Objective: Delay in diagnosis and treatment of endometrial cancer may be associated with disease progression and impact management and outcomes. Social and cultural barriers influence recognition of symptoms and self-advocacy in seeking and complying with care. Associations between social determinants of health (SDH) and disease presentation, treatment and outcomes has been shown in some healthcare systems. Our objective was to investigate these in Ontario’s universal access system. Methods: Endometrial cancer patients in Ontario diagnosed 2009-2017 were identified, and clinical, social and demographic information extracted from administrative databases. SDH were quantified using previously validated marginalization quintiles (material deprivation, residential instability and ethnic concentration). Associations between SDH, disease stage, treatment and outcome were explored using chi-square, log-rank and logistic regression. Results: 19530 patients were identified. 73% of cancers were confined to the uterus. Stage distribution differed across marginalization quintiles (p<0.001) with advanced disease found more frequently in highly marginalized patients (highest vs lowest quintile): OR=1.28 (95% CI 1.14-1.45) for deprivation, OR=1.2 (95% CI 1.06-1.35) for residential instability and OR=1.3 (95% CI 1.15-1.46) for ethnic concentration (<0.0001)). Highly marginalized patients also had less timely surgery (p<0.0001). Overall survival was shorter in patients in high deprivation and residential instability quintiles (log rank p-value<0.0001) but not in high ethnic concentration quintiles, with HR=1.4 for deprivation (p<0.0001) and HR=1.53 for instability (p<0.0001) for the highest marginalization quintile. Survival differences persisted in more uniform cohorts of early (stage I) disease and endometrioid tumors and on multivariable analysis. Conclusions: Marginalized populations diagnosed with uterine cancer present at more advanced stages, wait longer for surgery and have shorter overall survival. Associations of SDH with uterine cancer presentation and management in Ontario could shed light on the impact of these factors on disease trajectory, drive policies for patient advocacy and redistribution of resources and promote health equity in this population. / Thesis / Master of Public Health (MPH) / Conditions in the social environment in which people are born, live and work are powerful influencers of health and well-being. In fact, these circumstances have also been called Social Determinants of Health (SDH). Cancer outcomes are one of the domains impacted by SDH. In this study, we set out to investigate the association between SDH and uterine cancer outcomes in Ontario, Canada. We guessed that SDH may influence how soon patients with symptoms seek help from their doctors, how quickly their problem is investigated and how well they are able to undergo treatment. We used a tool called the Ontario Marginalization Index to break down Ontario’s uterine cancer patient population into groups according to degree of social, financial and ethnic marginalization. We found that more marginalized patients tended to present to care with more advanced cancers, that they took longer to have surgery for their cancer and that their survival was worse. These findings suggest there is more work to be done to promote health equity in cancer care.

INTRODUCTION: Older patients with AML (> 60 years) often receive intensive EOL care including hospitalizations and chemotherapy close to death. Intensive EOL care has been shown to increase emotional and financial burdens for patients and families, while often not aligning with patients’ preferences. However, factors associated with the intensity of EOL care in this population are unknown. OBJECTIVES: There is a need to better understand the factors associated with intense EOL care, in hopes of providing more informed, high-quality EOL care in line with patient preferences and decreasing burdens associated with unnecessary healthcare. We aim to describe the associations between the intensity of EOL care, patient demographics, and baseline psychological distress in older patients with AML. METHODS: We conducted a secondary analysis of two supportive care studies including 168 deceased older patients with AML. We assessed patients’ demographics, quality of life (QOL) [Functional Assessment Cancer Therapy-Leukemia], and anxiety and depression symptoms [Hospital Anxiety and Depression Scale (HADS); Patient Health Questionnaire (PHQ-9)] at the time of diagnosis. We used multivariate logistic regression models to examine the association among demographic factors, patient-reported outcomes, and the following EOL care outcomes abstracted from the electronic health record: 1) hospitalizations in the last 7 days of life; 2) receipt of chemotherapy in the last 30 days of life; and 3) hospice utilization. RESULTS: The median age of the cohort was 69 (range 20-100), and the majority were males (63.7% 107/168). Overall, 66.7% (110/165) of patients were hospitalized in the last 7 days of life, 51.8% (71/137) received chemotherapy in the last 30 days of life, and 40.7% (70/168) utilized hospice services. In multivariate models, higher education (OR = 1.54, SE=0.24, P=0.006), and elevated depression symptoms [PHQ-9: OR=1.09, SE=0.04, P=0.028] at the time of diagnosis were associated with higher odds of being hospitalized in the last 7 days of life. In contrast, higher QOL at diagnosis [OR=0.98, SE=0.01, P=0.009] was associated with lower odds of being hospitalized in the last 7 days of life. Depression symptoms at the time of diagnosis as measured by the HADS was the only factor associated with the receipt of chemotherapy in the last 30 days of life [HADS-Depression: OR=1.10, SE=0.05, P=0.042]. Patients factors were not associated with hospice utilization. CONCLUSIONS: Older patients with AML who are more educated and report elevated depression symptoms and lower QOL at the time of diagnosis were more likely to receive intensive EOL care. These findings identify a population at the time of diagnosis of AML who are at higher risk for hospitalizations and chemotherapy use at the EOL and who may benefit from targeted supportive care interventions.

BACKGROUND: Patient reported outcomes (PROs) are important cancer outcomes that can be measured electronically but are understudied in the safety-net hospital setting. Routine electronic screening to address social determinants of health (SDH) has been established in primary care clinics and the emergency department of New England’s largest safety-net hospital. The burden of SDH in safety-net oncology patients is less well-studied. This study aimed to determine the feasibility and challenges of routine administration of ePROMs in a safety-net Radiation Oncology clinic, describe treatment toxicities and quality of life (QOL) experienced by this vulnerable population during radiotherapy, and evaluate SDH and the need for SDH screening in the oncology clinic. METHODS: Patients with lung or head and neck cancer scheduled for radiation oncology consultation from 3/2019–1/2020 were deemed eligible for electronic questionnaire participation based on primary language spoken and absence of metastases. At consultation, patients were administered a set of baseline ePROMs (EQ-5D-3L, FACT, PRO-CTCAE) and a social needs screener (THRIVE) using a widely-used cloud-based, patient-centered outcomes platform. Associations between patient demographics and questionnaire completion were retrospectively evaluated. The set of ePROMs were collected at the end of treatment to characterize treatment-related toxicities and changes in self-reported QOL. RESULTS: In total, 99 eligible head and neck cancer (51.5%) and lung cancer (48.5%) patients were identified. Median age was 65. The majority of patients were male (71.7%), and English-speaking (82.8%). Whites, Blacks, and Asians/Others comprised 42.4%, 38.4%, and 6.1% of patients, respectively. Fifteen patients were Hispanic (15.2%). Patients were most likely to have private health insurance (39.4%), followed by joint Medicare-Medicaid (25.3%), Medicaid (17.2%), and Medicare (16.2%). Two patients were insured by Corrections (2.0%). Eight patients (8.1%) no-showed or cancelled, while 91 patients were seen in consultation. Forty-four patients (48.4%) completed the initial questionnaires. For the remaining 47 patients (51.6%), the most common reason for lack of ePROM completion was clinic understaffing and/or clinical decision based on the absence of indication for radiotherapy (n=27, 57.4%). Ten patients refused to complete questionnaires (21.3%), with reasons cited including length of questionnaires and low energy. Ten patients were physically unable to attempt questionnaires (21.3%), for reasons including disabilities and low-literacy. Age, language, race, ethnicity, insurance, marital status, gender, and disease site were not significantly associated with ePROM completion (P≥0.05). For patients who completed the general (QOL) questionnaire EQ-5D-3L, there was no significant difference in general QOL domains nor self-reported overall health score at baseline vs. end of treatment. For head and neck cancer patients, FACT-H&N Total scores, measuring disease-specific QOL, were significantly worse at end of treatment vs. baseline (P=0.006). For lung cancer patients, FACT-L Total scores at the end of radiation treatment were not significantly worse at end of treatment vs. baseline (P=0.953). For head and neck cancer patients who completed PRO-CTCAE, there was a significant increase in the number with moderate to very severe taste issues (P=0.008) and decrease in appetite (P=0.025) by end of treatment. For lung cancer patients, there was a trend towards an increase in the number reporting moderate to very severe nausea (P=0.083). Eighty-one of 99 patients (81.8%) were screened for at least one SDH domain using the THRIVE screener at the study hospital. Nineteen patients (19.1%) had all 8 THRIVE social determinants of health statuses documented. Only housing status was documented for 61 patients (61.6%). There was a trend for married individuals (P=0.068) and females (P=0.074) to be associated with the completion of at least one THRIVE domain. Age, race, language, and insurance status were not associated with THRIVE screening (P>0.05). Transportation to appointments (21.1%), food insecurity (20%), and affording medications (10.5%) were the most prevalent concerns among these oncology patients, with 100% of patients who reported insecurities with medication and transportation requesting resources for these needs. CONCLUSION: Routine ePROs collection in a busy safety-net oncology setting is feasible, but challenging and labor-intensive. Implementation was met with both patient and staff challenges and revealed the need for dedicated project management, staff training, and opportunities to increase patient accessibility. Preliminary PROs analyses revealed several significant detriments in quality of life and increased symptoms for this patient population during treatment, but additional data collection is required. Safety-net oncology patients report significant social needs. Routine SDH screening and resource referral should be considered in these vulnerable patients. Efforts in a specialized department such as Radiation Oncology could fill gaps in existing efforts in a large safety-net hospital. Safety-net oncology clinics can likely help vulnerable cancer patients access available community resources and reduce disparities due to SDH.