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2014 ; 13
(6
): 345-56
Nephropedia Template TP
Pharm Stat
2014[Nov]; 13
(6
): 345-56
PMID25319733
show ga
Multiple testing procedures defined by directed, weighted graphs have recently
been proposed as an intuitive visual tool for constructing multiple testing
strategies that reflect the often complex contextual relations between hypotheses
in clinical trials. Many well-known sequentially rejective tests, such as
(parallel) gatekeeping tests or hierarchical testing procedures are special cases
of the graph based tests. We generalize these graph-based multiple testing
procedures to adaptive trial designs with an interim analysis. These designs
permit mid-trial design modifications based on unblinded interim data as well as
external information, while providing strong family wise error rate control. To
maintain the familywise error rate, it is not required to prespecify the adaption
rule in detail. Because the adaptive test does not require knowledge of the
multivariate distribution of test statistics, it is applicable in a wide range of
scenarios including trials with multiple treatment comparisons, endpoints or
subgroups, or combinations thereof. Examples of adaptations are dropping of
treatment arms, selection of subpopulations, and sample size reassessment. If, in
the interim analysis, it is decided to continue the trial as planned, the
adaptive test reduces to the originally planned multiple testing procedure. Only
if adaptations are actually implemented, an adjusted test needs to be applied.
The procedure is illustrated with a case study and its operating characteristics
are investigated by simulations.
|Clinical Trials as Topic/methods/*statistics & numerical data
[MESH]
free
free
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