This study sought to illuminate the relationship between ADI and QOL performance following ablative surgery for breast cancer. After adjusting for competing risk factors, we found that patients from high ADI neighborhoods had significantly lower BREAST-Q psychosocial well-being and SF-12 global physical quality of life. In addition, our unadjusted results suggest that residents of areas with high economic deprivation were likely to have a high BMI and a racial background that was Black or Hispanic. This latter finding is consistent with a larger body of work that has documented racialized economic and residential segregation, upheld by sustained divestment, predatory lending policies, limited educational opportunities, and structural racism.[33, 34] Collectively, these results also suggest that the assertion “zip codes matter more than genetic code”[35, 36] has some credence with respect to surgical outcomes (clinical and PROs). Therefore, initiatives designed to improve surgical outcomes must address both patient- and community-level factors.
Neighborhoods are complex environments with a variety of economic, social, and physical characteristics that have a significant impact on the health of the residing individual. According to some estimates, the SDoH contribute > 50% of the modifiable factors that drive health outcomes.[38, 39] A recent paper by Hyer et al documented a higher risk of adverse outcomes and 20% lower odds of attaining “textbook outcomes” among individuals with high social vulnerability following major cancer surgery. Therefore, contextualizing the association between the SDoH, as represented by area-level deprivation, and health outcomes in cancer care is of great interest to payers, physicians, patients, and policymakers. In light of recently signaled Medicare interest in utilizing PROs and functional outcomes as markers of healthcare quality, our aforementioned results also enrich the policy salience of the extant literature.
There are several conceivable explanations for our finding, including the premise that patients from vulnerable neighborhoods are more likely to face cumulative lifelong stress (i.e. allostatic load), such as anxiety for personal safety, chronic food and housing insecurity, and exposure to violence, the enduring impact of which has implications for QoL outcomes.[19, 37] Additionally, financial toxicity, which is the economic burden of treatment-associated costs on patients and their families, has been strongly correlated with worse post-operative condition-specific and global QOL in breast cancer patients.[23, 41] This provides an additional explanatory framework for our findings as ADI is likely to be highly correlative with financial toxicity. Lastly, patients from vulnerable neighborhoods have been associated with low health literacy and reduced access to physicians, resulting in differences in health maintenance and knowledge gaps.[42, 43] This is important because the surgical management of breast cancer is preference-sensitive with different risks, complications and benefits associated with each choice i.e. lumpectomy, mastectomy, and receipt of reconstruction. These knowledge gaps not only undermine the quality of patient decision-making, but they also contribute to a discrepancy between pre-operative expectations and post-operative outcomes, which subsequently engenders poor QoL performance.
Previous studies have also shown that unrealistic patient expectations predict adverse outcomes, such as a worsening in functional status and health-related quality of life. Unrealistic expectations, for example, may cause patients to become easily discouraged with postoperative therapy and nonadherent to postoperative recommendations. Patients with low expectations may also lack the motivation needed to continue with therapy, resulting in patients not receiving the full benefit of breast cancer surgery. Therefore, measures should be taken to better understand what patients in deprived neighborhoods expect after breast cancer surgery, so that services may be provided to fulfill these needs and ensure alignment between patients and breast surgeons as they jointly work toward the same goals.
Although beyond our study scope and the expertise of our research team, we hope that our results serve to catalyze efforts to operationalize the assessment of the SDoH in breast cancer care encounters. Pursuant to this, ADI can be used as a scalable tool for identifying populations at high risk of poor outcomes following breast cancer surgery by integrating it with the electronic medical record. A treatment plan based on this assessment might now entail a social work consult, use of patient navigators, and referrals to community-based services and financial assistance for immediate resource allocation. Furthermore, increasing the interdisciplinary care team’s awareness of and engagement with the SDoH will measurably enhance the patient-provider relationship.
Our study should be viewed in light of limitations including the single-institution, cross-sectional design. Our institution is a specialized, quaternary referral center, and results may not be generalizable to all practice settings. Our study included only a population of insured women undergoing breast cancer surgery, yet ADI was still associated with patient-reported outcomes. This only strengthens our findings; effect sizes are expected to be magnified in the general population with worse socioeconomic characteristics, particularly among those without baseline insurance coverage. The outcomes were measured at a single point in time and do not demonstrate a causal relationship. Finally, all patient-reported outcomes were self-reported. We minimized reporting bias by using objective data from patient medical records, employing validated patient-reported outcome measures, and administering the survey within 18 months of surgery. In addition, by including only consecutive patients, we were able to minimize selection bias. Future prospective multicenter studies that address these limitations are needed. Notwithstanding, our study is the first to assess the impact of ADI on patient-reported outcomes after breast cancer surgery using validated measures and robust statistical analysis.