| Literature DB >> 34228129 |
Rema Raman1, Yakeel T Quiroz2,3, Oliver Langford1, Jiyoon Choi1, Marina Ritchie4, Morgan Baumgartner4, Dorene Rentz2,5, Neelum T Aggarwal6, Paul Aisen1, Reisa Sperling2,5, Joshua D Grill4,7,8.
Abstract
Importance: Underrepresentation of many racial/ethnic groups in Alzheimer disease (AD) clinical trials limits generalizability of results and hinders opportunities to examine potential effect modification of candidate treatments. Objective: To examine racial and ethnic differences in recruitment methods and trial eligibility in a multisite preclinical AD trial. Design, Setting, and Participants: This cross-sectional study analyzed screening data from the Anti-Amyloid in Asymptomatic AD study, collected from April 2014 to December 2017. Participants were categorized into 5 mutually exclusive ethnic/racial groups (ie, Hispanic, Black, White, Asian, and other) using participant self-report. Data were analyzed from May through December 2020 and included 5945 cognitively unimpaired older adults between the ages of 65 and 85 years screened at North American study sites. Main Outcomes and Measures: Primary outcomes included recruitment sources, study eligibility, and ineligibility reasons. To assess the probability of trial eligibility, regression analyses were performed for the likelihood of being eligible after the first screening visit involving clinical and cognitive assessments.Entities:
Mesh:
Year: 2021 PMID: 34228129 PMCID: PMC8261604 DOI: 10.1001/jamanetworkopen.2021.14364
Source DB: PubMed Journal: JAMA Netw Open ISSN: 2574-3805
Demographic Variables of Screened Participants by Racial/Ethnic Group
| Characteristic | Race/ethnicity, No. (%) | |||||
|---|---|---|---|---|---|---|
| Hispanic (N = 261) | Black (N = 323) | White (N = 5107) | Asian (N = 112) | Other (N = 142) | ||
| Age, mean (SD), y | 71.8 (4.8) | 71.3 (4.9) | 71.7 (4.9) | 72.5 (5.3) | 71.5 (5.0) | .18 |
| Education, mean (SD), y | 15.5 (3.2) | 15.4 (3.1) | 16.7 (2.8) | 16.9 (3.4) | 16.6 (3.3) | <.001 |
| Participant sex | ||||||
| Female | 163 (62.5) | 226 (70.0) | 2986 (58.5) | 60 (53.6) | 89 (62.7) | <.001 |
| Male | 98 (37.5) | 97 (30.0) | 2121 (41.5) | 52 (46.4) | 53 (37.3) | |
| Marital status | ||||||
| Married | 166 (63.6) | 122 (37.8) | 3655 (71.6) | 80 (71.4) | 86 (60.6) | <.001 |
| Widowed | 30 (11.5) | 51 (15.8) | 472 (9.2) | 16 (14.3) | 11 (7.7) | |
| Divorced | 48 (18.4) | 90 (27.9) | 686 (13.4) | 11 (9.8) | 19 (13.4) | |
| Never married | 9 (3.4) | 43 (13.3) | 206 (4.0) | 5 (4.5) | 9 (6.3) | |
| Unknown/other/NA | 8 (3.1) | 17 (5.3) | 88 (1.7) | 0 | 17 (12.0) | |
| Relationship to study partner | ||||||
| Spouse | 119 (45.6) | 86 (26.6) | 2960 (58.0) | 55 (49.1) | 70 (49.3) | <.001 |
| Adult child | 42 (16.1) | 42 (13.0) | 536 (10.5) | 20 (17.9) | 9 (6.3) | |
| Child-in-law | 3 (1.1) | 2 (0.6) | 20 (0.4) | 2 (1.8) | 0 | |
| Other relative | 18 (6.9) | 44 (13.6) | 231 (4.5) | 6 (5.4) | 2 (1.4) | |
| Friend/companion | 44 (16.9) | 93 (28.8) | 871 (17.1) | 15 (13.4) | 29 (20.4) | |
| Paid caregiver | 0 | 3 (0.9) | 1 (<0.1) | 0 | 0 | |
| Other | 3 (1.1) | 5 (1.5) | 92 (1.8) | 0 | 3 (2.1) | |
| Not applicable | 32 (12.3) | 48 (14.9) | 396 (7.8) | 14 (12.5) | 29 (20.4) | |
| Study partner sex | ||||||
| Female | 151 (57.9) | 181 (56.0) | 2783 (54.5) | 66 (58.9) | 65 (45.8) | <.001 |
| Male | 110 (42.1) | 142 (44.0) | 2324 (45.5) | 46 (41.1) | 77 (54.2) | |
| Recruitment source | ||||||
| No. | 258 | 315 | 5006 | 110 | 123 | |
| Internal | 154 (59.7) | 218 (69.2) | 2128 (42.5) | 61 (55.5) | 75 (61.0) | <.001 |
| Outside physician | 4 (1.5) | 6 (1.9) | 154 (3.1) | 1 (0.9) | 3 (2.4) | .77 |
| Earned media – national | 29 (11.2) | 15 (4.8) | 826 (16.5) | 11 (10.0) | 11 (8.9) | <.001 |
| Earned media – local | 41 (15.9) | 38 (12.1) | 1097 (21.9) | 23 (20.9) | 19 (15.4) | <.001 |
| Earned media - unknown | 9 (3.5) | 7 (2.2) | 186 (3.7) | 4 (3.6) | 5 (4.1) | .77 |
| Paid advertising | 10 (3.9) | 17 (5.4) | 362 (7.2) | 12 (10.9) | 4 (3.3) | .11 |
| Organization | 22 (8.5) | 31 (9.8) | 574 (11.5) | 4 (3.6) | 14 (11.4) | .12 |
| 53 (20.3) | 79 (24.5) | 1469 (28.8) | 17 (15.2) | 28 (19.7) | <.001 | |
Kruskal-Wallis test for continuous variables and Fisher exact test for categorical variables.
Multiple sources of recruitment were possible, so the categories are not mutually exclusive. A Fisher exact test with Holm adjusted P values was used for comparisons.
Frequency of Screen Failure by Criterion and Racial/Ethnic Group
| Characteristic | Total, No. | Race/ethnicity, No. (%) | ||||
|---|---|---|---|---|---|---|
| Hispanic | Black | White | Asian | Other | ||
| Total participants screened at ScV1 | 5945 | 261 | 323 | 5107 | 112 | 142 |
| ScV1 screen failures | ||||||
| Screen failures by specific inclusion criteria | 1683 (28.3) | 103 (39.5) | 147 (45.5) | 1338 (26.2) | 43 (38.4) | 52 (36.6) |
| MMSE score | 100 (1.7) | 16 (6.1) | 15 (4.6) | 60 (1.2) | 4 (3.6) | 5 (3.5) |
| Global CDR score at screening of 0 | 352 (5.9) | 26 (10.0) | 41 (12.7) | 265 (5.2) | 11 (9.8) | 9 (6.3) |
| Logical Memory II score | 718 (12.1) | 42 (16.1) | 62 (19.2) | 570 (11.2) | 21 (18.8) | 23 (16.2) |
| ≥1 of MMSE, CDR or Logical Memory II score | 1056 (17.8) | 68 (26.1) | 99 (30.7) | 825 (16.2) | 30 (26.8) | 34 (23.9) |
| Screen failures by specific exclusion criteria | ||||||
| Current serious or unstable illness | 161 (2.7) | 11 (4.2) | 10 (3.1) | 132 (3) | 2 (2) | 6 (4) |
| History of primary or recurrent malignant disease | 59 (1.0) | 2 (0.8) | 2 (0.6) | 54 (1.1) | 0 | 1 (0.7) |
| Clinically significant ECG | 106 (1.8) | 4 (1.5) | 7 (2.2) | 93 (1.8) | 1 (0.9) | 1 (0.7) |
| History of immunological disorders | 56 (0.9) | 5 (1.9) | 4 (1.2) | 43 (0.8) | 1 (0.9) | 3 (2.1) |
| Clinically significant lab abnormalities | 32 (0.5) | 4 (1.5) | 6 (1.9) | 20 (0.4) | 2 (1.8) | 0 |
| Total participants screened at ScV3 | 3937 (66.2) | 138 (52.9) | 156 (48.3) | 3507 (68.7) | 62 (55.4) | 74 (52.1) |
| ScV3 screen failures (PET scan showing nonelevated brain amyloid) | 2716 (45.7) | 100 (38.3) | 122 (37.8) | 2393 (46.9) | 53 (47.3) | 48 (33.8) |
Abbreviations: CDR, Clinical Dementia Rating; ECG, electrocardiogram; MMSE, Mini-Mental State Exam; ScV, screening visit.
Percentages are based on the total participants screened at ScV1 for a given race/ethnicity.
Limited to inclusion and exclusion criteria that accounted for at least 2% of the total screens within a group or over 50 participants overall.
Multivariable Logistic Regression Model
| Model 1: Eligibility after ScV1 (N = 5735) | Model 2: Elevated amyloid (N = 3875) | |||
|---|---|---|---|---|
| Odds ratio (95% CI) | Odds ratio (95% CI) | |||
| Age at screening, y | ||||
| Women | 0.96 (0.95-0.97) | <.001 | 1.05 (1.04-1.07) | <.001 |
| Years of education | 1.21 (1.08-1.36) | .001 | 1.00 (0.87-1.16) | >.99 |
| Racial/ethnic group | ||||
| White (reference group) | 1.05 (1.03-1.08) | <.001 | 0.99 (0.97-1.02) | .68 |
| Hispanic | 0.53 (0.41-0.69) | <.001 | 0.82 (0.55-1.19) | .31 |
| Black | 0.43 (0.34-0.54) | <.001 | 0.59 (0.39-0.86) | .008 |
| Asian | 0.56 (0.38-0.82) | .003 | 0.38 (0.17-0.73) | .007 |
Abbreviation: ScV, screening visit.
Actionable Recommendations to Improve Recruitment and Enrollment of Underrepresented Racial and Ethnic Groups in Preclinical AD Trials
| Recommendation | Rationale |
|---|---|
| Organizational structure | |
| Establish centralized prescreening databases | Prescreening databases permit real-time evaluation of outreach and screening efforts, allowing for the identification of the impact of centralized and local recruitment efforts while also assessing whether specific groups may be lost at varying levels of prescreening activities. |
| Establish a minimal data set for recruitment | Incorporating standardized data elements through the use of a minimal data set for recruitment ensures consistent data capture as it relates to race and ethnicity and may also enable collection of sociocultural factors (eg, education, occupation, socioeconomic status, neighborhood health variables), research attitudes, and other relevant constructs. |
| Provide earmarked funding for recruitment of participants from underrepresented groups | Line-item budgets do not typically offer differential reimbursement based on participant demographics. Offering specific support for sites to engage in diverse recruitment supports efforts to recruit underrepresented participants. |
| Select sites with diverse teams | Participants from underrepresented racial and ethnic groups may feel more comfortable communicating with and participating at sites with diverse study teams. Facilitate and reward sites for increasing the diversity of investigators. |
| Invest in community partnerships | Community-based organizations are often trusted gatekeepers. Providing funding to substantiate and strengthen relationships between sites and these organizations may enhance local recruitment of participants from underrepresented racial and ethnic groups. Engaging community advocates in study design and recruitment planning can ensure culturally sensitive designs. Identify participants from underrepresented groups who might serve as research ambassadors. |
| Study-specific approaches | |
| Develop a protocol-specific recruitment and retention plan | Comprehensive recruitment and retention study plans that prioritize diverse enrollment are essential to inclusivity and representation. |
| Develop specific recruitment strategies for unique underrepresented groups | Barriers to recruitment are likely to differ among unique communities. Unique strategies may be necessary to facilitate enrollment of underrepresented groups. This may require focus groups and market research to optimize recruitment messaging or may require more comprehensive strategies specific to groups. |
| Ensure that underrepresented groups are not disproportionately excluded by eligibility criteria | Broad inclusion criteria, adjusted for unique biological or cultural norms, may be necessary to optimally include participants from underrepresented groups. Performing data collection, especially cognitive testing, in non-English languages may be essential to ensuring inclusive enrollment. |
| Seek earned media opportunities to describe study recruitment needs | Earned media may increase awareness of the study through a trusted source. In particular, media stories through outlets serving underrepresented communities may offer promise. |
| Quantify site and central recruitment efforts and costs | Quantifying the costs associated with different recruitment strategies and cost per enrolled and randomized participant for each strategy can help future studies develop reasonable recruitment budgets. |