Associations between insurance status and the cancer clinical trial enrollment process. Issue 28 (1st October 2022)

• Record Type: Journal Article
• Authors: Caston, Nicole E.; Lalor, Fallon; Wall, Jaclyn; Sussell, Jesse; Patel, Shilpen A.; Williams, Courtney; Azuero, Andres; Arend, Rebecca Christian; Liang, Margaret Irene; Rocque, Gabrielle Betty
• Is Part Of: Journal of clinical oncology. Volume 40:Issue 28(2022)Supplement
• Page Start: 85
• Page End: 85
• Publication Date: 2022-10-01
• Subjects: 298-145-222 -- 329-334-348 -- 283-252-190 -- 329-334-532 -- 329-334-533 -- 281-318-5774; 6 -- 3 -- 2 -- 2 -- 2 -- 2; Oncology -- Periodicals; Cancer -- Periodicals; Oncology; Medical Oncology; Cancérologie -- Périodiques; Cancer -- Périodiques; Cancérologie; Cancer; Oncology; Oncologia; Càncer; Periodicals; 616.994
• DOI: 10.1200/JCO.2022.40.28_suppl.085
• Languages: English
• ISSNs: 0732-183X

Abstract

Abstract : 85 Background: Most patients with cancer experience multi-leveled barriers to clinical trial participation, potentially including financial concerns due to the complexity surrounding trial-related insurance coverage. Our study sought to understand the association between insurance status and cancer clinical trial eligibility, offer, and enrollment. Methods: This retrospective cohort study included patients with breast or ovarian cancer receiving a therapeutic cancer drug at the University of Alabama at Birmingham between January 2017 and February 2020. Available clinical trials and eligibility criteria were abstracted from OnCore and ClinicalTrials.gov. Patient trial eligibility, offer from provider, demographics, and clinical characteristics were abstracted from electronic medical records. Patient trial enrollment was determined via OnCore. Odds of clinical trial eligibility, offer, and enrollment by insurance status (private, public [Medicaid, Medicare]) were estimated using logistic regression models. Models estimating odds of trial offer and enrollment contained only eligible patients. Models were adjusted for patient age at diagnosis, race and ethnicity, rural-urban residence, Area Deprivation Index, cancer type, and cancer stage (early, late). Results: A total of 513 patients with breast (71%) or ovarian (29%) cancer were included in our analyses. Median age at diagnosis was 60 (interquartile range: 49-67) years; the majority were White (69%) and had early stage cancer (65%). Half of patients had private insurance (54%), and 46% of patients had public insurance (38% Medicare, 8% Medicaid). Patients with private insurance more often had early stage cancer compared to patients with public insurance (73% vs 57%). Almost two-thirds of patients (65%) were eligible for clinical trial enrollment. Of eligible patients (n = 333), 68% were offered a trial and 47% enrolled onto a trial. In adjusted analyses, patients with public vs private insurance had similar odds of clinical trial eligibility (odds ratio [OR] 0.95, 95% confidence intervals [CI] 0.61-1.48), being offered to participate (OR 1.23, 95% CI 0.71-2.14), and clinical trial enrollment (OR 1.13, 95% CI 0.68-1.89). Conclusions: Our results suggest oncologists do not assess trial eligibility or offering a trial based on insurance status, and patients do not differentially participate based on their insurance coverage. Further research is needed to understand implications of trial participation (e.g., out-of-pocket and time costs) for patients covered by differing insurance.