Ten-Year Single Institutional Analysis of Geographic and Demographic Characteristics of Patients Treated With Stereotactic Body Radiation Therapy for Localized Prostate Cancer.

SBRT (stereotactic body radiation therapy) disparities (health) machine learning prostate cancer racial travel distance treatment burden

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2020
Historique:
received: 11 10 2020
accepted: 23 12 2020
entrez: 15 3 2021
pubmed: 16 3 2021
medline: 16 3 2021
Statut: epublish

Résumé

Stereotactic Body Radiation Therapy (SBRT) offers definitive treatment for localized prostate cancer with comparable efficacy and toxicity to conventionally fractionated radiotherapy. Decreasing the number of treatment visits from over 40 to five may ease treatment burden and increase accessibility for logistically challenged patients. Travel distance is one factor that affects a patient's access to treatment and is often related to geographic location and socioeconomic status. In this study, we review the demographic and geographic factors of patients treated with SBRT for prostate cancer for a single institution with over a decade of experience. Patient zip codes from one thousand and thirty-five patients were derived from a large, prospectively maintained quality of life database for patients treated for prostate cancer with SBRT from 2008 to 2017. The geospatial distance between the centroid of each zip code to our institution was calculated using the R package Geosphere. Characteristics for seven hundred and twenty-one patients were evaluated at the time of analysis including: race, age, and insurance status. To assess the geographic reach of our institution, we evaluated the demographic features of each zip code using US Census data. Statistical comparisons for these features and their relation to distance traveled for treatment was performed using the Mann-Whitney U test. Finally, an unsupervised learning algorithm was performed to identify distinct clusters of patients with respect to median income, racial makeup, educational level, and rural residency. Patients traveled from 246 distinct zip codes at a median distance of 11.35 miles. Forty percent of patients were African American, 6.9% resided in a rural region, and 22% were over the age of 75. Using K-means cluster analysis, four distinct patient zip-code groups were identified based on the aforementioned demographic features: Suburban/high-income (45%), Urban (30%), Suburban/low-income (17%), and Rural (8%). For each of the clusters, the average travel distance for SBRT was significantly different at 11.17, 9.26, 11.75, and 40.2 miles, respectively (p-value: <0.001). Distinct demographic features are related to travel distance for prostate SBRT. In our large cohort, travel distance did not prevent uptake of prostate SBRT in African American, elderly or rural patient populations. Prostate SBRT offers a diverse population modern treatment for their localized prostate cancer and particularly for those who live significant distances from a treatment center.

Identifiants

pubmed: 33718117
doi: 10.3389/fonc.2020.616286
pmc: PMC7947279
doi:

Types de publication

Journal Article

Langues

eng

Pagination

616286

Informations de copyright

Copyright © 2021 Aghdam, Carrasquilla, Wang, Pepin, Danner, Ayoob, Yung, Collins, Kumar, Suy, Collins and Lischalk.

Déclaration de conflit d'intérêts

SC, BC, and JL serve as clinical consultants to Accuray Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Nima Aghdam (N)

Department of Radiation Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States.

Michael Carrasquilla (M)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Edina Wang (E)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Abigail N Pepin (AN)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.
George Washington University School of Medicine, Washington, DC, United States.

Malika Danner (M)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Marilyn Ayoob (M)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Thomas Yung (T)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Brian T Collins (BT)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Deepak Kumar (D)

The Julius L. Chambers Biomedical Biotechnology Research Institute, North Carolina Central University, Durham, NC, United States.

Simeng Suy (S)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Sean P Collins (SP)

Department of Radiation Medicine, MedStar Georgetown University Hospital, Washington, DC, United States.

Jonathan W Lischalk (JW)

Perlmutter Cancer Center, Langone Medical Center, New York University, New York, NY, United States.

Classifications MeSH