Clinical trials are essential for evaluating the safety and efficacy of potential disease modifying drugs for Alzheimer’s disease (AD) but face notable challenges.[1, 2] In particular, inefficient recruitment and challenging retention consistently delay AD trials and threaten their integrity. Barriers to recruitment include low awareness of trials, primary care physicians’ reluctance to refer patients, participants’ hesitancy to take investigational therapies and undergo invasive procedures, and strict inclusion criteria that may preclude participation for a large proportion of AD patients.[3–5] Resultantly, AD trial participants tend to be disproportionately white and well educated, compared to all AD patients in the United States.[4–6]
All AD clinical trials require participants to enroll with a study partner. The study partner is often the participant’s primary caregiver. Study partners are integral to AD clinical trial conduct—they may assist with informed consent, ensure protocol compliance, and serve as informants for cognitive, functional, and behavioral outcome measures. Most primary caregivers for people with dementia are non-spouses, in particular adult children of the person with dementia.[7–9] Adult children are more likely than spouses to be working, caring for families, and have other responsibilities besides caregiving. Thus, it may be more difficult for adult children to fulfill trial obligations in long-term studies.
We previously observed an association between study partner type and trial recruitment and retention in a meta-dataset composed of six trials funded by the National Institute of Aging (NIA) that enrolled participants with possible or probable AD. In these studies, 67% percent of patients enrolled with a spouse, 26% enrolled with an adult child study partner, and 7% enrolled with a study partner who was neither a spouse nor an adult child (herein “other”). Trial incompletion was higher among participants enrolling with a non-spouse study partner.
Early study exit due to dropout or death in clinical trials causes missing data. In the best case scenario this results in a loss of statistical precision for estimated treatment effects and reduced power. In the worst case scenario missing data can produce bias in the estimated treatment effect. Expert guidance on statistical handling of missing data is clear: the first priority should be to prevent its occurrence. Understanding predictors of early study exit will allow trial investigators to better design trials and to identify and support participants at increased risk for incompletion in order to prevent missing data.
Whether the relationship between AD study partner type and trial completion is homogenous across varying trial types and designs is unknown. The phases of the drug development process have unique objectives and therefore unique study designs. Additionally, site networks conducting industry-funded trials differ from academic trials and may enroll different patient populations. For example, NIA funded Mild Cognitive Impairment (MCI) trials may enroll larger proportions of apolipoprotein E ε4 (APOE4) carriers than do industry-funded trials. An analysis of a single MCI trial found that academic sites had lower rates of dropout compared to commercial sites. Alternatively, a recent review of an antidepressant clinical trial found no significant difference in dropout between academic and non-academic sites. Multinational trials are essential to regulatory goals and a thorough understanding of drug safety, but may carry increased risk of variability, including differences in the proportions of enrolled study partner dyad types by geographic region.[16, 17] Completion rates also may differ among global geographic regions in multinational trials.
The objective of this study was to quantify the relationship between study partner type and trial recruitment and retention in two multisite, industry-funded multinational registrational mild-to-moderate AD dementia trials and to assess whether previously found results in NIA-sponsored trials were replicated.