Disparities in Surgical Care of Patients with Colorectal Cancer Liver Metastases
摘要
Up to 25% of patients with colorectal cancer present with liver metastases (CRLM), and 50% develop metastases over time. Surgical and ablative management of CRLM can be curative, but certain demographic and socioeconomic factors disproportionately hinder vulnerable patient populations from receiving advanced local therapies.
MethodsWe queried the 2011–2021 National Cancer Database for cases of CRLM. We explored patient and facility characteristics associated with receipt of local intervention versus no intervention for metastatic liver lesions.
ResultsOf 72,273 cases, 18.0% underwent hepatectomy or ablation. Controlling for patient- and center-level factors, non-Hispanic Black and Hispanic/Latino patients were less likely to undergo liver intervention than were non-Hispanic white patients (odds ratio [OR] 0.83 [95% confidence interval (CI) 0.78–0.88] vs. OR 0.92 [95% CI 0.85–0.99]). Patients treated at academic programs had significantly higher odds of liver intervention than did those in community cancer programs (OR 2.24 [95% CI 2.06–2.43]). Patients with private, Medicaid, Medicare, or other government insurance had higher odds of liver intervention than did uninsured patients (OR 2.07 [95% CI 1.86–2.30], OR 1.40 [95% CI 1.24–1.58], OR 1.81 [95% CI 1.61–2.03], OR 2.20 [95% CI 1.81–2.66], respectively). Patients in the highest income quartile were more likely to have liver intervention than those in the lowest quartile (OR 1.18 [95% CI 1.10–1.27]). Patients receiving liver intervention traveled farther than those receiving non-surgical care (p<0.001).
ConclusionSurgical or local ablative management of CRLM is necessary to achieve cure for appropriately selected patients. However, this advanced liver interventional care is not equally distributed among patient populations. Significant socioeconomic and demographic disparities exist in the receipt of local liver interventional management among patients with CRLM and require further exploration to improve resource allocation.