Disparities in Rectal Cancer: Moving from Descriptions to Solutions

Abstract

Although healthcare disparities, particularly in surgery and cancer, have been abundantly described, potential solutions have been lacking. Aptly presented by Lee and colleagues in this issue of the Annals of Surgical Oncology, disparities can occur anywhere along the patient care continuum.1 Because of the numerous sources of healthcare disparities, a concerted effort is needed to successfully mitigate them. 2,3Lee and colleagues highlight three interconnected sources of healthcare disparities within the context of cancer: obtaining healthcare access, provider-level factors, and patient-level factors. Using the National Cancer Data Base, the authors investigated whether the differences in receipt of neoadjuvant therapy and survival for adolescents and young adults (AYAs; aged 15-39 years) with clinical stage II-III rectal cancer were associated with race and ethnicity (non-Hispanic white, Hispanic, black, and others). They discovered that nonoperative management occurred most frequently in blacks (22.4 %) and Hispanics (21.6 %) compared with non-Hispanic whites (12.3 %; p \ 0.0001). On multivariable analysis, insurance coverage rather than race/ethnicity was associated with undergoing surgery. Similarly, neoadjuvant therapy was omitted more frequently in blacks (37.9 %) and Hispanics (42.2 %) compared with non-Hispanic whites (27.9 %; p \ 0.05).On multivariable analysis, both insurance coverage and race/ethnicity were associated with receipt of neoadjuvant therapy. On multivariable survival analysis, lack of insurance [hazard ratio (HR) 1.71, 95 % confidence interval (CI) 1.08-2.70] and having government insurance (HR 1.86, 95 % CI 1.33-2.59) not race/ethnicity were most significantly associated with poorer survival. Taken together, the data argue that socioeconomic status, rather than sociodemographic status, account for the survival differences in this AYA population.

Cancer treatment and the risk of cancer death among Aboriginal and non-Aboriginal South Australians: analysis of a matched cohort study

“…Firstly, Aboriginal cases up to 24% less likely to be hospitalised with a primary diagnosis of cancer than their non-Indigenous contemporaries. Secondly, once hospitalised, differences in utilisation and quality of care [60, 61] were apparent and fewer Aboriginal patients received surgery, systemic therapies or radiotherapy. Effective, systematic responses are needed to address these gaps in service access, utilisation and quality.…”

The fraction of life years lost after diagnosis (FLYLAD): a person-centred measure of cancer burden

“…FLYLAD also demonstrated an ability to enumerate disparities in cancer burden associated with stage and ancestry 24-months after cancer diagnosis, a time during which people are more likely to be receiving care through health services [ 46 ]. This becomes particularly useful in supporting activities that promote access [ 61 ], uptake and quality [ 15 , 62 ] of effective and available cancer treatments. In short, FLYLAD enumerates people’s capacity to benefit from cancer control initiatives involving prevention, early detection and treatment and thus contributes to prioritising health system activities.…”

The premature mortality to incidence ratio (PREMIER): a person-centred measure of cancer burden

“…PREMIER also demonstrated an ability to enumerate disparities in cancer burden associated with stage and ethnicity 24-months after cancer diagnosis, a time during which people are more likely to be receiving care through health services [45]. This becomes particularly useful in supporting activities that promote access [60], uptake and quality [15, 61] of effective and available cancer treatments. In short, PREMIER enumerates people’s capacity to benefit from cancer control initiatives involving prevention, early detection and treatment and thus contributes to prioritising health system activities.…”

“…This higher fatal burden is influenced by comparatively greater incidence of cancers with poor survival [5,7,8], diagnoses at more advanced stage [9][10][11], lower exposure to cancer treatment [9,12], and excess case fatality concentrated in the first two-years after diagnosis [13]. Each of these influences suggest an unmet capacity to benefit from cancer control initiatives and actions including augmented cancer screening programs and addressing variations in treatment [14][15][16]. Such interventions need to be accompanied by relevant performance measures; measures which ensure system accountability [17], first by articulating disparity, then quantifying the capacity to benefit from prevention, early detection and intervention.…”