Retention of Alzheimer Disease Research Participants

Supplemental Digital Content is available in the text. Introduction: Participant retention is important to maintaining statistical power, minimizing bias, and preventing scientific error in Alzheimer disease and related dementias research. Methods: We surveyed representative investigators from NIH-funded Alzheimer’s Disease Research Centers (ADRC), querying their use of retention tactics across 12 strategies. We compared survey results to data from the National Alzheimer’s Coordinating Center for each center. We used a generalized estimating equation with independent working covariance model and empirical standard errors to assess relationships between survey results and rates of retention, controlling for participant characteristics. Results: Twenty-five (83%) responding ADRCs employed an average 42 (SD=7) retention tactics. In a multivariable model that accounted for participant characteristics, the number of retention tactics used by a center was associated with participant retention (odds ratio=1.68, 95% confidence interval: 1.42, 1.98; P<0.001 for the middle compared with the lowest tertile survey scores; odds ratio=1.59, 95% confidence interval: 1.30, 1.94; P<0.001 for the highest compared with the lowest tertile survey scores) at the first follow-up visit. Participant characteristics such as normal cognition diagnosis, older age, higher education, and Caucasian race were also associated with higher retention. Conclusions: Retention in clinical research is more likely to be achieved by employing a variety of tactics.

[1]  Charles Mock,et al.  Version 3 of the National Alzheimer’s Coordinating Center’s Uniform Data Set , 2018, Alzheimer disease and associated disorders.

[2]  J. Weuve,et al.  Quantitative Bias Analysis for Collaborative Science. , 2018, Epidemiology.

[3]  Hiroko H. Dodge,et al.  Version 3 of the Alzheimer Disease Centers’ Neuropsychological Test Battery in the Uniform Data Set (UDS) , 2017, Alzheimer disease and associated disorders.

[4]  L. Schneider,et al.  Challenging Assumptions About African American Participation in Alzheimer Disease Trials. , 2017, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[5]  A. Agarwal,et al.  Discontinuation and non-publication of randomised clinical trials supported by the main public funding body in Switzerland: a retrospective cohort study , 2017, BMJ Open.

[6]  Howard J. Rosen,et al.  Willingness to Be a Brain Donor: A Survey of Research Volunteers From 4 Racial/Ethnic Groups , 2017, Alzheimer disease and associated disorders.

[7]  M. Weiner,et al.  The crisis in recruitment for clinical trials in Alzheimer's and dementia: An action plan for solutions , 2016, Alzheimer's & Dementia.

[8]  D. Needham,et al.  Updated systematic review identifies substantial number of retention strategies: using more strategies retains more study participants. , 2015, Journal of clinical epidemiology.

[9]  Ignacio Ferreira-González,et al.  Prevalence, characteristics, and publication of discontinued randomized trials. , 2014, JAMA.

[10]  W. Klunk,et al.  Disclosure of amyloid imaging results to research participants: Has the time come? , 2013, Alzheimer's & Dementia.

[11]  Keith A. Johnson,et al.  Appropriate Use Criteria for Amyloid PET: A Report of the Amyloid Imaging Task Force, the Society of Nuclear Medicine and Molecular Imaging, and the Alzheimer’s Association , 2013, The Journal of Nuclear Medicine.

[12]  J. Karlawish,et al.  Effect of study partner on the conduct of Alzheimer disease clinical trials , 2013, Neurology.

[13]  M. Mintun,et al.  Alzheimer’s disease therapeutic trials: EU/US task force report on recruitment, retention, and methodology , 2012, The journal of nutrition, health & aging.

[14]  B. Vellas Recruitment, retention and other methodological issues related to clinical trials for Alzheimer’s disease , 2012, The Journal of Nutrition, Health & Aging.

[15]  William J. Jagust,et al.  Predicting missing biomarker data in a longitudinal study of Alzheimer disease , 2012, Neurology.

[16]  J. Karlawish,et al.  Addressing the challenges to successful recruitment and retention in Alzheimer's disease clinical trials , 2010, Alzheimer's Research & Therapy.

[17]  R. Petersen,et al.  NIA-Funded Alzheimer Centers Are More Efficient than Commercial Clinical Recruitment Sites for Conducting Secondary Prevention Trials of Dementia , 2010, Alzheimer disease and associated disorders.

[18]  P. Harris,et al.  Research electronic data capture (REDCap) - A metadata-driven methodology and workflow process for providing translational research informatics support , 2009, J. Biomed. Informatics.

[19]  G. Gronseth,et al.  Invited Article: Lost in a jungle of evidence , 2008, Neurology.

[20]  Robert A Gross,et al.  Levels of evidence , 2008, Neurology.

[21]  Bruno Vellas,et al.  Predictive Factors of Attrition in a Cohort of Alzheimer Disease Patients , 2008, Neuroepidemiology.

[22]  Peter J Pronovost,et al.  Systematic review identifies number of strategies important for retaining study participants. , 2007, Journal of clinical epidemiology.

[23]  Joylee Wu,et al.  The National Alzheimer's Coordinating Center (NACC) Database: The Uniform Data Set , 2007, Alzheimer disease and associated disorders.

[24]  J. Morris,et al.  The Uniform Data Set (UDS): Clinical and Cognitive Variables and Descriptive Data From Alzheimer Disease Centers , 2006, Alzheimer disease and associated disorders.

[25]  J. Karlawish,et al.  The continuing unethical conduct of underpowered clinical trials. , 2002, JAMA.

[26]  G. Fillenbaum,et al.  Determinants of attrition in a natural history study of Alzheimer disease. , 1999, Alzheimer disease and associated disorders.

[27]  K Y Liang,et al.  Longitudinal data analysis for discrete and continuous outcomes. , 1986, Biometrics.