Disparities in refusal of surgery for gynecologic cancer.

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.

Factors contributing to delays in initiation of front-line cervical cancer therapy: disparities in a diverse south Florida population.

OBJECTIVE: Delay in initiating cervical cancer treatment may impact outcomes. In a cohort of patients initially treated by surgery, chemoradiation, chemotherapy, or in a clinical trial, we aim to define factors contributing to prolonged time to treatment initiation. METHODS: Data from patients initiating treatment for cervical cancer at a single institution was abstracted. Time to treatment initiation was defined as the interval from the date of cancer diagnosis to the date of treatment initiation. Poisson regression model was used for analysis. RESULTS: Of 274 patients studied, the median time to treatment initiation was 60 days (range 0-551). The median times to initiate surgery (54 days, range 3-96) and chemoradiation (58 days, range 4-187) were not significantly different (relative risk (RR) 1.01, 95% CI 0.98 to 1.04, p=0.54). The shortest median initiation time was for chemotherapy (47 days; RR 1.13, 95% CI 1.08 to 1.19, p<0.0001) and the longest was for clinical trial (62 days; RR 1.18, 95% CI 1.12 to 1.24, p<0.0001). Charity care (RR 1.09, 95% CI 1.05 to 1.14, p<0.0001), Medicare or Medicaid (RR 1.10, 95% CI 1.06 to 1.14, p<0.0001), and self-pay (RR 1.38, 95% CI 1.32 to 1.45, p<0.0001) delayed treatment initiation more than private insurance. Hispanic White women (RR 0.69, 95% CI 0.66 to 0.73, p<0.0001) had a shorter treatment initiation time compared with non-Hispanic White patients, while Afro-Caribbean/Afro-Latina women (RR 0.86, 95% CI 0.81 to 0.90, p<0.0001) and African-American patients (RR 1.13, 95% CI 1.07 to 1.19, p<0.0001) had longer initiation times. Spanish speaking patients did not have a prolonged treatment initiation (RR 0.68, 95% CI 0.66 to 0.71, p<0.0001), though Haitian-Creole speaking patients did (RR 1.07, 95% CI 1.01 to 1.13, p<0.002). Diagnosis at an outside institution delayed treatment initiation time (RR 1.24, 95% CI 1.18 to 1.30, p<0.0001) compared with diagnosis at the cancer center. CONCLUSION: Factors associated with prolonged time to treatment initiation include treatment modality, insurance status, language spoken, and institution of diagnosis. By closely examining each of these factors, barriers to treatment can be identified and modified to shorten treatment initiation time.