," Annals of Operations Research, Springer, vol. 176(1), pages 221-234, April.
    17. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    18. Lin, Tsung-I & Wang, Wan-Lun, 2024. "On moments of truncated multivariate normal/independent distributions," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    19. Huiping Xu & Bruce A. Craig, 2009. "A Probit Latent Class Model with General Correlation Structures for Evaluating Accuracy of Diagnostic Tests," Biometrics, The International Biometric Society, vol. 65(4), pages 1145-1155, December.
    20. Raúl Alejandro Morán-Vásquez & Edwin Zarrazola & Daya K. Nagar, 2022. "Some Statistical Aspects of the Truncated Multivariate Skew- t Distribution," Mathematics, MDPI, vol. 10(15), pages 1-14, August.

    More about this item

    Statistics

    Access and download statistics

    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:bla:biomet:v:79:y:2023:i:3:p:2565-2576. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.