scholarly journals P1.06-009 Barriers to Clinical Trial Participation in Lung Cancer Patients, a Single Institution Experience

2017 ◽  
Vol 12 (11) ◽  
pp. S1989
Author(s):  
C. Geiger ◽  
K. Baker ◽  
M. Redman ◽  
B. Goulart ◽  
K. Eaton ◽  
...  
2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18548-e18548
Author(s):  
Grace E. Mishkin ◽  
Luisa Franzini

e18548 Background: Disparities in clinical trial participation can mean disparities in medical advances, and disproportionate participation is an ethical issue even if differential results are not expected. The disparate impact of Covid-19 highlighted the importance of representativeness in trials aiming to prevent or treat disease. Previous analyses suggest there are likely significant differences in cancer clinical trial participants by race, ethnicity, and age. However, these analyses generally compare trial demographics to broad population demographics. Methods: This analysis used the SEER-Medicare linked database with claims data from 2014-2016 to compare lung cancer clinical trial participants to similar lung cancer patients not participating in a treatment trial. We compared the race, ethnicity, sex, age, and number of comorbidities for Medicare beneficiaries with at least one claim for an active treatment for lung cancer to the demographics of Medicare beneficiaries with at least one claim coded with the National Clinical Trials (NCT) number for an active treatment trial in lung cancer. The relationship between clinical trial participation and demographic variables was assessed using chi-square tests for binary variables and t-tests for continuous variables and corrected for multiplicity. A logistic regression model was used to assess robustness of these findings. Clinical trial participants were hypothesized to be more likely to be White, non-Hispanic, and male, and have a lower mean age and fewer comorbidities than the comparable non-trial active treatment population. Results: We compared 1,624 lung cancer clinical trial patients to 34,077 active treatment lung cancer patients. Clinical trial participants were more likely than non-trial active treatment patients to be female (53.6% vs. 50.4%, p = 0.015) or Asian/Pacific Islander (13.0% vs. 5.2%, p < 0.001) and less likely to be Black (5.2% vs. 9.0%, p < 0.001) or White (76.5% vs. 81.4%, p < 0.001). Trial participants had a lower mean age (70.7 vs. 73.7, p < 0.001) and fewer comorbidities (3.0 vs. 4.6, p < 0.001). There was not a significant difference by Hispanic ethnicity (5.2% vs. 4.4%, p = 0.106). The regression analyses supported these findings. Conclusions: Most analyses of clinical trials enrollment do not have a direct comparison group. Because this study is directly comparing lung cancer trial participants and non-participants from the same Medicare beneficiary population, the results fill a gap in our understanding of disparities in cancer clinical trial participation. Trial participants in this analysis were more representative than hypothesized, although the results supported previous findings that Black patients and older patients are underrepresented in cancer trials. There was also lower participation by White patients. Underrepresentation of patients with comorbidities may be due to trial eligibility criteria.


2015 ◽  
Vol 33 (29_suppl) ◽  
pp. 26-26 ◽  
Author(s):  
Toby Christopher Campbell

26 Background: Clinical trials are crucial to the development of new treatments that may improve survival and quality of life for patients. Cancer clinical trials are hampered by chronically low participation rates. A decision support intervention designed to facilitate a shared decision making discussion with cancer patients regarding chemotherapy options could help oncologists align patient preferences with treatment options, including clinical trials. We performed a retrospective chart review comparing lung cancer patients seen in our integrated onco-palliative care clinic (PC) with standard oncology care (SOC) patients for clinical trial participation as a means of assessing potential effectiveness of the tool. The PC clinic is staffed exclusively by the author who also developed the tool. The tool is a combination of a structured discussion paired with a paper diagram the patient takes home which details all the treatment options including best supportive care alone, standard chemotherapy, and a clinical trial. Methods: Charts of every patient seen in our institution with advanced lung cancer from July 2007-June 2011 were reviewed. Eligible patients were those who received any care at our center thus excluding patient seen only for a second opinion. Demographic, treatment details, survival, and hospice utilization data were obtained. There were five oncologists included the SOC group though the vast majority of patients were seen by two providers. All providers (PC and SOC) are academic physicians who work closely together, meet weekly, have clinic on the same day, share the same research staff and have the same promotion requirements. Results: 207 patients with advanced lung cancer were identified, 82 in the PC group. A significantly higher proportion of patients participated in therapeutic clinical trials in the PC group when compared to the SOC group (29% versus 19%, adjusted OR = 2.54, p = 0.014). No difference in overall chemotherapy utilization was seen between the groups. Conclusions: Our chart review provides initial evidence that the best case/worst case: clinical trials tool may help facilitate clinical trial participation in patients with advanced lung cancer who are exploring their options.


BMC Cancer ◽  
2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Sean Pollock ◽  
Ricky O’Brien ◽  
Kuldeep Makhija ◽  
Fiona Hegi-Johnson ◽  
Jane Ludbrook ◽  
...  

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