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Some recommendations for multi-arm multi-stage trials

Research output: Contribution to journalJournal article

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Some recommendations for multi-arm multi-stage trials. / Wason, James; Magirr, Dominic; Law, Martin; Jaki, Thomas.

In: Statistical Methods in Medical Research, Vol. 25, No. 2, 04.2016, p. 716-727.

Research output: Contribution to journalJournal article

Harvard

Wason, J, Magirr, D, Law, M & Jaki, T 2016, 'Some recommendations for multi-arm multi-stage trials', Statistical Methods in Medical Research, vol. 25, no. 2, pp. 716-727. https://doi.org/10.1177/0962280212465498

APA

Wason, J., Magirr, D., Law, M., & Jaki, T. (2016). Some recommendations for multi-arm multi-stage trials. Statistical Methods in Medical Research, 25(2), 716-727. https://doi.org/10.1177/0962280212465498

Vancouver

Wason J, Magirr D, Law M, Jaki T. Some recommendations for multi-arm multi-stage trials. Statistical Methods in Medical Research. 2016 Apr;25(2):716-727. https://doi.org/10.1177/0962280212465498

Author

Wason, James ; Magirr, Dominic ; Law, Martin ; Jaki, Thomas. / Some recommendations for multi-arm multi-stage trials. In: Statistical Methods in Medical Research. 2016 ; Vol. 25, No. 2. pp. 716-727.

Bibtex

@article{77e0281355aa41e9bcfcf9f7bd26f3d3,
title = "Some recommendations for multi-arm multi-stage trials",
abstract = "Multi-arm multi-stage designs can improve the efficiency of the drug-development process by evaluating multiple experimental arms against a common control within one trial. This reduces the number of patients required compared to a series of trials testing each experimental arm separately against control. By allowing for multiple stages experimental treatments can be eliminated early from the study if they are unlikely to be significantly better than control. Using the TAILoR trial as a motivating example, we explore a broad range of statistical issues related to multi-arm multi-stage trials including a comparison of different ways to power a multi-arm multi-stage trial; choosing the allocation ratio to the control group compared to other experimental arms; the consequences of adding additional experimental arms during a multi-arm multi-stage trial, and how one might control the type-I error rate when this is necessary; and modifying the stopping boundaries of a multi-arm multi-stage design to account for unknown variance in the treatment outcome. Multi-arm multi-stage trials represent a large financial investment, and so considering their design carefully is important to ensure efficiency and that they have a good chance of succeeding.",
keywords = "Clinical trial design, group-sequential designstesting statistical design, interim analysis, multi-arm multi-stage designs, multiple-testing , statistical design",
author = "James Wason and Dominic Magirr and Martin Law and Thomas Jaki",
note = "This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.",
year = "2016",
month = apr
doi = "10.1177/0962280212465498",
language = "English",
volume = "25",
pages = "716--727",
journal = "Statistical Methods in Medical Research",
issn = "0962-2802",
publisher = "SAGE Publications Ltd",
number = "2",

}

RIS

TY - JOUR

T1 - Some recommendations for multi-arm multi-stage trials

AU - Wason, James

AU - Magirr, Dominic

AU - Law, Martin

AU - Jaki, Thomas

N1 - This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PY - 2016/4

Y1 - 2016/4

N2 - Multi-arm multi-stage designs can improve the efficiency of the drug-development process by evaluating multiple experimental arms against a common control within one trial. This reduces the number of patients required compared to a series of trials testing each experimental arm separately against control. By allowing for multiple stages experimental treatments can be eliminated early from the study if they are unlikely to be significantly better than control. Using the TAILoR trial as a motivating example, we explore a broad range of statistical issues related to multi-arm multi-stage trials including a comparison of different ways to power a multi-arm multi-stage trial; choosing the allocation ratio to the control group compared to other experimental arms; the consequences of adding additional experimental arms during a multi-arm multi-stage trial, and how one might control the type-I error rate when this is necessary; and modifying the stopping boundaries of a multi-arm multi-stage design to account for unknown variance in the treatment outcome. Multi-arm multi-stage trials represent a large financial investment, and so considering their design carefully is important to ensure efficiency and that they have a good chance of succeeding.

AB - Multi-arm multi-stage designs can improve the efficiency of the drug-development process by evaluating multiple experimental arms against a common control within one trial. This reduces the number of patients required compared to a series of trials testing each experimental arm separately against control. By allowing for multiple stages experimental treatments can be eliminated early from the study if they are unlikely to be significantly better than control. Using the TAILoR trial as a motivating example, we explore a broad range of statistical issues related to multi-arm multi-stage trials including a comparison of different ways to power a multi-arm multi-stage trial; choosing the allocation ratio to the control group compared to other experimental arms; the consequences of adding additional experimental arms during a multi-arm multi-stage trial, and how one might control the type-I error rate when this is necessary; and modifying the stopping boundaries of a multi-arm multi-stage design to account for unknown variance in the treatment outcome. Multi-arm multi-stage trials represent a large financial investment, and so considering their design carefully is important to ensure efficiency and that they have a good chance of succeeding.

KW - Clinical trial design

KW - group-sequential designstesting statistical design

KW - interim analysis

KW - multi-arm multi-stage designs

KW - multiple-testing

KW - statistical design

U2 - 10.1177/0962280212465498

DO - 10.1177/0962280212465498

M3 - Journal article

VL - 25

SP - 716

EP - 727

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

SN - 0962-2802

IS - 2

ER -