Location as Destiny: Identifying Geospatial Disparities in Radiation Treatment Interruption by Neighborhood, Race, and Insurance

Academic Article

Abstract

  • Purpose: Radiation therapy interruption (RTI) worsens cancer outcomes. Our purpose was to benchmark and map RTI across a region in the United States with known cancer outcome disparities. Methods and Materials: All radiation therapy (RT) treatments at our academic center were cataloged. Major RTI was defined as ≥5 unplanned RT appointment cancellations. Univariate and multivariable logistic and linear regression analyses identified associated factors. Major RTI was mapped by patient residence. A 2-sided P value <.0001 was considered statistically significant. Results: Between 2015 and 2017, a total of 3754 patients received RT, of whom 3744 were eligible for analysis: 962 patients (25.8%) had ≥2 RT interruptions and 337 patients (9%) had major RTI. Disparities in major RTI were seen across Medicaid versus commercial/Medicare insurance (22.5% vs 7.2%; P <.0001), low versus high predicted income (13.0% vs 5.9%; P <.0001), Black versus White race (12.0% vs 6.6%; P <.0001), and urban versus suburban treatment location (12.0% vs 6.3%; P <.0001). On multivariable analysis, increased odds of major RTI were seen for Medicaid patients (odds ratio [OR], 3.35; 95% confidence interval [CI], 2.25-5.00; P <.0001) versus those with commercial/Medicare insurance and for head and neck (OR, 3.74; 95% CI, 2.56-5.46; P <.0001), gynecologic (OR, 3.28; 95% CI, 2.09-5.15; P <.0001), and lung cancers (OR, 3.12; 95% CI, 1.96-4.97; P <.0001) compared with breast cancer. Major RTI was mapped to urban, majority Black, low-income neighborhoods and to rural, majority White, low-income regions. Conclusions: Radiation treatment interruption disproportionately affects financially and socially vulnerable patient populations and maps to high-poverty neighborhoods. Geospatial mapping affords an opportunity to correlate RT access on a neighborhood level to inform potential intervention strategies.
  • Digital Object Identifier (doi)

    Author List

  • Wakefield DV; Carnell M; Dove APH; Edmonston DY; Garner WB; Hubler A; Makepeace L; Hanson R; Ozdenerol E; Chun SG
  • Start Page

  • 815
  • End Page

  • 826
  • Volume

  • 107
  • Issue

  • 4