Abstract
Background:
Enrollment in non-oncology clinical trials is often challenging and social determinants that may serve as motivators or barriers to clinical trial enrollment are largely unexplored. We sought to assess engagement in non-oncology clinical trials with a focus on social determinants of health as barriers or motivators toward participation.
Methods:
A cross-sectional analysis of non-cancer respondents was conducted using the Health Information National Trends Survey (HINTS) administered in 2020. Our analytic cohort was comprised of respondents with no reported history of cancer. Our primary outcome of interest was trial engagement defined as receiving an invitation to participate in a clinical trial. Secondary outcomes included participation in a clinical trial and reported motivators and barriers to clinical trial participation.
Results:
A total of 3113 respondents with no reported history of cancer were included. Overall, 8.1% of respondents reported being invited to participate in a clinical trial. Among those invited to participate, 47.7% reported participating in a clinical trial. Respondents reported that clinical trial participation was motivated “somewhat” or “a lot” by “wanting to get better” (80.5%), “helping other people” (61.4%), “physician encouragement” (60.6%), “getting a chance to try new care” (60.2%), “family friend encouragement” (54.2%), or “getting paid” (50.0%). Overall, 82.5% of all respondents “don’t know anything” or have “a little knowledge” about clinical trials. Reported barriers to clinical trial participation including getting transportation, childcare or paid time off work (48.4%) and standard of care not covered by insurance (62.0%) influenced the decision to participate “somewhat” or “a lot.”
Conclusion:
Among a nationally representative sample, non-oncology clinical trial invitation is low, but participation among those invited is nearly 50%. This highlights the need for clinician engagement in clinical trials. Identifying modifiable social determinants of non-oncologic clinical trial participation may help promote improved engagement.
Keywords: non-oncology, clinical trial, engagement, motivator, barrier
1. Introduction
Clinical trials are critical to medical progress. Successful clinical trials are dependent upon insightful questions, thoughtful trial design, and patient participation.1 There are 384,708 active clinical trials registered on clinicaltrials.gov (as of 9/2021), the vast majority (78.3%, 304,718) of which are non-oncologic.2 These studies encompass a broad range of fields and include treatment, prevention, screening, and quality of life trials. Non-oncology clinical trials are frequently less complex and costly than oncology trials, recruit faster and have shorter trial cycle times,3 but enrollment for non-oncology trials remains challenging.4 For example, an 11-year review of heart failure clinical trials demonstrated enrollment rates did not change over time with a median of only 0.49 patients enrolled per month per site.5 Barriers to clinical trial enrollment include time and travel requirements associated with participation, risks, side effects, and fears that participation may impact current treatment.6,7 Further, many patients do not participate in placebo-controlled trials due to concern that they will not be stratified to a treatment arm.8 Poor recruitment has led to the discontinuation of many clinical trials.5,9–12 These findings illustrate a need to better understand participation in non-oncology clinical trials.
Despite the broad scope and substantial number of open non-oncology clinical trials, there is a paucity of literature summarizing non-oncology clinical trial participation rates, and the social determinants that impact participation. In this study, we aim to analyze rates of invitation to, and participation in, non-oncology clinical trials amongst the general population. Further, we assess social determinants that serve as motivators and barriers to clinical trial enrollment. We hypothesize that the most significant factor limiting non-oncologic clinical trial participation is invitation to participate in a clinical trial, while we expect that patients invited to participate will often enroll.
2. Methods
2.1. Data Source and Cohort Selection
The Health Information National Trends Survey (HINTS) is an ongoing cross-sectional survey administered by the National Cancer Institute (NCI). The HINTS queries a nationally representative sample of civilian, non-institutionalized adults (18 years or older) in the United States regarding health information, socioeconomic factors, clinical trial perceptions, and participation. Sampling in the HINTS is performed in two stages: 1) selection of a stratified assortment of households; and 2) selection of an individual adult from that household. In this study, the HINTS 5, cycle 4, conducted in 2020, was utilized. Our analytic cohort was comprised of adults who answered “no” to the question “have you ever been diagnosed as having cancer?”
2.2. Clinical Trials Engagement
For this study, the primary outcome was invitation to participate in a clinical trial. This was assessed by the survey question: “Have you ever been invited to participate in a clinical trial?” Secondary outcome included participation in a clinical trial. Among those respondents who endorsed being invited, participation was gauged using the question “Did you participate in the clinical trial?”. Responses included “Yes” or “No” or “Do Not Know”. Do Not Know was merged with No in the analyses.
2.3. Motivators to participating in a clinical trial
Assessment of motivators that may influence a respondent’s decision to participate in a clinical trial were assessed from the responses to the 6 questions: “Imagine that you had a health issue and you were invited to participate in a clinical trial for that issue.” 1.) “How much would getting a chance to try a new kind of care influence your decision to participate in the clinical trial?” 2.) “How much would getting paid to participate influence your decision to participate in the clinical trial?” 3.) “How much would wanting to get better influence your decision to participate in the clinical trial?” 4.) “How much would helping other people by participating influence your decision to participate in the clinical trial?” 5.) “How much would your doctor encouraging you to participate influence your decision to participate in the clinical trial?” 6.) “How much would your family and friends encouraging you to participate influence your decision to participate in the clinical trial?” Responses included: “Not at all”, “A little”, “Somewhat” and “A lot”. Responses were then consolidated into two groups including “Not at all” and “A little” vs. “Somewhat” and “A lot”.
2.4. Barriers to participating in a clinical trial
Assessment of barriers that may influence a respondent’s decision to participate in a clinical trial were assessed from the responses to the 3 questions: 1.) “How would you describe your level of knowledge about clinical trials?” Responses included “I don’t know anything about clinical trials”, “I know a little bit about clinical trials”, “I know a lot about clinical trials”. 2.) “Imagine that you had a health issue and you were invited to participate in a clinical trial for that issue. How much would getting support such as transportation, childcare, or paid time off from work influence your decision to participate in the clinical trial?” 3.) “How much would the standard care not being covered by your insurance influence your decision to participate in the clinical trial?” Responses included: “Not at all”, “A little” “Somewhat” and “A lot”. Responses were then categorized as “Not at all” and “A little” vs “Somewhat” and “A lot”.
2.5. Measures
The HINTS collects regular socioeconomic and demographic variables, which were included as covariates: Age (continuous variable); Sex (male and female); Marital Status (married before, now, and single); Education (High School (HS) or less, some college, or college degree and higher); Race (White, Black, and Other); Income (<$35,00; $35,000-<$75,000; and ≥$75,000); Income Feeling (living comfortably on present income, getting by on present income, finding it difficult on present income); Metro location (defined as area of residence for counties in metro areas using USDA Rural/Urban Designation (2013); E-device Ownership (owning a tablet or smartphone); Medicaid (Medicaid, medical assistance, or any kind of government-assistance plan); Regular Provider (response of “Yes” to the question “Is there a doctor/nurse/health provider that you see most often?”); Cardiovascular disease was based on answering “Yes” to the question “Has the doctor or other health professional ever told you that you had any of the following medical conditions: Diabetes or high blood sugar? High blood pressure or hypertension? A heart condition such as heart attack, angina, or congestive heart failure?”
2.6. Statistical Analysis
The study cohort was described with/without survey weights. Survey results were weighted to approximately adjust to the overall United States population, as recommended by the HINTS. To ensure valid inferences, replicate weight and variance estimation methods were used, according to the HINTS protocol, accounting for clustering of subjects, and nonresponse/noncoverage biases. Rates of invitation, participation, motivators and barriers were presented as frequencies and percentages, stratified by social determinants. Due to limited sample size, variables were selected based on univariate analysis with the outcome, substantive interests, and/or an a priori conceptual model. SAS version 9.4 survey procedures (SAS Institute) designed for large surveys, yielding nationally representative estimates was utilized for data analysis.
3. Results
3.1. Demographics
There were 3,113/3731 (90.8%, population weighted estimate 223,616,213/246,339,260) respondents who reported no cancer history included in the final study cohort. Mean age amongst these respondents was 63.3 years, and 57.9% of respondents were male (Table 1). Most patients were White (61.3%), lived in a metro area (88.6%), had non-Medicaid insurance (84.1%) and had a regular medical provider (60.4%).
Table 1.
Sociodemographic characteristics of suvey respondents.
| Weighted Frequency | |
|---|---|
| Age | 63.3 |
| Sex | |
| Female | 106,501,643 (50.1) |
| Male | 105,959,691 (49.9) |
| Married | |
| Before | 29,968,842 (13.7) |
| Now | 118,550,649 (54.1) |
| Single | 70,714,939 (32.3) |
| Education | |
| HS/less | 65,818,862 (30.0) |
| Some Coll | 86,463,187 (39.4) |
| Coll+ | 67,416,822 (30.7) |
| Race | |
| White | 133,968,233 (61.3) |
| Black | 26,709,543 (12.2) |
| Other | 57,871,124 (26.5) |
| Income | |
| <$35k | 53,783,241 (25.8) |
| $35–74K | 64,122,066 (30.7) |
| $75k+ | 90,953,148 (43.5) |
| Income Feeling | |
| Comfortable | 77,752,863 (36.1) |
| Difficult | 48,363,105 (22.5) |
| Getting By | 88,990,423 (41.4) |
| Metro | |
| No | 25,454,077 (11.4) |
| Yes | 198,162,136 (88.6) |
| E-Device | |
| No | 23,678,916 (10.6) |
| Yes | 199,937,296 (89.4) |
| Medicaid | |
| No | 182,948,163 (84.1) |
| Yes | 34,626,040 (15.9) |
| Regular Provider | |
| No | 87,606,455 (39.6) |
| Yes | 133,495,946 (60.4) |
| Cardiovascular Disease | |
| No | 117,961,677 (52.8) |
| Yes | 105,654,536 (47.2) |
3.2. Clinical Trial Invitation and Participation
Overall, rate of invitation to participate in a clinical trial was 8.1%. Amongst those invited to participate in a clinical trial, participation rate was 47.7%. Patients with higher education attainment (11.0%, p=0.017), Black race (14.4%, p=0.006), residence in a metropolitan area (8.6%, p=0.011), Medicaid insurance (8.6%, p=0.005), a regular provider (10.3%, p=0.002), and cardiovascular disease (10.2%, p=0.02) more frequently received an invitation to participate. Respondents of White race (52.7%, p=0.03), and those with non-Medicaid insurance (55.3%, p=0.019) participated more often.
3.3. Motivators to Clinical Trial Participation
Respondents reported that clinical trial participation was motivated “somewhat” or “a lot” by “wanting to get better” (80.5%), “helping other people” (61.4%), “physician encouragement” (60.6%), “getting a chance to try new care” (60.2%), “family friend encouragement” (54.2%), or “getting paid” (50.0%).
Respondents of White race (68.7%, p=0.002), those reporting E-device use (67.1%, p=0.015), and those with a regular provider (70.7%, p=0.0002) more frequently reported participation motivated by “getting a chance to try new care.” Respondents who were currently married (90.8%, p=0.0027), with educational attainment of college or more (93.6%, p=0.0017), with higher income level (93.0%, p=0.001) or those who reported E-device use (90.1%, p<0.0001) more frequently reported that they were motivated to participate “somewhat” or “a lot” by “wanting to get better.” Respondents who were single (66.0%, p<0.0001), those who reported income feeling as “difficult” on present income (64.9%, p=0.003), those who resided in a metro area (55.7%, p=0.0055), those who reported E-device use (56.6%, p<0.0001), and those with cardiovascular disease (49.9%, p=0.0002) reported being motivated “somewhat” or “a lot” by “getting paid” (Table 3). Income and race were not associated with participation because of financial incentivization.
Table 3.
Frequency, weighted frequency, and weigheted percent responses to motivators to clinical trial participation (Getting A Chance To Try New Care, Wanting To Get Better, Getting Paid)
| Getting A Chance To Try New Care¶ | Wanting To Get Better¶ | Getting Paid¶ | |||||||
|---|---|---|---|---|---|---|---|---|---|
| A Little + Not At All | A lot + Somewhat | P-value | A Little + Not At All | A lot + Somewhat | P-value | A Little + Not At All | A lot + Somewhat | P-value | |
| Frequency (Weighted Percent) | Frequency (Weighted Percent) | Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | ||||
| Overall | |||||||||
| 73,228,701 (30.8) | 143,078,686 (60.2) | 24,684,463 (10.4) | 191,309,035 (80.5) | 96,611,021 (40.8) | 118,346,224 (50.0) | ||||
| Sex | |||||||||
| Female | 32,568,810 (31.8) | 69,962,475 (68.2) | 0.36 | 12,232,421 (11.9) | 90,137,414 (88.1) | 0.31 | 49,525,290 (48.5) | 52,607,220 (51.5) | 0.19 |
| Male | 36,049,184 (34.9) | 67,302,993 (65.1) | 10,260,561 (9.9) | 93,000,581 (90.1) | 41,788,319 (40.7) | 60,764,702 (37.0) | |||
| Married | |||||||||
| Before | 8,444,648 (30.6) | 19,195,864 (69.4) | 0.17 | 5,078,838 (18.3) | 22,670,460 (81.7) | 0.0027 | 14,321,594 (52.0) | 13,224,204 (48.0) | <0.0001 |
| Now | 37,028,442 (32.2) | 77,821,895 (68.8) | 10,605,684 (9.2) | 104,358,847 (90.8) | 56,835,910 (49.9) | 57,132,792 (50.1) | |||
| Single | 26,244,453 (37.6) | 43,534,406 (62.4) | 8,105,539 (11.7) | 61,332,398 (88.3) | 23,671,761 (34.0) | 45,868,198 (66.0) | |||
| Education | |||||||||
| HS/less | 21,184,159 (34.5) | 40,151,081 (59.9) | 0.25 | 10,517,789 (17.1) | 50,872,028 (82.9) | 0.0017 | 29,219,900 (48.3) | 31,279,144 (51.7) | 0.09 |
| Some Coll | 30,595,552 (36.1) | 54,071,112 (63.9) | 9,165,035 (10.8) | 75,346,944 (89.2) | 36,338,624 (43.1) | 47,955,847 (56.9) | |||
| Coll+ | 19,993,342 (29.9) | 46,765,102 (70.1) | 4,246,588 (6.4) | 62,289,797 (93.6) | 29,456,855 (44.2) | 37,262,621 (55.8) | |||
| Race | |||||||||
| White | 41,091,984 (31.3) | 90,303,309 (68.7) | 0.002 | 12,591,414 (9.6) | 118,440,089 (90.4) | 0.073 | 61,055,013 (46.7) | 69,718,789 (56.0) | 0.60 |
| Black | 8,818,005 (35.0) | 16,375,715 (65.0) | 3,189,008 (12.8) | 21,678,125 (87.2) | 10,670,670 (42.9) | 14,208,429 (57.1) | |||
| Other | 21,394,091 (38.7) | 33,830,481 (61.3) | 8,201,418 (14.8) | 47,319,005 (85.2) | 22,420,247 (40.8) | 32,543,464 (59.2) | |||
| Income | |||||||||
| <$35k | 17,453,363 (34.2) | 33,586,781 (65.8) | 0.56 | 8,301,018 (16.4) | 42,349,846 (83.6) | 0.001 | 22,269,791 (44.0) | 28,397,039 (56.0) | 0.201 |
| $35–74K | 21,819,952 (35.3) | 39,906,908 (64.7) | 7,245,828 (11.6) | 55,129,044 (88.4) | 25,712,471 (41.7) | 36,013,543 (58.3) | |||
| $75k+ | 28,378,528 (31.5) | 61,601,929 (68.5) | 6,271,489 (7.0) | 83,386,499 (93.0) | 40,640,982 (45.4) | 48,829,954 (54.6) | |||
| Income Feeling | |||||||||
| Comfortable | 27,453,549 (36.3) | 48,091,079 (63.7) | 0.39 | 9,694,349 (12.7) | 66,382,393 (87.3) | 0.29 | 39,337,116 (52.3) | 35,936,145 (47.7) | 0.003 |
| Difficult | 14,323,945 (30.7) | 32,323,190 (69.3) | 5,562,958 (12.0) | 40,712,218 (88.0) | 16,345,183 (35.1) | 30,279,278 (64.9) | |||
| Getting By | 27,860,875 (32.2) | 58,539,699 (67.8) | 8,046,333 (9.4) | 77,917,350 (90.6) | 36,546,905 (42.7) | 48,996,832 (57.3) | |||
| Metro | |||||||||
| No | 10,072,016 (40.8) | 14,586,302 (59.2) | 0.12 | 2,916,256 (11.8) | 21,721,808 (88.2) | 0.87 | 12,171,539 (50.1) | 12,099,007 (49.9) | 0.0055 |
| Yes | 63,156,685 (33.0) | 128,492,384 (67.0) | 21,768,206 (11.4) | 169,587,228 (88.6) | 84,439,482 (44.3) | 106,247,217 (55.7) | |||
| E-Device | |||||||||
| No | 8,920,502 (43.4) | 11,627,561 (56.6) | 0.015 | 5,328,827 (25.4) | 15,667,191 (74.6) | <0.0001 | 12,076,634 (60.5) | 7,901,128 (39.5) | <0.0001 |
| Yes | 64,308,199 (32.9) | 131,451,125 (67.1) | 19,355,635 (9.9) | 175,641,844 (90.1) | 84,534,387 (43.4) | 110,445,097 (56.6) | |||
| Medicaid | |||||||||
| No | 60,367,906 (33.9) | 117,553,390 (66.1) | 0.92 | 18,865,933 (10.6) | 159,287,163 (89.4) | 0.063 | 80,409,074 (45.4) | 96,838,393 (54.6) | 0.12 |
| Yes | 11,275,434 (34.2) | 21,655,993 (65.8) | 5,004,088 (15.5) | 27,348,891 (84.5) | 13,582,991 (41.7) | 9,392,163 (58.3) | |||
| Regular Provider | |||||||||
| No | 34,236,945 (40.8) | 49589282 (59.2) | 0.0002 | 10,967,871 (13.0) | 73,193,441 (87.0) | 0.085 | 33,938,278 (41.0) | 48,857,150 (59.0) | 0.11 |
| Yes | 38,162,712 (29.3) | 91,977,812 (70.7) | 13,109,206 (10.1) | 116,416,902 (89.9) | 61,725,633 (47.5) | 68,123,984 (52.5) | |||
| Cardiovascular Disease | |||||||||
| No | 39,971,328 (34.7) | 75,105,042 (65.3) | 0.49 | 13,278,789 (11.5) | 101,730,627 (88.5) | 0.88 | 67,946,700 (59.4) | 46,396,335 (40.6) | 0.0002 |
| Yes | 33,257,373 (32.9) | 67,973,644 (67.1) | 11,405,674 (11.3) | 89,578,409 (88.7) | 50,399,525 (50.1) | 50,214,686 (49.9) | |||
A lot, and Somewhat, vs. A little, Not At All
Respondents reporting motivation on the basis of “helping other people” were more often female (70.2%, p=0.029), had higher level of education (74.8%, p=0.006), White (68.9%, p=0.03), and used E-device (68.8%, p=0.003). Respondents who reported “physician encouragement” as a motivator more frequently reported being married (69.8%, p=0.035), reported White race (72.7%, p<0.0001), had non-Medicaid insurance (67.8%, p=0.02) or had a regular provider (72.9%, p<0.0001). Those who reported “family and friend encouragement” as the motivating factor for enrollment in a clinical trial were more frequently White (63.1%, p=0.007) or report E-device use (60.0%, p=0.01) (Table 4).
Table 4.
Frequency, weighted frequency, and weigheted percent responses to motivators to clinical trial participation (Helping Other People, Doctor Encourage, Family and Friends Encourage)
| Helping Other People¶ | Doctor Encourage¶ | Family and Friends Encourage¶ | |||||||
|---|---|---|---|---|---|---|---|---|---|
| A Little + Not At All | A lot + Somewhat | P-value | A Little + Not At All | A lot + Somewhat | P-value | A Little + Not At All | A lot + Somewhat | P-value | |
| Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | ||||
| Overall | |||||||||
| 70,684,211 (29.5) | 147,214,317 (61.4) | 72,407,842 (30.3) | 144,723,723 (60.6) | 87,402,585 (36.7) | 128,915,912 (54.2) | ||||
| Sex | |||||||||
| Female | 30,965,969 (29.8) | 73,005,723 (70.2) | 0.029 | 32,435,296 (31.5) | 70,695,108 (68.5) | 0.34 | 42,186,592 (35.5) | 60,660,849 (59.0) | 0.43 |
| Male | 35,428,557 (34.3) | 67,994,460 (65.7) | 35,108,144 (34.0) | 68,282,614 (66.0) | 39,528,007 (38.3) | 63,584,901 (61.7) | |||
| Married | |||||||||
| Before | 24,986,019 (30.0) | 19,606,426 (70.0) | 0.17 | 9,403,140 (33.3) | 18,809,731 (66.7) | 0.035 | 13,316,338 (48.0) | 14,439,859 (52.0) | 0.24 |
| Now | 35,643,839 (30.6) | 80,702,825 (69.4) | 34,886,573 (30.2) | 80,655,618 (69.8) | 43,689,052 (37.8) | 71,750,327 (62.2) | |||
| Single | 24,757,115 (35.7) | 44,675,058 (64.3) | 26,695,348 (38.4) | 42,842,683 (61.6) | 28,666,526 (41.3) | 40,700,744 (58.7) | |||
| Education | |||||||||
| HS/less | 24,986,019 (39.7) | 37,978,189 (60.3) | 0.006 | 24,859,903 (39.7) | 37,683,275 (60.3) | 0.01 | 25,966,291 (42.0) | 35,801,617 (58.0) | 0.63 |
| Some Coll | 26,943,262 (31.8) | 57,768,232 (62.5) | 27,923,852 (33.0) | 56,790,269 (67.0) | 35,690,098 (42.2) | 48,947,256 (57.8) | |||
| Coll+ | 16,805,723 (25.2) | 49,799,810 (74.8) | 18,236,764 (27.5) | 48,023,992 (72.5) | 24,149,525 (36.4) | 42,253,071 (63.6) | |||
| Race | |||||||||
| White | 40,951,415 (31.1) | 90,514,806 (68.9) | 0.03 | 35,903,769 (27.3) | 95,679,404 (72.7) | <0.0001 | 48,440,596 (36.9) | 83,011,577 (63.1) | 0.007 |
| Black | 8,290,574 (32.8) | 17,133,008 (67.4) | 11,022,593 (44.1) | 13,966,872 (55.9) | 12,310,379 (49.4) | 12,616,095 (50.6) | |||
| Other | 19,051,450 (33.8) | 37,309,141 (66.2) | 24,188,274 (43.2) | 31,830,431 (56.8) | 24,261,444 (43.7) | 31,221,004 (56.3) | |||
| Income | |||||||||
| <$35k | 18,164,834 (35.2) | 33,440,196 (64.8) | 0.26 | 18,681,818 (36.3) | 32,723,393 (63.7) | 0.09 | 22,720,722 (44.6) | 28,186,995 (55.4) | 0.07 |
| $35–74K | 18,222,873 (29.1) | 44,456,371 (70.9) | 20,574,376 (32.3) | 41,274,644 (66.7) | 24,937,629 (40.3) | 36,969,739 (59.7) | |||
| $75k+ | 28,131,384 (31.2) | 61,963,853 (68.8) | 27,641,323 (30.6) | 62,555,111 (69.4) | 33,157,119 (36.9) | 56,805,085 (63.1) | |||
| Income Feeling | |||||||||
| Comfortable | 25,863,872 (34.0) | 50,252,371 (66.0) | 0.28 | 25,442,888 (33.5) | 50,446,028 (66.5) | 0.34 | 30,211,871 (40.0) | 45,408,704 (60.0) | 0.06 |
| Difficult | 15,138,014 (32.4) | 31,610,811 (67.6) | 16,813,258 (36.1) | 29,769,326 (63.9) | 20,153,671 (43.5) | 26,137,469 (56.5) | |||
| Getting By | 25,660,045 (29.5) | 61,387,325 (70.5) | 26,926,855 (31.0) | 60,016,017 (69.0) | 33,163,808 (38.3) | 53,423,829 (61.7) | |||
| Metro | |||||||||
| No | 9,696,116 (39.4) | 14,916,543 (60.6) | 0.44 | 7,016,971 (28.3) | 17,755,229 (71.7) | 0.39 | 9,570,423 (38.7) | 15,152,825 (61.3) | 0.8342 |
| Yes | 60,988,095 (31.6) | 132,297,775 (68.4) | 65,390,870 (34.0) | 98,437,519 (66.0) | 77,832,161 (40.6) | 113,763,088 (59.4) | |||
| E-Device | |||||||||
| No | 9,364,320 (43.8) | 12,004,812 (56.2) | 0.003 | 8,671,765 (40.6) | 12,695,297 (59.4) | 0.07 | 9,267,851 (44.5) | 11,536,350 (55.5) | 0.01 |
| Yes | 61,319,892 (31.2) | 135,209,505 (68.8) | 63,736,077 (32.6) | 132,028,426 (67.4) | 78,134,735 (40.0) | 117,379,564 (60.0) | |||
| Medicaid | |||||||||
| No | 57,682,150 (32.2) | 121,483,439 (67.8) | 0.09 | 57,451,902 (32.2) | 121,228,131 (67.8) | 0.02 | 70,387,440 (39.6) | 107,530,977 (60.4) | 0.17 |
| Yes | 11,188,803 (33.7) | 21,996,208 (66.3) | 13,529,661 (41.0) | 19,469,946 (59.0) | 15,103,383 (45.9) | 17,794,474 (54.1) | |||
| Regular Provider | |||||||||
| No | 30,476,163 (35.7) | 54,873,437 (64.3) | 0.25 | 35917744 (42.6) | 48,486,374 (57.4) | <0.0001 | 37,352,080 (44.3) | 46,956,008 (55.7) | 0.09 |
| Yes | 39,295,654 (30.2) | 90,885,279 (69.8) | 35,291,232 (27.1) | 95,042,681 (72.9) | 17,342,776 (13.4) | 81,913,095 (63.2) | |||
| Cardiovascular Disease | |||||||||
| No | 79,426,866 (68.5) | 36,585,671 (31.5) | 0.11 | 74,167,959 (64.4) | 41,052,475 (35.6) | 0.19 | 69,485,790 (60.3) | 45,794,982 (39.7) | 0.15 |
| Yes | 67,787,451 (66.5) | 34,098,541 (33.5) | 70,555,763 (69.2) | 31,355,366 (30.8) | 59,430,124 (58.8) | 41,607,602 (41.2) | |||
A lot, and Somewhat, vs. A little, Not At All
3.4. Barriers to Clinical Trial Participation
Barriers to clinical trial enrollment explored in the HINTS survey include knowledge, or lack thereof, regarding clinical trials (82.5% report “don’t know anything” or “a little knowledge”), difficulty getting transportation, childcare or paid time off from work (48.4%), or standard care not being covered by patient insurance (62.0%). For respondents who reported limited knowledge (“don’t know anything” or “a little”) of clinical trials, most were noted to have a lower level of educational attainment. Overall, 97.9% and 94.3% of those with “high school” or “some college” level of education versus 79.5% of those with “college or more” education reported limited knowledge of clinical trial options (p<0.0001). Similarly, individuals with lower incomes (p<0.0001) and those who did not use E-devices (p=0.0004) reported less knowledge about clinical trials.
Respondents who reported “getting transportation, childcare or paid time off work” as a barrier to clinical trial participation were more often single (60.2%, p=0.009), reported their income feeling as “difficult” on present income (63.2%, p<0.0001) or had cardiovascular disease (49.9%, p=0.0035). Further, these respondents frequently reported E-device use (54.4%, p=0.0004). Finally, respondents reporting “standard care not being covered by insurance” as a barrier to clinical trial participation reported higher educational attainment (75.9%, p<0.0001), White race (71.2%, p=0.025), had higher income (75.4%, p<0.0001), reported E-device use (69.9%, p<0.0001), had non-Medicaid insurance (70.3%, p=0.0006), or had a regular provider (71.2%, p=0.026).
4. Discussion
Poor participation rates limit the success of non-oncology clinical trials, with a significant number of trials requiring extensions to meet accrual targets or closing due to under-recruitment.13 Prior studies have examined factors that motivate participation in clinical trials. These include contributing to the health of others, opportunities to access new care, or scientific curiosity.14 Limited understanding or knowledge of clinical trials and patient factors serve as barriers that limit participation.15 In this study, we utilize the HINTS, a population-based questionnaire, to characterize invitation to and participation rates in non-oncologic clinical trials. Invitation rates to clinical trials were low, with less than 10% of patients receiving an invitation to participate in a clinical trial underscoring the need for health care providers to be educated regarding the benefits of clinical trials. Our study findings corroborate a survey of nearly 2,000 health care providers, in which ~750 physicians and ~1,250 nurses reported extremely low clinical trial referral rates (0.2% and 0.04% of annual patients seen, respectively).16 Outside of this survey study, there are a paucity of studies evaluating engagement in non-oncology trials, making comparisons to our results challenging. Prior studies have identified the poor referral process as a critical barrier.17,18 One group demonstrated that an electronic health record-based alert system improved recruitment rates in an active clinical trial,19 and a more recent study demonstrated that artificial intelligence could be used to optimize the process of determining clinical trial eligibility.20
In our study, when invited, nearly half of patients elected to participate, demonstrating that lack of invitation to a non-oncologic clinical trial may be a primary obstacle to enrollment and that invitation may serve to significantly increase overall participation. Our study findings that nearly half of patients invited to enroll in a clinical trial subsequently participated support prior clinical trials enrollment data. For example, an analysis of 15 randomized controlled trials in a single institution study reported a 58% participation rate amongst patients screened for studies pertaining to cardiovascular disease.6 Nevertheless, participation rates remain low in comparison to the rate of individuals perceiving clinical trials to be important (~85%).14
Racial and ethnic minorities have been underrepresented in clinical trials.21,22 Recognizing our unadjusted analysis and small sample size, we found Black respondents reported an invitation to participate in a clinical trial at higher rates, while White respondents participated more often. This is converse to previous studies, in which Black patients were enrolled in clinical trials less frequently than White patients.21,22 Nevertheless, the increased invitation rate may reflect the effort to improve minority representation through policy and advocacy including amendment of the Health Revitalization Act and U.S. Food and Drug Administration guidance.23 In non-oncology clinical trials, the increased invitation rate may also reflect a difference in disease prevalence, as many chronic diseases are more prevalent in underrepresented minority populations.24 Despite legislative efforts, Black participation in clinical trials remains limited.21 This may be due, in part, to mistrust in the medical research system amongst Black patients. Nevertheless, this is a multifaceted issue that incorporates systemic factors, and mistrust alone likely represents an oversimplified explanation.15 Further, a recent study reported similar clinical trial participation rates between White and Black patients,15 and in another study, Black and White respondents reported similar levels of mistrust in the clinical trial system.25
Geographic location also influences clinical trial participation.26 We found that patients in non-metro areas were less likely to receive an invitation to participate in a research study, while participating at a higher rate when invited, although the latter finding was not statistically significant. This is concordant with a study of rural patients in South Carolina who reported no difference in willingness to participate, but felt that access to clinical trials was limited by geographic location and awareness.26 Similarly, our study demonstrated that higher educational attainment was associated with higher rate of being invited to participate in a clinical trial. This has also been demonstrated in the literature, as Saphner et al. noted that absence of a high school and absence of a college degree were both associated with lower rates of clinical trial participation.27
Various prior studies have examined factors that motivate clinical trial participation, which include altruism, monetary incentives, and scientific curiosity.28,29 In this study, respondents reported motivation to participate in non-oncologic trials on the basis of wanting to get better, trying new care, altruism, encouragement from a doctor or friend/family member, or financial incentivization. Our findings are comparable to those of other studies carried out in various diseases. In a study regarding motivators for participation in a clinical trial amongst patients with Alzheimer’s or their caregivers, a majority of respondents reported desire to participate on the basis of helping others or themselves (>80%), while fewer respondents reported financial incentivization as a motivator (~30%).30 Another study including patients with inflammatory bowel disease highlighted the physician-patient relationship as a motivator for participating, while altruism was also reported to influence patients to enroll.31 In a systematic review of studies surveying clinical trial participation motivators amongst healthy volunteers, authors concluded that financial incentives serve as a primary motivator.28 In one study, incentivization was demonstrated to improve participation rates by 22% as compared to no incentive.32 Notably, Walter et al. assessed a nationally representative sample and demonstrated that Hispanic participants were noted to request higher payment to participate in clinical research, while non-Hispanic Whites and non-Hispanic Blacks were noted to request comparable compensation. The study also noted that differences in income were not associated with increased willingness to participate on the basis of receiving financial incentives.33 In our study, we found no association between race or income level and financial incentive motivating trial participation.
Regarding barriers to clinical trial participation, a significant number of respondents (82.5%) reported that they “don’t know anything” or know “a little” about clinical trials, which highlights an area of needed education and opportunity for improvement. Additionally, these results are in line with a survey questionnaire including responses from ~12,500 individuals in which a majority of respondents (~41%) were unable to name an institution conducting a clinical trial, and many reported that clinical trials were rarely discussed as a treatment option.13 In our study, patients with lower levels of educational attainment or income levels less frequently reported clinical trial knowledge. However, a recent study assessing the impact of an educational tool on clinical trial enrollment amongst newly diagnosed cancer patients demonstrated no improvement in enrollment suggesting this may be a challenging barrier to address.34 Logistical concerns regarding transportation, childcare, and absence from work impacted clinical trial participation less often. These findings may be population dependent, as the study by Durant et al. found that, amongst Black patients, free transportation to trial site, or concordant race amongst the clinical trial team mitigated participation rates.25 Interestingly, out-of-pocket costs associated with standard care were reported to serve as a barrier for wealthier, more educated patients with non-Medicaid insurance. This may be attributable to Medicare patients, who are often no longer eligible for copayment assistance programs upon transitioning to Medicare from commercial insurance after age 65. However, this is speculative and the factors underlying these findings require further study.
This study is strengthened by the use of a validated, nationally representative, population-weighted survey. However, use of the HINTS produces limitations. As the survey is designed to be cross-sectional, inferences regarding causal relationships cannot be made from these results. Additionally, the HINTS does not collect data regarding the specific type of clinical trial offered to patients. Similarly, given the dataset constraints limiting information regarding trial type, patients with a history of cancer who were invited to participate in a non-oncologic trial would be excluded from this analysis. Unfortunately, granular data regarding past medical history of respondents were limited to self-reported history of cardiovascular disease. A more detailed understanding of this information would likely aid in contextualizing the clinical trial invitation rate. Furthermore, due to the design of the HINTS as a questionnaire, survey biases including selection and response biases must be considered. Despite the design of the HINTS, which serves to minimize the effects of these biases, there may be implications on survey results.
This study is unique in that we assess invitation/participation rates, and analyze social determinants impacting participation in non-oncologic trials on a population-basis. We demonstrate that the most significant obstacle to clinical trial participation is likely low invitation (referral rates) to clinical trials by health care providers. Future studies should aim to further address causes of low referral rates. Furthermore, additional work is required to assess the individual motivators and barriers to non-oncologic clinical trial participation to further characterize and understand the impact of these factors on enrollment. This information may be used to improve clinical trial design and infrastructure to encourage improved participation, maximizing patient accrual and generalizability.
Using a nationally representative survey, this study demonstrates a low rate of invitation to participate in non-oncologic clinical trials, with a nearly 50% participation rate amongst invited respondents. Assessment of motivators and barriers may serve to provide opportunities to improve patient accrual in non-oncologic clinical trials.
Table 2.
Clinical trial invitation, participation, and discussion as a cancer treatment option among survey respondents.
| Have you ever been invited to participate in a clinical trial? Yes | Did you participate in the clinical trial? Yes | |||
|---|---|---|---|---|
| Weighted Frequency | P-Value | Weighted Frequency | P-Value | |
| Overall | ||||
| 17,892,352 (8.1) | 8,505,175 (47.7) | |||
| Sex | ||||
| Female | 8,257,409 (7.8) | 0.87 | 3,654,114 (44.5) | 0.68 |
| Male | 8,010,986 (7.6) | 3,946,162 (49.3) | ||
| Married | ||||
| Before | 2,134,757 (7.3) | 0.27 | 856,682 (40.1) | 0.36 |
| Now | 8,561,868 (7.3) | 4,650,325 (54.6) | ||
| Single | 6,715,325 (9.5) | 2,665,059 (39.7) | ||
| Education | ||||
| HS/less | 3,551,602 (5.5) | 0.017 | 1,275,500 (36.2) | 0.27 |
| Some Coll | 6,422,508 (7.5) | 2,704,190 (42.1) | ||
| Coll+ | 7,410,780 (11.0) | 4,168,365 (56.4) | ||
| Race | ||||
| White | 9,635,858 (7.3) | 0.006 | 5,082,678 (52.7) | 0.030 |
| Black | 3,825,725 (14.4) | 1,003,369 (26.4) | ||
| Other | 3,531,964 (6.1) | 2,053,440 (58.5) | ||
| Income | ||||
| <$35k | 4,737,620 (8.9) | 0.65 | 1,849,724 (39.0) | 0.47 |
| $35–74K | 4,883,931 (7.7) | 2,449,439 (50.6) | ||
| $75k+ | 6,458,836 (7.1) | 3,456,479 (53.5) | ||
| Income Feeling | ||||
| Comfortable | 5,333,625 (6.9) | 0.38 | 2,496,657 (46.8) | 0.20 |
| Difficult | 4,581,988 (9.6) | 1,632,468 (35.8) | ||
| Getting By | 7,041,536 (8.0) | 3,756,216 (53.5) | ||
| Metro | ||||
| No | 949,831 (3.8) | 0.011 | 663,691 (69.9) | 0.22 |
| Yes | 16,942,521 (8.6) | 7,841,484 (46.4) | ||
| E-Device | ||||
| No | 1,659,430 (7.2) | 0.64 | 596,611 (36.0) | 0.30 |
| Yes | 16,232,923 (8.2) | 7,908,564 (48.9) | ||
| Medicaid | ||||
| No | 12,793,635 (7.0) | 0.005 | 7,058,381 (55.3) | 0.019 |
| Yes | 4,534,383 (13.2) | 1,292,700 (28.5) | ||
| Regular Provider | ||||
| No | 4,207,867 (4.8) | 0.002 | 2,438,644 (58.0) | 0.18 |
| Yes | 13,652,640 (10.3) | 6,062,046 (44.5) | ||
| Cardiovascular Disease | ||||
| No | 7,233,593 (6.2) | 0.02 | 3,645,234 (50.6) | 0.46 |
| Yes | 10,658,760 (10.2) | 4,859,941 (45.7) | ||
Table 5.
Frequency, weighted frequency, and weigheted percent responses to barriers to clinical trial participation (clinical trial knowledge, getting transportation, childcare, or paid time off work, and standard care not being covered by your insurance)
| Clinical Trial Knowledge* | Getting Transportation, Childcare, or Paid Time Off Work¶ | Standard Care Not Being Covered By Your Insurance¶ | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Don’t Know Anything + A little | Alot | P-value | A Little + Not At All | A lot + Somewhat | P-value | A Little + Not At All | A lot + Somewhat | P-value | ||
| Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | Weighted Frequency | |||||
| Overall | ||||||||||
| 200,925,707 (82.5) | 20,379,890 (8.4) | 100,909,510 (42.6) | 114,794,409 (48.4) | 68,758,132 (28.9) | 147,310,025 (62.0) | |||||
| Sex | ||||||||||
| Female | 95,570,555 (90.9) | 9,552,522 (9.1) | 47,781,443 (46.6) | 54,742,095 (53.4) | 0.36 | 31,665,374 (30.9) | 70,835,083 (69.1) | 0.65 | ||
| Male | 95,266,720 (90.4) | 10,128,789 (9.6) | 0.71 | 47,709,165 (46.4) | 55,076,666 (53.6) | 33,553,262 (32.5) | 69,628,029 (67.5) | |||
| Married | ||||||||||
| Before | 27,112,927 (93.0) | 2,025,432 (7.0) | 0.49 | 14,178,986 (51.4) | 13,423,525 (48.6) | 0.009 | 10,575,076 (38.2) | 17,083,359 (61.8) | 0.11 | |
| Now | 106,747,939 (90.7) | 10,972,026 (9.3) | 57,454,905 (49.9) | 57,664,302 (50.1) | 33,367,120 (29.1) | 81,418,085 (70.9) | ||||
| Single | 63,123,921 (89.9) | 7,111,631 (10.1) | 27,547,542 (39.8) | 41,642,607 (60.2) | 23,079,233 (33.1) | 46,581,230 (66.9) | ||||
| Education | ||||||||||
| HS/less | 63,343,196 (97.9) | 1,384,493 (2.1) | <0.0001 | 28,464,416 (46.6) | 32,642,798 (53.4) | 0.99 | 26,584,010 (43.2) | 34,897,422 (56.8) | <0.0001 | |
| Some Coll | 80808221 (94.3) | 4856580 | 39,966,642 (47.2) | 44,730,537 (52.8) | 24,528,196 (29.0) | 60,013,663 (71.0) | ||||
| Coll+ | 53,389,017 (79.5) | 13,776,812 (20.5) | 30,798,663 (46.4) | 39,966,642 (53.6) | 16,029,718 (24.1) | 50,492,672 (75.9) | ||||
| Race | ||||||||||
| White | 119,902,677 (90.1) | 13,192,102 (9.9) | 0.47 | 63,468,031 (48.5) | 67,338,465 (51.5) | 0.42 | 37,878,753 (28.8) | 93,493,380 (71.2) | 0.025 | |
| Black | 24,298,788 (93.2) | 1,766,843 (6.8) | 10,295,340 (41.1) | 14,754,974 (58.9) | 9,704,049 (38.6) | 15,447,643 (61.4) | ||||
| Other | 52,225,700 (91.0) | 5,150,144 (9.0) | 130,651,585 (44.5) | 30,701,719 (55.5) | 19,199,936 (34.9) | 35,875,157 (65.1) | ||||
| Income | ||||||||||
| <$35k | 49,181,651 (93.0) | 3,683,576 (7.0) | <0.0001 | 20,335,970 (40.3) | 30,084,363 (59.7) | 0.097 | 20,542,944 (40.2) | 30,515,771 (59.8) | <0.0001 | |
| $35–74K | 58,578,826 (92.2) | 4,936,061 (7.8) | 29,725,049 (48.0) | 32,154,803 (52.0) | 21,357,246 (34.6) | 40,433,995 (65.4) | ||||
| $75k+ | 79,725,870 (88.0) | 10,918,264 (12.0) | 42,601,806 (48.8) | 47,408,740 (52.7) | 22,074,398 (24.6) | 67,742,753 (75.4) | ||||
| Income Feeling | ||||||||||
| Comfortable | 69,639,895 (90.0) | 7,705,850 (10.0) | 0.80 | 41,315,241 (54.7) | 34,272,703 (45.3) | <0.0001 | 24,082,547 (31.9) | 51,450,131 (68.1) | 0.62 | |
| Difficult | 43,423,207 (90.5) | 4,549,403 (9.5) | 16,935,211 (36.8) | 29,073,516 (63.2) | 15,676,967 (33.5) | 31,061,912 (70.7) | ||||
| Getting By | 80,130,391 (91.3) | 7,665,253 (8.7) | 38,413,917 (44.5) | 47,953,056 (55.5) | 26,078,893 (30.2) | 60,166,214 (69.8) | ||||
| Metro | ||||||||||
| No | 23,388,663 (93.5) | 1,634,611 (6.5) | 0.29 | 12,450,295 (54.7) | 12,186,876 (45.3) | 0.68 | 9,429,973 (38.3) | 15,169,173 (61.7) | 0.066 | |
| Yes | 177,537,043 (90.4) | 18,,745,279 (9.6) | 88,459,215 (36.8) | 102,607,532 (63.2) | 59,328,159 (31.0) | 132,140,852 (69.0) | ||||
| E-Device | ||||||||||
| No | 22,055,627 (96.3) | 841,739 (3.7) | 0.0004 | 11,958,688 (58.3) | 8,553,008 (41.7) | 0.0004 | 9,983,647 (48.7) | 10,532,083 (51.3) | <0.0001 | |
| Yes | 178,870,079 (90.2) | 19,538,151 (9.8) | 88,950,822 (45.6) | 106,241,401 (54.4) | 58,774,485 (30.1) | 136,777,942 (69.9) | ||||
| Medicaid | ||||||||||
| No | 164,044,685 (90.4) | 17,466,239 | 0.31 | 84,375,527 (47.6) | 93,000,152 (52.4) | 0.59 | 52,757,793 (29.7) | 125,132,337 (70.3) | 0.0006 | |
| Yes | 31,372,091 (92.4) | 2,597,665 (7.6) | 13,993,414 (42.7) | 18,775,358 (57.3) | 14,327,610 (43.6) | 18,560,247 (56.4) | ||||
| Regular Provider | ||||||||||
| No | 80,432,028 (92.8) | 6,241,647 (7.2) | 0.055 | 38,028,431 (45.2) | 46,015,092 (54.8) | 0.48 | 30,428,147 (36.4) | 53,250,056 (63.6) | 0.026 | |
| Yes | 118,567,097 (89.7) | 13,624,672 (10.3) | 61,653,422 (47.6) | 67,735,988 (52.4) | 37,417,311 (28.8) | 92,640,844 (71.2) | ||||
| Cardiovascular Disease | ||||||||||
| No | 12,254,705 (10.5) | 104,525,515 (89.5) | 0.056 | 64,369,744 (56.0) | 50,637,528 (44.0) | 0.0035 | 36,419,726 (31.7) | 78,360,621 (68.3) | 0.94 | |
| Yes | 8,125,185 (7.8) | 96,400,192 (92.2) | 50,424,664 (50.1) | 50,271,982 (49.9) | 32,338,406 (31.9) | 68,949,404 (68.1) | ||||
Don’t know anything, vs. a little vs. alot
A lot, and Somewhat, vs. A little, Not At All
Acknowledgements
The authors would like to acknowledge the Clinical Research Support Office (CRSO) at the University of North Carolina at Chapel Hill.
Funding
This project described was supported by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR002489. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Footnotes
Declaration of conflicting interests
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: None
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