Journal Basic Info

  • Impact Factor: 2.709**
  • H-Index: 11 
  • ISSN: 2474-1663
  • DOI: 10.25107/2474-1663
**Impact Factor calculated based on Google Scholar Citations. Please contact us for any more details.

Major Scope

  •  Urological Cancers
  •  Blood Cancer
  •  Cervical Cancer
  •  Prostate Cancer
  •  Breast Cancer
  •  Adjuvant Therapy
  •  Thoracic Oncology
  •  Stomach Cancer


Citation: Clin Oncol. 2021;6(1):1880.DOI: 10.25107/2474-1663.1880

Assessing Barriers to Cancer Clinical Trial Enrollment: A Potential Application of a Clinical Decision-Support Tool

Shawn Hsu, Ana Paula Cupertino, Fergal Fleming, David C Linehan, Arpan Patel, Patrick Reagan, Katherine J Rosen, Eric Snyder, Myla Strawderman, Larissa Temple and Paul Barr

Department of Surgery, University of Rochester Medical Center, USA
James P Wilmot Cancer Institute, Community Outreach & Engagement, University of Rochester Medical Center, USA
Division of Hematology/Oncology, University of Rochester School of Medicine and Dentistry, USA
Department of Biostatistics and Computational Biology, University of Rochester, USA

*Correspondance to: Shawn Hsu 

 PDF  Full Text Research Article | Open Access


Introduction: Despite the importance of clinical trials for improving cancer therapies, enrollment in clinical trials remains limited and many trials are interrupted due to barriers to enrollment. Identifying clinical trial recruitment barriers is necessary to guide future interventions to improve this process.
Methods: This is a retrospective study from April 2019 to October 2020 at a multi-site academic medical system. New cancer patients receiving systemic chemotherapy navigated using a decisionsupport tool were identified and categorized based on a hierarchical framework for clinical trial recruitment, which includes structural, clinical, physician, and patient domains. Multivariable
logistic regression was performed to determine predictors of progression through each barrier domain.
Results: A total of 1,725 patients with breast, gastrointestinal, genitourinary, lung, or hematopoietic cancers were navigated using the decision-support tool and 15.5% were referred for clinical trial screening. Overall, 72.3% (1,248/1,725) of patients did not have a trial available and 27.0% (129/477) of patients with a trial available were ineligible. There were significant differences in trial availability (p<0.0001) and eligibility (p<0.0001) between different tumor groups. Among those eligible for an available trial, breast cancer patients and those ≥ 75 years old were less likely to be referred for clinical trial screening. Participation rates were similar for Black patients (89%, 95% CI = 71% to 98%) and white patients (91%, 95% CI = 88% to 95%).
Conclusion: Trial availability was the most significant barrier to clinical trial enrollment. Decisionsupport platforms are promising tools for understanding enrollment barriers and facilitating recruitment. Future studies will explore specific reasons for differences in trial availability across tumor groups.


Cite the Article:

Hsu S, Cupertino AP, Fleming F, Linehan DC, Patel A, Reagan P, et al. Assessing Barriers to Cancer Clinical Trial Enrollment: A Potential Application of a Clinical Decision-Support Tool. Clin Oncol. 2021;6:1880..

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