Leveraging the Dynamic Immune Environment Triad in Patients with Breast Cancer: Tumour, Lymph Node, and Peripheral Blood

SIMPLE SUMMARY: The primary, secondary and tertiary immune sites, namely the tumour microenvironment (TME), the lymph nodes (LNs) and the peripheral blood, form the cardinal trinity of immune environments in breast cancer. With the success of immuno-therapies in some subtypes of breast cancers, an integrated understanding of these intertwined immune sites is essential to potentiate their anti-cancer responses and enhance the efficacies of therapeutic agents, and in turn, illuminate novel pathways of anti-cancer immunity and therapeutic opportunities. ABSTRACT: During the anti-tumour response to breast cancer, the primary tumour, the peripheral blood, and the lymph nodes each play unique roles. Immunological features at each site reveal evidence of continuous immune cross-talk between them before, during and after treatment. As such, immune responses to breast cancer are found to be highly dynamic and truly systemic, integrating three distinct immune sites, complex cell-migration highways, as well as the temporal dimension of disease progression and treatment. In this review, we provide a connective summary of the dynamic immune environment triad of breast cancer. It is critical that future studies seek to establish dynamic immune profiles, constituting multiple sites, that capture the systemic immune response to breast cancer and define patient-selection parameters resulting in more significant overall responses and survival rates for breast cancer patients

The Role of Community-Based Organizations in Improving Chronic Care for Safety-Net Populations

IntroductionSocial determinants of health (SDoH) influence health outcomes and contribute to disparities in chronic disease in vulnerable populations. To inform health system strategies to address SDoH, we conducted a multi-stakeholder qualitative study to capture the multi-level influences on health for those living in socio-economically deprived contexts.MethodsVaried qualitative inquiry methods - in-depth interviews, participant-led neighborhood tours, and clinic visit observations - involving a total of 23 participants (10 patients with chronic illnesses in San Francisco neighborhoods with high chronic disease rates, 10 community leaders serving the same neighborhoods, and 3 providers from San Francisco's public health care delivery system). Qualitative analyses were guided by the Chronic Care Model (CCM).ResultsSeveral key themes emerged from this study. First, we enumerated a large array, neighborhood resources such as food pantries, parks/green spaces, and financial assistance services that interact with patients' self-management. Health service providers leveraged these resources to address patients' social needs but suggested a clear need for expanding this work. Second, analyses uncovered multiple essential mechanisms by which community-based organizations (CBOs) provided and navigated among many neighborhood health resources, including social support and culturally aligned knowledge. Finally, many examples of how structural issues such as institutional racism, transportation, and housing inequities are intertwined with health and social service delivery were elucidated.ConclusionThe results contribute new evidence toward the community domain of the CCM. Health care systems must intentionally partner with CBOs to address SDoH and improve community resources for chronic care management, and directly address structural issues to make progress

Assessing Alignment of Patient and Clinician Perspectives on Community Health Resources for Chronic Disease Management

Addressing social determinants of health (SDoH) is associated with improved clinical outcomes for patients with chronic diseases in safety-net settings. This qualitative study supplemented by descriptive quantitative analysis investigates the degree of alignment between patient and clinicians’ perceptions of SDoH resources and referrals in clinics within the public healthcare delivery system in San Francisco. We conducted a qualitative analysis of in-depth interviews, patient-led neighborhood tours, and in-person clinic visit observations with 10 patients and 7 primary care clinicians. Using a convergent parallel mixed methodology, we also completed a descriptive quantitative analysis comparing the categories of neighborhood health resources mentioned by patients or community leaders to the resources integrated into the electronic health record. We found that patients held a wealth of knowledge about neighborhood resources relevant to SDoH that were highly localized and specific to their communities. In addition, multiple stakeholders were involved in conducting SDoH screenings and referrals, including clinicians, system navigators such as case workers, and community-based organizations. Yet, the information flow between these stakeholders and patients lacked systematization, and the prioritization of social needs by patients and clinicians was misaligned, as represented by qualitative themes as well as quantitative differences in resource category distribution analysis (p < 0.001). Our results shed light upon opportunities for strengthening social care delivery in safety-net healthcare settings by improving patient engagement, clinic workflow, EHR engagement, and resource dissemination