Categories, components, and techniques in a modular construction of basket trials for application and further research.
Bayes
basket trial
frequentist
overview
precision medicine
Journal
Biometrical journal. Biometrische Zeitschrift
ISSN: 1521-4036
Titre abrégé: Biom J
Pays: Germany
ID NLM: 7708048
Informations de publication
Date de publication:
08 2021
08 2021
Historique:
revised:
15
02
2021
received:
22
10
2020
accepted:
30
04
2021
pubmed:
5
5
2021
medline:
3
11
2021
entrez:
4
5
2021
Statut:
ppublish
Résumé
Basket trials have become a virulent topic in medical and statistical research during the last decade. The core idea of them is to treat patients, who express the same genetic predisposition-either personally or their disease-with the same treatment irrespective of the location of the disease. The location of the disease defines each basket and the pathway of the treatment uses the common genetic predisposition among the baskets. This opens the opportunity to share information among baskets, which can consequently increase the information of the basket-wise response with respect to the investigated treatment. This further allows dynamic decisions regarding futility and efficacy of individual baskets during the ongoing trial. Several statistical designs have been proposed on how a basket trial can be conducted and this has left an unclear situation with many options. The different designs propose different mathematical and statistical techniques, different decision rules, and also different trial purposes. This paper presents a broad overview of existing designs, categorizes them, and elaborates their similarities and differences. A uniform and consistent notation facilitates the first contact, introduction, and understanding of the statistical methodologies and techniques used in basket trials. Finally, this paper presents a modular approach for the construction of basket trials in applied medical science and forms a base for further research of basket trial designs and their techniques.
Identifiants
pubmed: 33942894
doi: 10.1002/bimj.202000314
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1159-1184Informations de copyright
© 2021 The Authors. Biometrical Journal published by Wiley-VCH GmbH.
Références
Asano, J., & Hirakawa, A. (2020). A Bayesian basket trial design accounting for uncertainties of homogeneity and heterogeneity of treatment effect among subpopulations. Pharmaceutical Statistics, 19, 975-1000.
Ashley, E. A. (2016). Towards precision medicine. Nature Reviews Genetics, 17, 507-522.
Bayes, T., & Price (1763). Lii. an essay towards solving a problem in the doctrine of chances. by the late rev. mr. bayes, f. r. s. communicated by mr. price, in a letter to john canton, a. m. f. r. s. Philosophical Transactions of the Royal Society of London, 53, 370-418.
Beckman, R., Antonijevic, Z., Kalamegham, R., & Chen, C. (2016). Adaptive design for a confirmatory basket trial in multiple tumor types based on a putative predictive biomarker. Clinical Pharmacology & Therapeutics, 100, 617-625.
Berry, D. A. (2015). The brave new world of clinical cancer research: Adaptive biomarker-driven trials integrating clinical practice with clinical research. Molecular Oncology, 9, 951-959.
Berry, S. M., Broglio, K. R., Groshen, S., & Berry, D. A. (2013). Bayesian hierarchical modeling of patient subpopulations: Efficient designs of phase ii oncology clinical trials. Clinical Trials, 10, 720-734.
Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., & Jemal, A. (2018). Global cancer statistics 2018: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians, 68, 394-424.
Chen, C., Li, X., Yuan, S., Antonijevic, Z., Kalamegham, R., & Beckman, R. A. (2016). Statistical design and considerations of a phase 3 basket trial for simultaneous investigation of multiple tumor types in one study. Statistics in Biopharmaceutical Research, 8, 248-257.
Chen, N., & Lee, J. J. (2019). Bayesian hierarchical classification and information sharing for clinical trials with subgroups and binary outcomes. Biometrical Journal, 61, 1219-1231.
Chen, N., & Lee, J. J. (2020). Bayesian cluster hierarchical model for subgroup borrowing in the design and analysis of basket trials with binary endpoints. Statistical Methods in Medical Research, 29, 2717-2732.
Chu, Y., & Yuan, Y. (2018a). A Bayesian basket trial design using a calibrated Bayesian hierarchical model. Clinical Trials, 15, 149-158.
Chu, Y., & Yuan, Y. (2018b). Blast: Bayesian latent subgroup design for basket trials accounting for patient heterogeneity. Journal of the Royal Statistical Society: Series C (Applied Statistics), 67, 723-740.
Collignon, O., Gartner, C., Haidich, A.-B., James Hemmings, R., Hofner, B., Pétavy, F., Posch, M., Rantell, K., Roes, K., & Schiel, A. (2020). Current statistical considerations and regulatory perspectives on the planning of confirmatory basket, umbrella, and platform trials. Clinical Pharmacology & Therapeutics, 107, 1059-1067.
Cunanan, K. M., Gonen, M., Shen, R., Hyman, D. M., Riely, G. J., Begg, C. B., & Iasonos, A. (2017a). Basket trials in oncology: A trade-off between complexity and efficiency. Journal of Clinical Oncology, 35, 271-273.
Cunanan, K. M., Iasonos, A., Shen, R., Begg, C. B., & Gönen, M. (2017b). An efficient basket trial design. Statistics in Medicine, 36, 1568-1579.
Fleming, T. R., & LeMets, D. L. (1996). Surrogate end points in clinical trials: Are we being misled? Annals of Internal Medicine, 125, 605-613.
Freidlin, B., & Korn, E. L. (2013). Borrowing information across subgroups in phase ii trials: Is it useful? Clinical Cancer Research, 19, 1326-1334.
Fujikawa, K., Teramukai, S., Yokota, I., & Daimon, T. (2020). A Bayesian basket trial design that borrows information across strata based on the similarity between the posterior distributions of the response probability. Biometrical Journal, 62, 330-338.
Hobbs, B. P., & Landin, R. (2018). Bayesian basket trial design with exchangeability monitoring. Statistics in Medicine, 37, 3557-3572.
Jackson, S. E., & Chester, J. D. (2015). Personalised cancer medicine. International Journal of Cancer, 137, 262-266.
Jin, J., Liu, Q., Zheng, W., Shun, Z., Lin, T. T., Gao, L., & Dong, Y. (2020a). A Bayesian method for the detection of proof of concept in early phase oncology studies with a basket design. Statistics in Biosciences, 12, 167-179.
Jin, J., Riviere, M.-K., Luo, X., & Dong, Y. (2020b). Bayesian methods for the analysis of early-phase oncology basket trials with information borrowing across cancer types. Statistics in Medicine, 39, 3459-3475.
Kaizer, A. M., Koopmeiners, J. S., & Hobbs, B. P. (2017). Bayesian hierarchical modeling based on multisource exchangeability. Biostatistics, 19, 169-184.
Kitsios, G. D., & Kent, D. M. (2012). Personalised medicine: Not just in our genes. BMJ, 344, e2161.
Li, W., Chen, C., Li, X., & Beckman, R. A. (2017). Estimation of treatment effect in two-stage confirmatory oncology trials of personalized medicines. Statistics in Medicine, 36, 1843-1861.
Li, W., Zhao, J., Li, X., Chen, C., & Beckman, R. A. (2019). Multi-stage enrichment and basket trial designs with population selection. Statistics in Medicine, 38, 5470-5485.
Lin, R., Thall, P. F., & Yuan, Y. (2020). Bags: A Bayesian adaptive group sequential trial design with subgroup-specific survival comparisons. Journal of the American Statistical Association, 116, 322-334.
Lin, R., Thall, P. F., & Yuan, Y. (2021). A phase i-ii basket trial design to optimize dose-schedule regimes based on delayed outcomes. Bayesian Analysis, 16, 179-202.
Liu, R., Liu, Z., Ghadessi, M., & Vonk, R. (2017). Increasing the efficiency of oncology basket trials using a Bayesian approach. Contemporary Clinical Trials 63, 67-72.
Lyu, J., Zhou, T., Yuan, S., Guo, W., & Ji, Y. (2020). MUCE: Bayesian hierarchical modeling for the design and analysis of phase 1b multiple expansion cohort trials. arXiv:2006.07785.
Meyer, E. L., Mesenbrink, P., Dunger-Baldauf, C., Fülle, H.-J., Glimm, E., Li, Y., Posch, M., & König, F. (2020). The evolution of master protocol clinical trial designs: A systematic literature review. Clinical Therapeutics, 42, 1330-1360.
Neuenschwander, B., Wandel, S., Roychoudhury, S., & Bailey, S. (2016). Robust exchangeability designs for early phase clinical trials with multiple strata. Pharmaceutical Statistics, 15, 123-34.
Park, J. J. H., Siden, E., Zoratti, M. J., Dron, L., Harari, O., Singer, J., Lester, R. T., Thorlund, K., & Mills, E. J. (2019). Systematic review of basket trials, umbrella trials, and platform trials: A landscape analysis of master protocols. Trials, 20, 572.
Psioda, M. A., Xu, J., Jiang, Q., Ke, C., Yang, Z., & Ibrahim, J. G. (2019). Bayesian adaptive basket trial design using model averaging. Biostatistics, 22, 19-34.
Renfro, L. A., & Sargent, D. J. (2017). Statistical controversies in clinical research: Basket trials, umbrella trials, and other master protocols: a review and examples. Annals of Oncology, 28, 34-43.
Saville, B. R., Connor, J. T., Ayers, G. D., & Alvarez, J. (2014). The utility of Bayesian predictive probabilities for interim monitoring of clinical trials. Clinical Trials, 11, 485-493.
Sethuraman, J. (1994). A constructive definition of the dirichlet prior. Statistica Sinica, 4, 639-650.
Simon, R., Geyer, S., Subramanian, J., & Roychowdhury, S. (2016). The Bayesian basket design for genomic variant-driven phase ii trials. Seminars in Oncology, 43, 13-18.
Thall, P. F., Wathen, J. K., Bekele, B. N., Champlin, R. E., Baker, L. H., & Benjamin, R. S. (2003). Hierarchical Bayesian approaches to phase ii trials in diseases with multiple subtypes. Statistics in Medicine, 22, 763-80.
Trippa, L., & Alexander, B. M. (2017). Bayesian baskets: A novel design for biomarker-based clinical trials. Journal of Clinical Oncology, 35(6), 681-687.
Ventz, S., Barry, W. T., Parmigiani, G., & Trippa, L. (2017). Bayesian response-adaptive designs for basket trials. Biometrics, 73, 905-915.
Wathen, J. K., & Thall, P. F. (2017). A simulation study of outcome adaptive randomization in multi-arm clinical trials. Clinical Trials, 14, 432-440.
Woodcock, J., & LaVange, L. M. (2017). Master protocols to study multiple therapies, multiple diseases, or both. New England Journal of Medicine, 377, 62-70.
Xu, Y., Müller, P., Tsimberidou, A. M., & Berry, D. (2019). A nonparametric Bayesian basket trial design. Biometrical Journal, 61, 1160-1174.
Yin, G., Yang, Z., Odani, M., & Fukimbara, S. (2020). Bayesian hierarchical modeling and biomarker cutoff identification in basket trials. Statistics in Biopharmaceutical Research, 1-11. https://doi.org/10.1080/19466315.2020.1811146.
Zheng H., & Wason, J.M.S. (2020). Borrowing of information across patient subgroups in a basket trial based on distributional discrepancy. Biostatistics, https://doi.org/10.1093/biostatistics/kxaa019.
Zhou, H., Liu, F., Wu, C., Rubin, E. H., Giranda, V. L., & Chen, C. (2019). Optimal two-stage designs for exploratory basket trials. Contemporary Clinical Trials, 85, 105807.
Zhou T., & Ji, Y. (2020). RoBoT: a robust Bayesian hypothesis testing method for basket trials. Biostatistics, https://doi.org/10.1093/biostatistics/kxaa005.