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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - The R package MAMS for designing multi-arm multi-stage clinical trials
AU - Jaki, Thomas Friedrich
AU - Pallmann, Philip Steffen
AU - Magirr, Dominic
PY - 2019/1/31
Y1 - 2019/1/31
N2 - In the early stages of drug development there is often uncertainty about the most promising among a set of different treatments, different doses of the same treatment, or combinations of treatments. Multi-arm multi-stage (MAMS) clinical studies provide an efficient solution to determine which intervention is most promising. In this paper we discuss the R package MAMS that allows designing such studies within the group-sequential framework. The package implements MAMS studies with normal, binary, ordinal, or timeto-event endpoints in which either the single best treatment or all promising treatments are continued at the interim analyses. Additionally unexpected design modifications can be accounted for via the use of the conditional error approach. We provide illustrative examples of the use of the package based on real trial designs.
AB - In the early stages of drug development there is often uncertainty about the most promising among a set of different treatments, different doses of the same treatment, or combinations of treatments. Multi-arm multi-stage (MAMS) clinical studies provide an efficient solution to determine which intervention is most promising. In this paper we discuss the R package MAMS that allows designing such studies within the group-sequential framework. The package implements MAMS studies with normal, binary, ordinal, or timeto-event endpoints in which either the single best treatment or all promising treatments are continued at the interim analyses. Additionally unexpected design modifications can be accounted for via the use of the conditional error approach. We provide illustrative examples of the use of the package based on real trial designs.
KW - adaptive designs
KW - conditional error
KW - multi-arm
KW - R
KW - step-down procedure
U2 - 10.18637/jss.v088.i04
DO - 10.18637/jss.v088.i04
M3 - Journal article
VL - 88
JO - Journal of Statistical Software
JF - Journal of Statistical Software
SN - 1548-7660
IS - 4
ER -