Patterns of decision making about cancer clinical trial participation among the online cancer treatment community: A collaboration between SWOG and NexCura.

Abstract

CRA6009 Background: Studies have shown an association between socioeconomic status (SES) and quality of oncology care, but less is known about the impact of SES on decision-making about CT participation. Methods: We assessed patterns of CT treatment decision-making according to important SES and demographic factors (age, sex, race, income, education) in a large sample of patients surveyed via a web-based treatment decision tool (NexCura, The Woodlands, TX). Eligible patients had a new diagnosis of breast, lung, colorectal, or prostate cancer, and were >18. Logistic regression (conditioning on type of cancer) was used. Reasons for non-participation in CTs were assessed using pre-specified items about treatment, family, cost, and logistics. All data were self-reported. Results: 5,499 patients were surveyed from 2007-2011. 40% discussed CTs with their physician; this differed by age (42% <65 v. 29% >65), income (42% >$50k/yr v. 36% <$50k/yr), and education (42% >college degree (CD) v. 37% <CD). 45% of discussions led to offers of CT participation, and 51% of offers led to CT participation. The overall CT participation rate was 9%, differing by age, income, and education (see table below). In a multivariate model including all SES and demographic factors (plus covariates comorbidity status and “distance to clinic”, a surrogate for convenience), income remained a predictor of CT participation (OR 0.73, 95% CI, 0.57-0.94, p=.01). Even in patients >65, who are nearly universally covered by Medicare, lower income predicted reduced CT participation (age by income interaction test, p>.05). Cost concerns were much more evident among lower income patients (p=.0001). Conclusions: Lower income patients were less likely to participate in CTs, even when considering age group.A better understanding of why income is a barrier may help identify ways to make CTs better available to all patients, and would increase the generalizability of CT study results across all levels of SES. [Table: see text]