Disparities in refusal of surgery for gynecologic cancer

Gynecol Oncol. 2023 Jul:174:1-10. doi: 10.1016/j.ygyno.2023.04.017. Epub 2023 May 2.

Abstract

Objective: To identify sociodemographic and clinical factors associated with refusal of gynecologic cancer surgery and to estimate its effect on overall survival.

Methods: The National Cancer Database was surveyed for patients with uterine, cervical or ovarian/fallopian tube/primary peritoneal cancer treated between 2004 and 2017. Univariate and multivariate logistic regression were used to assess associations between clinico-demographic variables and refusal of surgery. Overall survival was estimated using the Kaplan-Meier method. Trends in refusal over time were evaluated using joinpoint regression.

Results: Of 788,164 women included in our analysis, 5875 (0.75%) patients refused surgery recommended by their treating oncologist. Patients who refused surgery were older at diagnosis (72.4 vs 60.3 years, p < 0.001) and more likely Black (OR 1.77 95% CI 1.62-1.92). Refusal of surgery was associated with uninsured status (OR 2.94 95% CI 2.49-3.46), Medicaid coverage (OR 2.79 95% CI 2.46-3.18), low regional high school graduation (OR 1.18 95% CI 1.05-1.33) and treatment at a community hospital (OR 1.59 95% CI 1.42-1.78). Patients who refused surgery had lower median overall survival (1.0 vs 14.0 years, p < 0.01) and this difference persisted across disease sites. Between 2008 and 2017, there was a significant increase in refusal of surgery annually (annual percent change +1.41%, p < 0.05).

Conclusions: Multiple social determinants of health are independently associated with refusal of surgery for gynecologic cancer. Given that patients who refuse surgery are more likely from vulnerable, underserved populations and have inferior survival, refusal of surgery should be considered a surgical healthcare disparity and tackled as such.

Keywords: Gynecologic oncology; Healthcare disparities; National cancer database; Refusal of surgery.

MeSH terms

  • Aged
  • Female
  • Healthcare Disparities* / statistics & numerical data
  • Humans
  • Kaplan-Meier Estimate
  • Logistic Models
  • Medicaid / statistics & numerical data
  • Medically Uninsured / statistics & numerical data
  • Middle Aged
  • Ovarian Neoplasms* / mortality
  • Ovarian Neoplasms* / surgery
  • Proportional Hazards Models
  • Treatment Refusal* / statistics & numerical data
  • United States / epidemiology
  • Vulnerable Populations / statistics & numerical data