Need for Diversity and Inclusion in Liver Cancer Clinical Trials
Cancer clinical trials contribute critical information about the safety and efficacy of novel therapies but also provide patients access to cutting-edge treatments. Although trial enrollment has increased over the past two decades in the U.S., there remain notable differences in sociodemographic profiles of patients affected by cancer and those participating in trials. Specifically, racial and ethnic minority populations, women, and older adults are often underrepresented. Primary liver cancer (PLC) is one of the fastest rising causes of cancer death in the U.S.,1 with striking disparities in incidence and mortality rates by gender, age, race, and ethnicity; men, older adults, and racial and ethnic minority populations are disproportionately affected.2–5 For example, Black, Hispanic and Asian persons have higher age-adjusted PLC incidence rates compared to White persons, with fastest increases observed in American Indian/Alaskan Native and Hispanic persons.6, 7 Disparities in tumor stage at diagnosis, curative treatment receipt and prognosis have also been consistently demonstrated, with Black patients having worse overall survival and Hispanic and Asian patients having better overall survival compared to White patients.5
While there have been tremendous recent advances in PLC locoregional and systemic therapies, diversity of trial participants has not been investigated. The epidemiology of PLC is shifting in the U.S. and globally: incidence rates are increasing in older adults, there is a trend toward less male predominance (particularly in younger birth cohorts), and fewer cases attributed to viral hepatitis while, in turn, the prevalence of non-alcoholic fatty liver disease (NAFLD)-related liver cancer is steadily rising in most countries.8, 9 This is important as the attributable fractions of known PLC risk factors (e.g., viral hepatitis, metabolic disorders, alcohol use) vary by region, race, ethnicity, gender and birth cohort. Thus, results from homogenous trial populations may not be generalizable to those most affected by PLC in contemporaneous cohorts. For example, the incidence of NAFLD-related HCC is rising in older, White and Hispanic patients, yet recent data suggest lower efficacy of immune checkpoint inhibitors in non-viral HCC10 and anti-angiogenic agents (e.g., bevacizumab) in patients who are obese.6 Disparities in trial enrollment also likely mirror other disparities in PLC care access, as disparities in surveillance and treatment receipt persist among racial and ethnic minority groups and the socioeconomically disadvantaged. Therefore, we aimed to characterize the representation of racial and ethnic minority groups, women, and older adults in PLC clinical trials.
Evaluating Enrollment Disparities in Liver Cancer Clinical Trials
We conducted a systematic search of the U.S. ClinicalTrials.gov database to derive enrollment data from therapeutic PLC trials conducted in adults >18 years from inception through July 19, 2019. All included trials had some degree of enrollment in the U.S. Demographics of interest included reported gender, race (White, Black, Asian/Pacific Islander, American Indian/Alaskan Native (AI/AN), multiracial, unknown), ethnicity (Hispanic vs. non-Hispanic), and age (18–64 years vs. 65+ years).
When possible, for trials missing demographic variables of interest in the ClinicalTrials.gov database, we located and recorded relevant variables from the final published data. We used Fisher’s exact test to compare trial phase (I, II, III-IV), study location (U.S. only, international), therapeutic type (locoregional vs. systemic), and funding source (NIH, industry, academic) of: men vs. women; older vs. younger; Hispanic vs. non-Hispanic; and White vs. Black vs. Asian participants. In a separate analysis, we calculated the enrollment fraction (EF) as the number of trial enrollees divided by number of patients with liver cancer matched to the period of trial enrollment using the U.S. Cancer Statistics database (overall and by gender, race, ethnicity, and age), as previously described by Murthy et al.11 We examined disparities in enrollment between U.S.-only and international trials by race, ethnicity, and gender. To calculate the EF for international trials, we estimated incidence rates based on GLOBOCAN data for each category of interest when possible; cancer incidence was assumed to be fixed during the study period.
Sixty-three trials met inclusion criteria; 30 (47.6%) were sponsored by an academic institution, 21 (33.3%) by industry, and 12 (19.1%) by NIH. Nineteen trials were international with some degree of U.S. enrollment and 44 trials were limited to U.S. only enrollment; all but one of the U.S.-only trials were phase I/II. Gender of participants was reported for all 63 trials (n=9749 participants), whereas enrollment data on race, ethnicity, and age were available for only 26 (n=4478), 21 (n=2907) and 28 (n=5176) trials, respectively. A higher proportion of U.S. only trials reported data on race and ethnicity compared to international trials (45.4% vs 36.8%, respectively). The proportion of studies reporting enrollment data on race and ethnicity increased over time (29.0% in 1998–2008 vs. 54.2% in 2009–2018, p=0.04), while reporting of age increased to a lesser degree (43.0% vs. 48.5%, respectively, p=0.66).
Although the EF in U.S.-only trials paralleled racial and ethnic composition of PLC cases in the U.S. (Supplemental Table 1), there was marked under-representation of Black and Hispanic patients among total and international trial participants. For example, Black patients comprised 14.4% and 1.6% of participants in U.S.-only and international trials, respectively. Similarly, Hispanic patients accounted for 14.8% of PLC cases in the U.S. but comprised only 8.3% of U.S.-only trial participants; 3.9% of international trial participants were Hispanic (Table 1; Figure 1). This is in contrast to Asian patients which accounted for 8.2% of PLC cases in the U.S. but comprised 9.0% of U.S.-only trial participants and a majority (54.4%) of international trial participants. Underrepresentation of racial and ethnic minority populations was observed across subgroups by trial phase, funding source, and type of therapeutic, with the most notable differences observed in international and phase III/IV trials. Across all trials, the proportion of White patients in trials increased from 1998–2008 to 2009–2018 (27.3% vs. 49.5%); however, there was a small increase in proportion of Black patients (3.5% vs. 3.6%) and a slight decrease in Hispanic patients (4.9% vs 4.7%) over the same period.
Table 1.
Demographics of trial participants
| Reported Gender (n=63 trials reporting gender, n=9,749 participants) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All trials | U.S.-only trials | International trials | |||||||||||
| Women (n=1,775, 18.2%) | Men (n=7,974, 81.8%) | p-value | Women (n=442, 22.7%) | Men (n=1,507, 77.3%) | Women (n=1,333, 17.1%) | Men (n=6,467, 82.9%) | |||||||
| Trial phase | <0.01 | ||||||||||||
| I | 49 (22.4) | 170 (77.6) | 49 (22.4) | 170 (77.6) | - | - | |||||||
| II | 570 (22.4) | 1968 (77.5) | 343 (24.9) | 1031 (75.1) | 227 (19.5) | 937 (80.5) | |||||||
| III and IV | 1156 (16.5) | 5836 (83.5) | 50 (14.0) | 306 (86.0) | 1106 (16.7) | 5530 (83.3) | |||||||
| Years | <0.01 | ||||||||||||
| 1998–2008 | 634 (20.5) | 2463 (79.5) | 191 (26.9) | 519 (73.1) | 443 (18.6) | 1944 (81.4) | |||||||
| 2009–2018 | 1141 (17.2) | 5511 (82.8) | 251 (20.2) | 988 (79.8) | 890 (16.4) | 4523 (83.6) | |||||||
| Sponsor | <0.01 | ||||||||||||
| Academic | 300 (24.7) | 913 (75.3) | 913 (75.3) | - | - | ||||||||
| NIH | 131 (18.8) | 564 (81.2) | 125 (19.5) | 516 (80.5) | 6 (11.1) | 48 (88.9) | |||||||
| Industry | 1179 (17.1) | 5706 (82.9) | 17 (17.9) | 78 (82.1) | 1327 (17.1) | 6419 (82.9) | |||||||
| Type of therapeutic | <0.01 | ||||||||||||
| Locoregional | 327 (23.4) | 1072 (76.6) | 187 (26.4) | 521 (73.6) | 140 (20.3) | 551 (79.7) | |||||||
| Systemic | 1448 (17.3) | 6902 (82.7) | 255 (20.5) | 986 (79.5) | 1193 (16.8) | 5916 (83.2) | |||||||
| Reported Age (n=28 trials reporting age, n=5,176 participants) | |||||||||||||
| All trials | U.S.-only trials | International trials | |||||||||||
| 18–64 years (n=2,750, 53.3%) | 65+ years (n=2,416, 46.7%) | p-value | 18–64 years (n=408, 59.7%) | 65+ years (n=275, 40.3%) | 18–64 years (n=2,352, 52.3%) | 65+ years (n=2,141, 47.7%) | |||||||
| Trial phase | 0.04 | ||||||||||||
| I | 97 (62.6) | 58 (37.4) | 97 (62.6) | 58 (37.4) | - | - | |||||||
| II | 606 (51.9) | 562 (48.1) | 311 (58.9) | 217 (41.1) | 295 (46.1) | 345 (53.9) | |||||||
| III and IV | 2057 (53.4) | 1796 (46.6) | - | - | 2057 (53.4) | 1796 (46.6) | |||||||
| Years | <0.01 | ||||||||||||
| 1998–2008 | 1393 (63.3) | 809 (36.7) | 176 (58.7) | 124 (41.3) | 1217 (64.0) | 685 (36.0) | |||||||
| 2009–2018 | 1367 (46.0) | 1607 (54.0) | 232 (60.6) | 151 (39.4) | 1135 (43.8) | 1456 (56.2) | |||||||
| Sponsor | <0.01 | ||||||||||||
| Academic | 346 (61.6) | 216 (38.4) | 346 (61.6) | 216 (38.4) | - | - | |||||||
| NIH | 35 (44.3) | 44 (55.7) | 35 (44.3) | 44 (55.7) | - | - | |||||||
| Industry | 2379 (52.5) | 2156 (47.5) | 27 (64.3) | 15 (35.7) | 2352 (52.3) | 2141 (47.7) | |||||||
| Type of therapeutic | 0.03 | ||||||||||||
| Locoregional | 658 (56.2) | 513 (43.8) | 110 (60.1) | 73 (39.9) | 548 (55.5) | 440 (44.5) | |||||||
| Systemic | 2102 (52.5) | 1903 (47.5) | 298 (59.6) | 202 (40.4) | 1804 (51.5) | 1701 (48.5) | |||||||
| Reported Race# (n=26 trials reporting race, n=4,478 participants) | |||||||||||||
| All trials | U.S.-only trials | International trials | |||||||||||
| Black (n=160, 3.6%) | White (n=1,984, 44.3%0 | Asian (n=2,123, 47.4%) | Unknown (n=196, 4.4%) | p-value | Black (99, 14.4%0 | White (494, 72.0%) | Asian (n=62, 9.0%) | Unknown (n=17, 2.5%) | Black (n=61, 1.6%) | White (n=1,490, 39.3%) | Asian (n=2,061, 54.4%) | Unknown (n=179, 4.7%) | |
| Trial phase | <0.0 1 | ||||||||||||
| I | 14 (29.8) | 29 (61.7) | 1 (2.1) | 2 (4.3) | 14 (29.8) | 29 (61.7) | 2 (4.3) | - | - | - | - | ||
| II | 97 (10.1) | 639 (66.7) | 194 (20.3) | 16 (1.7) | 85 (13.4) | 465 (73.2) | 61 (9.6) | 15 (2.4) | 12 (3.7) | 174 (54.4) | 133 (41.6) | 1 (0.3) | |
| III and IV | 49 (1.4) | 1316 (37.9) | 1928 (55.5) | 178 (5.1) | - | - | - | 49 (1.4) | 1316 (37.9) | 1928 (55.5) | 178 (5.1) | ||
| Years | <0.0 1 | ||||||||||||
| 1998–2008 | 36 (3.5) | 283 (27.3) | 638 (61.5) | 77 (7.4) | 36 (12.8) | 215 (76.2) | 23 (8.2) | 5 (1.8) | 0 (0.0) | 68 (9.0) | 615 (81.5) | 72 (9.5) | |
| 2009–2018 | 124 (3.6) | 1701 (49.5) | 1485 (43.2) | 63 (15.8) | 279 (69.9) | 39 (9.8) | 12 (4.0) | 61 (2.0) | 1422 (46.8) | 1446 (47.6) | 107 (3.5) | ||
| Sponsor | <0.0 1 | ||||||||||||
| Academic | 66 (14.9) | 328 (74.0) | 29 (6.5) | 13 (2.9) | 66 (14.9) | 328 (74.0) | 29 (6.5) | 13 (2.9) | - | - | - | - | |
| NIH | 29 (14.4) | 97 (48.0) | 73 (36.1) | 2 (1.0) | 29 (19.6) | 97 (65.5) | 13 (8.8) | 2 (1.4) | 0 (0.0) | 0 (0.0) | 60 (100.0) | 0 (0.0) | |
| Industry | 65 (1.7) | 1559 (40.7) | 2021 (52.7) | 181 (4.7) | 4 (4.2) | 69 (72.6) | 20 (21.0) | 2 (2.1) | 61 (1.6) | 1490 (39.9) | 2001 (53.5) | 179 (4.8) | |
| Type of therapeutic | <0.0 1 | ||||||||||||
| Locoregion al | 36 (3.7) | 282 (29.1) | 568 (58.6) | 77 (7.9) | 36 (13.6) | 214 (81.1) | 7 (2.7) | 5 (1.9) | 0 (0.0) | 68 (9.7) | 561 (80.0) | 72 (10.3) | |
| Systemic | 124 (3.5) | 1702 (48.5) | 1555 (44.3) | 119 (3.4) | 63 (15.1) | 280 (67.1) | 55 (13.2) | 12 (2.9) | 61 (2.0) | 1422 (46.0) | 1500 (48.5) | 107 (3.5) | |
| Reported Ethnicity (n=21 trials reporting ethnicity, n=2,907 participants) | |||||||||||||
| All trials | U.S.-only trials | International trials | |||||||||||
| Hispanic (n=136, 4.7%) | Non-Hispanic (n=2,711, 93.2%) | p-value | Hispanic (n=43, 8.3%) | Non-Hispanic (n=467, 90.5%) | Hispanic (n=93, 3.9%) | Non-Hispanic (n=2,244, 93.9%) | |||||||
| Trial phase | <0.01 | ||||||||||||
| I | 0 (0.0) | 0 (0.0) | - | - | - | - | |||||||
| II | 46 (6.7) | 629 (92.4) | 43 (8.4) | 467 (91.6) | 3 (1.8) | 162 (98.2) | |||||||
| III and IV | 90 (4.0) | 2082 (93.6) | - | - | 90 (4.1) | 2082 (95.9) | |||||||
| Years | 0.16 | ||||||||||||
| 1998–2008 | 12 (4.9) | 233 (94.7) | 12 (4.9) | 233 (95.1) | - | - | |||||||
| 2009–2018 | 124 (4.7) | 2478 (93.1) | 31 (11.7) | 234 (88.3) | 93 (3.9) | 2244 (96.1) | |||||||
| Sponsor | |||||||||||||
| Academic | 23 (7.3) | 286 (91.1) | 0.10 | 23 (7.4) | 286 (92.6) | - | - | ||||||
| NIH | 7 (6.6) | 99 (93.4) | 7 (6.6) | 99 (93.4) | - | - | |||||||
| Industry | 106 (4.3) | 2326 (93.5) | 13 (13.7) | 82 (86.3) | 93 (3.9) | 2244 (96.1) | |||||||
| Type of therapeutic | 0.43 | ||||||||||||
| Locoregional | 6 (4.3) | 129 (92.1) | 6 (4.4) | 129 (95.6) | - | - | |||||||
| Systemic | 130 (4.7) | 2582 (93.3) | 37 (9.9) | 338 (90.1) | 93 (3.9) | 2244 (96.1) | |||||||
Data from American Indian/Alaskan Native (n=10) and multiracial (n=5) populations not shown in table as number enrolled in trials was < 0.1% of the total enrolled population
Figure 1.
Participation in U.S.-only and international primary liver cancer clinical trials by reported gender, age, race, and ethnicity
In contrast, there was a gender disparity in trial participants and EF. Women accounted for 26.4% of PLC cases in the U.S. but comprised a slightly lower proportion of U.S.-only trial participants (22.7%). This gender disparity remained stable over time and was more pronounced among international trials (17.1% women vs 22.7% women in U.S.-only trials, p<0.001), as well as phase III/IV, industry-sponsored and systemic therapy trials. A gender disparity in EF was observed across U.S.-only (0.50% for women vs 0.61% for men) and international trials (0.04% for women vs 0.07% for men) (Supplemental Table 1).
Finally, older adults (aged 65+) had an EF of just 0.18% compared to 0.23% for younger adults (aged 18–64), although the proportion of older adults increased from 36.7% in 1998–2008 to 54.0% in 2009–2018.
Discussion
Overall, participation in PLC clinical trials varies significantly across racial and ethnic, gender and age groups, with highest participation among Whites, men, and younger adults. Although racial and ethnic disparities in EF were mitigated in the subset of U.S.-only trials, this accounted for a minority of all clinical trial participants and gender disparities persisted. Our findings are consistent with studies in other cancers12, 13 and emphasize the need for interventions to ensure PLC trial demographics better reflect the at-risk population.
Our findings also demonstrate the consistent under-reporting of race and ethnicity in clinical trials, with less than half of the included studies reporting race and/or ethnicity on ClinicalTrials.gov or in the final manuscript. Additionally, the absolute number of Black (n=160), Hispanic (n=136), American Indian/Alaskan Native (n=10) and multiracial (n=5) trial participants during the 20 year study period were exceedingly low; this further highlights disparities in trial access in racial and ethnic minority groups. Race is a social construct, but plays a significant role in understanding the distribution of someone’s determinants of health in the U.S., in large part due to structural racism; therefore, the first step to deepen our understanding of health disparities (including intersectionality), increase our health equity-related knowledge and improve equity in cancer care is to establish a baseline to which other interventions may be compared. This necessitates standardization of demographic reporting in clinical research (e.g., race, ethnicity, sex, gender), performing stratified analyses, and promoting the collection and publication of disaggregated data.14
Prior studies have established that racial and ethnic minority groups are equally willing to consent to a trial if offered.15 Therefore, enrollment targets on the basis of race and ethnicity, gender, and age should be defined and reflect the at-risk population. Active steps should be taken by researchers to be aware of implicit and explicit biases and improve communication skills when approaching patients about clinical trials, particularly those belonging to groups that have been socially and economically marginalized. Multilevel interventions are needed to improve trial access and must address patient- (e.g., transportation assistance, use of telemedicine, minimizing language barriers), provider- (e.g., implicit bias training, improving communication), and system-level (e.g., workforce diversity, funding for trials in racial and ethnic minority populations) barriers.16, 17 Various barriers to liver cancer care including: health literacy, medical mistrust, patient-provider communication and financial concerns appear to differ by race and ethnicity.18 For example, Black and Hispanic patients are more likely than White patients to report reluctance confiding in their doctor and lack of trust in their doctor, which may adversely impact trial enrollment in these groups. Ultimately, large-scale interventions and policy changes are needed to have lasting impact on equitable enrollment.
Our study’s limitations include: First, race is a social construct, with as much genetic variability within races as between races, so distinct racial categories may not reflect biological differences. Second, there is potential for misclassification bias given inconsistent reporting of race, ethnicity, and age across trials. Many trials did not provide any information on reported race, ethnicity, or age; while most cancer trials use self-reported race, ethnicity, and gender, not all trial participants may be explicitly asked, particularly in countries outside the U.S. with less racial and ethnic diversity. Third, data were limited on AI/AN populations and gender identity minority groups. Fourth, while unequal geographic distribution of clinical trial sites (e.g., in rural areas) may contribute to the low enrollment of racial and ethnic minorities19, disaggregated demographic data by region and granular patient level data (i.e., addresses, zip codes) were not available, so we were unable to explore the intersection of geography with racial and ethnic disparities in enrollment. Fifth, international studies with enrollment entirely outside of the U.S. were excluded as these are not included in clinicaltrials.gov. Finally, while most large PLC trials are international given the global distribution of the burden of liver cancer, with highest prevalence in East Asia, results are often not stratified by region or reported in disaggregated format by race, ethnicity, region or gender (both in published data nor in ClinicalTrials.gov). Among international trials, we found the proportion of Black trial participants to be low despite high PLC prevalence in Sub-Saharan Africa; in fact, very few global trials had any enrollment in Africa or South America, highlighting the poor access to cancer trials in these regions. Further, while the U.S. Cancer Statistics database provides demographics including race, ethnicity, and gender for incident PLC cases, published GLOBOCAN estimates include only gender and region (not race or ethnicity) which did not allow for calculation of EF by race or ethnicity for international trials.
Despite these limitations, our data highlight that available international data may not be generalizable to all groups, specifically Black patients, Hispanic patients, and women, particularly as PLC risk factors are in transition and differ by race, ethnicity, gender, and region. Our study demonstrates the need for accurate reporting of demographics (particularly race and ethnicity) as a necessary first step to reduce trial enrollment disparities, inform health-equity related knowledge and improve generalizability of the research. Additionally, future studies in diverse populations are needed to identify reasons for low clinical trial enrollment.
Conclusions
Improving diversity in clinical trials is not only morally imperative but has many benefits. Ethically, enrollment should reflect the affected patient population and offer equitable access to novel therapies. Diversity can inform benefits across subgroups and ensure generalizability of results. However, there are multiple barriers to equitable enrollment, including lack of invitation, lack of patient awareness regarding trials, strict eligibility criteria, and practical obstacles including costs (e.g., time off work, transportation, parking), cultural barriers, mistrust, and language differences. These barriers also differ by region; in the U.S, structural racism among other factors (e.g., lack of universal healthcare) contribute to lack of trial diversity, whereas globally, the lack of resources and critical research infrastructure plays a large role. We propose the following potential interventions to improve equitable enrollment in PLC clinical trials:
Sponsors and investigators must establish a commitment to diversity and inclusion efforts.
Clearly define enrollment targets, broaden eligibility, and re-evaluate strict inclusion criteria that may limit participation by patients belonging to groups disproportionately affected by PLC.
Improve research workforce diversity including principal investigators, coordinators, and other research staff.
Recognize implicit and explicit biases among research staff and provide implicit bias training
Patients are approached with cultural humility with tailored materials, research staff receive training to improve health communication skills.
Research consents should be made accessible to those with limited health literacy and made available in various languages, with the use of bilingual research staff or in-person interpreter services when possible.
Community-level advocacy and promotion of clinical trials
Provide financial and/or travel assistance for socioeconomically disadvantaged patients
Telehealth monitoring visits when feasible may help mitigate travel barriers
Improving access to trials by offering them at diverse sites in various geographic locations, both urban and rural
Improve resources and invest in clinical trial infrastructure in countries bearing a disproportionate burden of PLC (e.g., Africa and South America)
Establish accountability and regularly assess and monitor diversity and inclusion
In summary, there are persistent inequities in PLC clinical trial participation, with underrepresentation of racial and ethnic minority groups, women, and older adults despite disproportionate increases in the burden of PLC in these populations. While awareness of the problem is the necessary first step, targeted efforts are needed to ensure equity in PLC trial enrollment and improve outcomes for all patients.
Supplementary Material
Acknowledgments
Grant Support: Dr. Rich is supported by the American College of Gastroenterology Junior Faculty Development Award and the Texas Health Resources Clinical Scholar Award. Dr. Singal’s research is supported by National Cancer Institute R01 CA222900 and R01 MD12565. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Abbreviations:
- AI/AN
American Indian/Alaskan Native
- EF
enrollment fraction
- NIH
National Institutes of Health
- PLC
primary liver cancer
- U.S.
United States
Footnotes
Writing Assistance: None
Conflicts of Interest: Amit Singal has been on advisory boards and served as a consultant for FujiFilm Medical Sciences, Exact Sciences, Glycotest, Roche, GRAIL, Genentech, AstraZeneca, Bayer, Eisai, Exelixis, and TARGET-RWE. Nicole Rich has served as consultant for AstraZeneca. Caitlin Murphy has served as consultant for Freenome. The other authors have no relevant conflicts of interest.
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