TY - JOUR
T1 - Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables
AU - For the Alzheimer’s Disease Neuroimaging Initiative
AU - Qian, Tianchen
AU - Colantuoni, Elizabeth
AU - Fisher, Aaron
AU - Rosenblum, Michael
N1 - Funding Information:
This research was supported by the Patient-Centered Outcomes Research Institute ( ME-1306-03198 ). This paper's contents are solely the responsibility of the author and do not represent the views of the above agency. We thank the editor and two referees for constructive suggestions. We thank Mary Joy Argo for helpful comments. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) ( National Institutes of Health Grant U01 AG024904 ) and DOD ADNI ( Department of Defense award number W81XWH-12-2-0012 ). ADNI is funded by the National Institute on Aging , the National Institute of Biomedical Imaging and Bioengineering , and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organizatioin is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Appendix A
Publisher Copyright:
© 2017 The Authors
PY - 2017/12
Y1 - 2017/12
N2 - Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. Trial characteristics such as the accrual rate and the prognostic value of baseline variables are typically unknown when a trial is being planned; these values are typically assumed based on information available before the trial starts. Because of the added complexity in adaptive enrichment designs compared to standard designs, it may be of special concern how sensitive the trial performance is to deviations from assumptions. Through simulation studies, we evaluate the sensitivity of Type I error, power, expected sample size, and trial duration to different design characteristics. Our simulation distributions mimic features of data from the Alzheimer's Disease Neuroimaging Initiative cohort study, and involve two subpopulations based on a genetic marker. We investigate the impact of the following design characteristics: the accrual rate, the time from enrollment to measurement of a short-term outcome and the primary outcome, and the prognostic value of baseline variables and short-term outcomes. To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators. We apply information-based monitoring, and evaluate how accurately information can be estimated in an ongoing trial.
AB - Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. Trial characteristics such as the accrual rate and the prognostic value of baseline variables are typically unknown when a trial is being planned; these values are typically assumed based on information available before the trial starts. Because of the added complexity in adaptive enrichment designs compared to standard designs, it may be of special concern how sensitive the trial performance is to deviations from assumptions. Through simulation studies, we evaluate the sensitivity of Type I error, power, expected sample size, and trial duration to different design characteristics. Our simulation distributions mimic features of data from the Alzheimer's Disease Neuroimaging Initiative cohort study, and involve two subpopulations based on a genetic marker. We investigate the impact of the following design characteristics: the accrual rate, the time from enrollment to measurement of a short-term outcome and the primary outcome, and the prognostic value of baseline variables and short-term outcomes. To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators. We apply information-based monitoring, and evaluate how accurately information can be estimated in an ongoing trial.
KW - Adaptive enrichment
KW - Clinical trial design
KW - Group sequential stopping
KW - Multiple testing procedure
KW - Treatment effect heterogeneity
UR - http://www.scopus.com/inward/record.url?scp=85028341254&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028341254&partnerID=8YFLogxK
U2 - 10.1016/j.conctc.2017.08.003
DO - 10.1016/j.conctc.2017.08.003
M3 - Article
C2 - 29696195
AN - SCOPUS:85028341254
SN - 2451-8654
VL - 8
SP - 39
EP - 48
JO - Contemporary Clinical Trials Communications
JF - Contemporary Clinical Trials Communications
ER -