Literature DB >> 29700209

At What Cost to Clinical Trial Enrollment? A Retrospective Study of Patient Travel Burden in Cancer Clinical Trials.

Hala T Borno1, Li Zhang2,3, Adam Siegel2, Emily Chang3, Charles J Ryan2,3.   

Abstract

BACKGROUND: Recent literature suggests that living in a rural setting may be associated with adverse cancer outcomes. This study examines the burden of travel from home to cancer center for clinical trial (CT) enrollees.
MATERIALS AND METHODS: Patients from the University of California San Francisco Clinical Trial Management System database who enrolled in a cancer CT for a breast, genitourinary, or gastrointestinal malignancy between 1993 and 2014 were included. Cancer type, household zip code, race/ethnicity, phase of study, study sponsor, and year of signed consent were exported. Distance traveled from home to center was calculated using a GoogleMaps application programming interface. The relationships of distance with phase of CT, household income, and race/ethnicity were examined.
RESULTS: A total of 1,600 patients were enrolled in breast (55.8%), genitourinary (29.4%), or gastrointestinal (14.9%) cancer CTs. The overall median unidirectional distance traveled from home to study site was 25.8 miles (interquartile range [IQR] 11.5-75.3). Of the trial sponsors examined, principal investigator (56.4%), industry (22.2%), cooperative group (11.6%), and National Institutes of Health (NIH; 9.8%), the longest distance traveled was for NIH-sponsored trials, with a median of 39.4 miles (p < .001). Phase I (8.4%) studies had the longest distance traveled, with a median of 41.2 miles (IQR 14.5-101.0 miles; p = .001). White patients (83%) traveled longer compared with black patients (4.4%), with median distances of 29.9 and 13.9 miles, respectively (p < .001). Patients from lower-income areas (n = 799) traveled longer distances compared with patients from higher-income areas (n = 773; 58.3 vs. 17.8 miles, respectively; p < .001). A multivariable linear model where log10 (distance) was the outcome and adjusting for the exported variables and income revealed that cancer type, year of consent, race/ethnicity, and income were significantly associated with distance traveled.
CONCLUSION: This study found that the burden of travel is highest among patients enrolled in NIH-sponsored trials, phase I studies, or living in low-income areas. These data suggest that travel burden for cancer CT participants may be significant. IMPLICATIONS FOR PRACTICE: This study is one of the first to measure travel distance for patients in cancer clinical trials using a real-world GoogleMaps calculator. Out-of-pocket expenses such as travel are not typically covered by health care payers; therefore, patients may face considerable cost to attend each study visit. Using a single-center clinical trials enrollment database, this study found that the burden of travel is highest for patients enrolled in National Institutes of Health-sponsored trials and phase I studies, as well as for patients living in low-income areas. Results suggest that a significant proportion of patients enrolled in clinical trials face a substantial travel burden. © AlphaMed Press 2018.

Entities:  

Keywords:  Cancer clinical trial disparities; Health care costs; Recruitment science; Representativeness in clinical trials; Travel distance

Mesh:

Year:  2018        PMID: 29700209      PMCID: PMC6263122          DOI: 10.1634/theoncologist.2017-0628

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  18 in total

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Review 6.  Distance as a Barrier to Cancer Diagnosis and Treatment: Review of the Literature.

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8.  Participation in cancer clinical trials: race-, sex-, and age-based disparities.

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Review 10.  The impact of socioeconomic status on access to cancer clinical trials.

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5.  Nature versus Nurture: Investigating Racial Disparity in Advanced Prostate Cancer.

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Review 6.  Undercutting efforts of precision medicine: roadblocks to minority representation in breast cancer clinical trials.

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7.  Patient-Reported Out-of-Pocket Costs and Financial Toxicity During Early-Phase Oncology Clinical Trials.

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8.  Estimating the rate and reasons of clinical trial failure in urologic oncology.

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Review 10.  Overcoming Barriers to Parkinson Disease Trial Participation: Increasing Diversity and Novel Designs for Recruitment and Retention.

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