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@ARTICLE{Benda:144995,
author = {Benda, Norbert and Hänisch, Britta},
title = {{E}nrichment designs using placebo nonresponders.},
journal = {Pharmaceutical statistics},
volume = {19},
number = {3},
issn = {1539-1604},
address = {New York, NY},
publisher = {Wiley},
reportid = {DZNE-2020-00359},
pages = {303-314},
year = {2020},
abstract = {Enrichment designs that select placebo nonresponders have
gained much attention during the last years in areas with
high placebo response rates, eg, in depression. Proposals
were made that re-randomize patients who did not respond to
placebo during a first study phase as the sequential
parallel design (SPD). This design uses in a second phase an
enriched patient population where the treatment effect is
expected to be more pronounced. This may be problematic if
an effect in the overall population is claimed. Proposals
were made to combine the treatment effects in the overall
population from study phase 1 and the enriched population
from study phase 2, alleviating but not solving the issue of
a potential selection bias. This paper shows how this bias
corresponding to the effect difference between the overall
population and the enriched population depends on the
variability of a potential subject-by-treatment interaction.
Sample sizes are given, which lead to a significant result
in the combining test with a given probability if actually
the average effect in the overall population is zero. If, on
the other hand, no subject-by-treatment interaction is
given, the enrichment is shown to be inefficient. We
conclude that enrichment designs using placebo nonresponders
are not able to claim a positive average effect in the
overall population if a subject-by-treatment interaction
cannot be excluded. It cannot be used to demonstrate
positive efficacy in the overall population in a pivotal
phase III trial but may be used in early phases to
demonstrate varying treatment effects between patients.},
keywords = {Data Interpretation, Statistical / Double-Blind Method /
Humans / Models, Statistical / Placebo Effect / Randomized
Controlled Trials as Topic: statistics $\&$ numerical data /
Research Design: statistics $\&$ numerical data / Treatment
Outcome},
cin = {AG Hänisch ; AG Hänisch},
ddc = {610},
cid = {I:(DE-2719)1013010},
pnm = {345 - Population Studies and Genetics (POF3-345)},
pid = {G:(DE-HGF)POF3-345},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:31899854},
doi = {10.1002/pst.1992},
url = {https://pub.dzne.de/record/144995},
}