Barriers to cancer clinical trial participation have been the subject of frequent study, but the rate of trial participation has not changed substantially over time. Studies often emphasize ...patient-related barriers, but other types of barriers may have greater impact on trial participation. Our goal was to examine the magnitude of different domains of trial barriers by synthesizing prior research.
We conducted a systematic review and meta-analysis of studies that examined the trial decision-making pathway using a uniform framework to characterize and quantify structural (trial availability), clinical (eligibility), and patient/physician barrier domains. The systematic review utilized the PubMed, Google Scholar, Web of Science, and Ovid Medline search engines. We used random effects to estimate rates of different domains across studies, adjusting for academic vs community care settings.
We identified 13 studies (nine in academic and four in community settings) with 8883 patients. A trial was unavailable for patients at their institution 55.6% of the time (95% confidence interval CI = 43.7% to 67.3%). Further, 21.5% (95% CI = 10.9% to 34.6%) of patients were ineligible for an available trial, 14.8% (95% CI = 9.0% to 21.7%) did not enroll, and 8.1% (95% CI = 6.3% to 10.0%) enrolled. Rates of trial enrollment in academic (15.9% 95% CI = 13.8% to 18.2%) vs community (7.0% 95% CI = 5.1% to 9.1%) settings differed, but not rates of trial unavailability, ineligibility, or non-enrollment.
These findings emphasize the enormous need to address structural and clinical barriers to trial participation, which combined make trial participation unachievable for more than three of four cancer patients.
The COVID-19 pandemic has caused severe disruptions in care for many patients. A key question is whether the landscape of clinical research has also changed.
In a retrospective cohort study, we ...examined the association of the COVID-19 outbreak with new clinical trial activations. Trial data for all interventional and observational oncology, cardiovascular, and mental health studies from January 2015 through September 2020 were obtained from ClinicalTrials.gov . An interrupted time-series analysis with Poisson regression was used.
We examined 62,252 trial activations. During the initial COVID-19 outbreak (February 2020 through May 2020), model-estimated monthly trial activations for US-based studies were only 57% of the expected estimate had the pandemic not occurred (relative risk = 0.57, 95% CI 0.52 to 0.61, p < .001). For non-US-based studies, the impact of the pandemic was less dramatic (relative risk = 0.77, 95% CI 0.73 to 0.82, p < .001), resulting in an overall 27% reduction in the relative risk of new trial activations for US-based trials compared to non-US-based trials (relative risk ratio = 0.73, 95% CI 0.67 to 0.81, p < .001). Although a rebound occurred in the initial reopening phase (June 2020 through September 2020), the rebound was weaker for US-based studies compared to non-US-based studies (relative risk ratio = 0.87, 95% CI 0.80 to 0.95, p < .001).
These findings are consistent with the disproportionate burden of COVID-19 diagnoses and deaths during the initial phase of the pandemic in the USA. Reduced activation of cancer clinical trials will likely slow the pace of clinical research and new drug discovery, with long-term negative consequences for cancer patients. An important question is whether the renewed outbreak period of winter 2020/2021 will have a similarly negative impact on the initiation of new clinical research studies for non-COVID-19 diseases.
Women have more adverse events (AEs) from chemotherapy than men, but few studies have investigated sex differences in immune or targeted therapies. We examined AEs by sex across different treatment ...domains.
We analyzed treatment-related AEs by sex in SWOG phase II and III clinical trials conducted between 1980 and 2019, excluding sex-specific cancers. AE codes and grade were categorized using the Common Terminology Criteria for Adverse Events. Symptomatic AEs were defined as those aligned with the National Cancer Institute's Patient-Reported Outcome-Common Terminology Criteria for Adverse Events; laboratory-based or observable/measurable AEs were designated as objective (hematologic
nonhematologic). Multivariable logistic regression was used, adjusting for age, race, and disease prognosis. Thirteen symptomatic and 14 objective AE categories were examined.
In total, N = 23,296 patients (women, 8,838 37.9%; men, 14,458 62.1%) from 202 trials experiencing 274,688 AEs were analyzed; 17,417 received chemotherapy, 2,319 received immunotherapy, and 3,560 received targeted therapy. Overall, 64.6% (n = 15,051) experienced one or more severe (grade ≥ 3) AEs. Women had a 34% increased risk of severe AEs compared with men (odds ratio OR = 1.34; 95% CI, 1.27 to 1.42;
< .001), including a 49% increased risk among those receiving immunotherapy (OR = 1.49; 95% CI, 1.24 to 1.78;
< .001). Women experienced an increased risk of severe symptomatic AEs among all treatments, especially immunotherapy (OR = 1.66; 95% CI, 1.37 to 2.01;
< .001). Women receiving chemotherapy or immunotherapy experienced increased severe hematologic AE. No statistically significant sex differences in risk of nonhematologic AEs were found.
The greater severity of both symptomatic AEs and hematologic AEs in women across multiple treatment modalities indicates that broad-based sex differences exist. This could be due to differences in AE reported, pharmacogenomics of drug metabolism/disposition, total dose received, and/or adherence to therapy. Particularly large sex differences were observed for patients receiving immunotherapy, suggesting that studying AEs from these agents is a priority.
Since the onset of the COVID-19 pandemic, there have been calls for COVID-19 clinical trials to be fully representative of all demographic groups. However, limited evidence is available about the ...sex, racial, and ethnic representation among COVID-19 prevention and treatment trials.
To investigate whether female participants and racial and ethnic minority individuals are adequately represented in COVID-19 prevention and treatment trials in the US.
Identified studies were registered on ClinicalTrials.gov or published in the PubMed database from October 2019 to February 2022.
Included studies must have provided the number of enrolled participants by sex, race, or ethnicity. Only interventional studies conducted in the US for the primary purpose of the diagnosis, prevention, or treatment of (or supportive care for) COVID-19 conditions were included.
Data on counts of enrollments by demographic variables (sex, race, and ethnicity) and location (country and state) were abstracted. Studies were broadly categorized by primary purpose as prevention (including vaccine and diagnosis studies) vs treatment (including supportive care studies). A random effects model for single proportions was used. Trial estimates were compared with corresponding estimates of representation in the US population with COVID-19.
Sex, racial, and ethnic representation in COVID-19 clinical trials compared with their representation in the US population with COVID-19.
Overall, 122 US-based COVID-19 clinical trials comprising 176 654 participants were analyzed. Studies were predominantly randomized trials (n = 95) for treatment of COVID-19 (n = 103). Sex, race, and ethnicity were reported in 109 (89.3%), 95 (77.9%), and 87 (71.3%) trials, respectively. Estimated representation in prevention and treatment trials vs the US population with COVID-19 was 48.9% and 44.6% vs 52.4% for female participants; 23.0% and 36.6% vs 17.7% for Hispanic or Latino participants; 7.2% and 16.5% vs 14.1% for Black participants; 3.8% and 4.6% vs 3.7% for Asian participants; 0.2% and 0.9% vs 0.2% for Native Hawaiian or Other Pacific Islander participants; and 1.3% and 1.4% vs 1.1% for American Indian or Alaska Native participants. Compared with expected rates in the COVID-19 reference population, female participants were underrepresented in treatment trials (85.1% of expected; P < .001), Black participants (53.7% of expected; P = .003) and Asian participants (64.4% of expected; P = .003) were underrepresented in prevention trials, and Hispanic or Latino participants were overrepresented in treatment trials (206.8% of expected; P < .001).
In this systematic review and meta-analysis, aggregate differences in representation for several demographic groups in COVID-19 prevention and treatment trials in the US were found. Strategies to better ensure diverse representation in COVID-19 studies are needed, especially for prevention trials.
Abstract
Background
Patient participation in clinical trials is vital for knowledge advancement and outcomes improvement. Few adult cancer patients participate in trials. Although patient ...decision-making about trial participation has been frequently examined, the participation rate for patients actually offered a trial is unknown.
Methods
A systematic review and meta-analysis using 3 major search engines was undertaken. We identified studies from January 1, 2000, to January 1, 2020, that examined clinical trial participation in the United States. Studies must have specified the numbers of patients offered a trial and the number enrolled. A random effects model of proportions was used. All statistical tests were 2-sided.
Results
We identified 35 studies (30 about treatment trials and 5 about cancer control trials) among which 9759 patients were offered trial participation. Overall, 55.0% (95% confidence interval CI = 49.4% to 60.5%) of patients agreed to enroll. Participation rates did not differ between treatment (55.0%, 95% CI = 48.9% to 60.9%) and cancer control trials (55.3%, 95% CI = 38.9% to 71.1%; P = .98). Black patients participated at similar rates (58.4%, 95% CI = 46.8% to 69.7%) compared with White patients (55.1%, 95% CI = 44.3% to 65.6%; P = .88). The main reasons for nonparticipation were treatment choice or lack of interest.
Conclusions
More than half of all cancer patients offered a clinical trial do participate. These findings upend several conventional beliefs about cancer clinical trial participation, including that Black patients are less likely to agree to participate and that patient decision-making is the primary barrier to participation. Policies and interventions to improve clinical trial participation should focus more on modifiable systemic structural and clinical barriers, such as improving access to available trials and broadening eligibility criteria.
Clinical trials test the efficacy of a treatment in a select patient population. We examined whether cancer clinical trial patients were similar to nontrial, "real-world" patients with respect to ...presenting characteristics and survival.
We reviewed the SWOG national clinical trials consortium database to identify candidate trials. Demographic factors, stage, and overall survival for patients in the standard arms were compared with nontrial control subjects selected from the Surveillance, Epidemiology, and End Results program. Multivariable survival analyses using Cox regression were conducted. The survival functions from aggregate data across all studies were compared separately by prognosis (≥50% vs <50% average 2-year survival). All statistical tests were two-sided.
We analyzed 21 SWOG studies (11 good prognosis and 10 poor prognosis) comprising 5190 patients enrolled from 1987 to 2007. Trial patients were younger than nontrial patients (P < .001). In multivariable analysis, trial participation was not associated with improved overall survival for all 11 good-prognosis studies but was associated with better survival for nine of 10 poor-prognosis studies (P < .001). The impact of trial participation on overall survival endured for only 1 year.
Trial participation was associated with better survival in the first year after diagnosis, likely because of eligibility criteria that excluded higher comorbidity patients from trials. Similar survival patterns between trial and nontrial patients after the first year suggest that trial standard arm outcomes are generalizable over the long term and may improve confidence that trial treatment effects will translate to the real-world setting. Reducing eligibility criteria would improve access to clinical trials.
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