Each square represents an odds ratio (OR), and each horizontal line is the 95% CI. The vertical line is the line of equal odds. For lower-income individuals, the odds of clinical trial participation were consistently lower (that is, to the left of the line of equal odds) within nearly all subgroups of all the factors included in this analysis. Only some of these findings are statistically significant, likely due to limited power. There was no statistical evidence that the association of income and clinical trial participation differed according to any of the covariates (interaction P > .15 in all cases).
aAlthough 1581 patients were eligible, annual income data were not reported (n = 239), unknown (n = 68), or missing (n = 12) for 319 patients, leaving 1262 patients available for analysis.
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Unger JM, Gralow JR, Albain KS, Ramsey SD, Hershman DL. Patient Income Level and Cancer Clinical Trial Participation: A Prospective Survey Study. JAMA Oncol. 2016;2(1):137–139. doi:10.1001/jamaoncol.2015.3924
Cancer clinical trials provide the best evidence for showing the efficacy of new treatments. However, only a small percentage of adult patients with cancer participate in clinical trials.1 The issue of income disparities in clinical trial participation has been poorly addressed; limiting income disparities is important for ensuring rapid enrollment and fair access to trials. Our research group previously found that patients with annual household incomes below $50 000 were 27% less likely to participate in clinical trials.2 This provocative result was derived from one of many analyses of demographic and socioeconomic factors within a single, cross-sectional data set and so was considered hypothesis generating. The confirmation of this finding with prospectively collected data is critical for affirming its validity.
We used data from a prospective cooperative group survey study of barriers to participation in clinical trials conducted in 8 geographically diverse cancer clinics.3 The study protocol and informed consent documents were reviewed and approved by the institutional review boards of all participating institutions. Adult patients with a new diagnosis (de novo or recurrent disease) of breast, lung, or colorectal cancer under consideration for systemic therapy were enrolled prior to making a treatment decision. Patients were then followed for a maximum of 6 months to assess whether they participated in a clinical trial. Patient-level baseline characteristics, including income, were collected.
We examined the association of income (<$50 000/y vs ≥$50 000/y) and trial participation in a multivariable logistic regression model stratified by cancer type. We adjusted for the following factors that could potentially influence participation rates: age, sex, race (self-reported by participants), education, travel distance, and disease stage (initial diagnosis vs recurrent disease). The analysis was conducted at the α = .05 level. We also examined whether there was evidence of an ordinal association of income level and trial participation by categorizing income as less than $20 000/y vs $20 000/y to $49 999/y vs $50 000/y or higher.
In total, 1581 patients were eligible, and 1262 (80%) with annual income data were available for analysis. Patients were predominantly younger than 65 years (71%), female (84%), and not African American (93%; Table). In multivariable regression, patients with annual household income below $50 000 had 32% lower odds of trial participation than higher income patients (12% vs 17%; odds ratio [OR], 0.68; 95% CI, 0.47-0.99; P = .04). Trial participation decreased as annual household income decreased from $50 000 or higher to between $20 000 and $49 999 to less than $20 000 (17% vs 13% vs 11%, respectively; OR, 0.75; 95% CI, 0.58-0.96; P = .02). Lower-income patients were consistently less likely to participate in clinical trials across the key subgroups defined by model covariates (Figure).
In a prospective study of barriers to trial participation, lower-income patients were less likely to participate in clinical trials. Lower-income patients are likely more sensitive to marginal financial expenditures than higher-income patients.4,5 Incentives or reimbursements may be appropriate, though they should not be coercive to patients. One approach to alleviate the financial risk associated with clinical trial participation would be to cover the excess costs of participation, including copayments and coinsurance. Direct compensation to clinical trial participants has also been recommended.6 Considerations with respect to time off from work, child care, and transportation could also improve access to clinical trials for lower-income patients. Future research should investigate how to overcome financial barriers to clinical trial participation.
The identification of patient income level as an independent predictor of trial participation is important for multiple reasons. If income is associated with health status, then improving representativeness of lower-income patients in trials would improve the generalizability of study outcomes. Also, greater participation of lower-income patients would allow trials to be conducted more quickly, speeding the development of new treatments. Crucially, since clinical trial treatments represent the newest available treatments, access to this vital resource should be available to individuals of all income levels.
Corresponding Author: Joseph M. Unger, PhD, SWOG Statistical Center, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, M3-C102, PO Box 19024, Seattle, WA 98109-1024 (email@example.com).
Published Online: October 15, 2015. doi:10.1001/jamaoncol.2015.3924.
Author Contributions: Dr Unger had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Unger, Ramsey, Hershman.
Acquisition, analysis, or interpretation of data: Unger, Gralow, Albain, Ramsey, Hershman.
Drafting of the manuscript: Unger, Hershman.
Critical revision of the manuscript for important intellectual content: Unger, Gralow, Albain, Ramsey, Hershman.
Statistical analysis: Unger.
Obtained funding: Gralow, Ramsey.
Administrative, technical, or material support: Gralow.
Study supervision: Ramsey, Hershman.
Conflict of Interest Disclosures: None reported.
Funding/Support: This work was supported by a Breast Cancer Research Foundation grant and by the National Institutes of Health, National Cancer Institute (NCI) Community Oncology Research Program Research Base grant 5UG1CA189974-01.
Role of the Funder/Sponsor: The funding organizations had a role in the design and conduct of the study and in the collection and management of the data but had no role in the analysis and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit for publication.
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