Lee, Minji

Abstract Background: Financial toxicity can have devastating long-term effects for cancer patients (pts) and their family members which may impact their access to care, adherence and, ultimately, outcomes. Identifying those at greatest risk is key to mitigating costs and distress to pts. Here we report results from a screening questionnaire on financial risks among Southeast Asian (SE-A) pts. Methods: This retrospective review included pts on the cancer patient registry at Mayo Clinic (Arizona, Florida, Minnesota, Wisconsin, and Iowa) who had completed a clinical visit in an oncology-related department (hematology, medical oncology, radiation oncology, etc) within the past 270 days prior to 6/4/24. Pts completed an electronic social determinant of health questionnaire of which financial risks and transportation needs are the focus of this study: 1) how hard is it for you to pay for the very basics like food, housing, medical care, and heating? 2) in the past 12 months, has lack of transportation kept you from medical appointments or from getting medications. Our primary endpoints include the association between financial risks, active bad debts (defined as having >$5000 owed for high active bad debt, $0-$5000 for some active bad debt), pre-appointment review (PAR) flag status and transportation needs. Descriptive statistics and Chi-square were used to analyze factors associated with financial risks. Results: We identified 81, 731 pts who completed the questionnaire, among whom 387 were SE-A. Compared to non-SE-A and White, 6.5% have some active bad debt vs 3.3% and 3.6% (p<0.001), and 1.0% had high active bad debt vs 0.8% and 0.7% (p<.001); 58.4% had low financial risk vs 60% and 66% (p<0.001) and 2.3% with high risk vs 1.5% and 1.6% (p<0.001), 4.1% declined to answer and 29.7% were unknown. Bad debt was associated with PAR flag (P <0.001) and financial risk (P<0.001). For transportation among SE-A, 2.3% had unmet transportation needs, 1.8% declined/unable to answer, while 17.8% were unknown. Those with transportation needs were associated with active debt and financial risk (p<0.001). Conclusion: In this cohort, we identified SE-A with highest rates of active debt and higher financial risks compared to Non-SE-A and White. A large percentage of patients declined to answer or are unknown. Future pilot questionnaire is in development to identify pts concerns for medical costs, financial strain and the receptivity to be connected to resources/referrals to address them. Citation Format: Nguyen H. Tran, Jordan Mason, Wendy Hanson, Kimberly Steinbert, Minji Lee, Robert McWilliams. Financial risks in southeast asian patients with cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7094.

12040 Background: Novel strategies are needed to assess frailty in the context of therapy decisions for older adults with acute myeloid leukemia (AML). Our objectives were to describe pre-treatment DAFI scores for older AML patients treated on clinical trials and explore their relationship with treatment outcomes. Methods: We conducted a exploratory analysis utilizing data from two clinical trials of adults aged ≥60 years with newly diagnosed AML (Alliance/CALGB 11001 [intensive therapy] and Alliance/CALGB 11002 [non-intensive therapy]). We included the subset of patients in each trial enrolled on geriatric assessment companion studies (Alliance/CALGB 361006, 361101). A DAFI score was calculated for each patient using 51 variables including demographic, geriatric assessment, and laboratory data derived from the geriatric assessment. Individuals with ≥90% items were included (consistent with other studies); DAFI scores ranged from 0 to 1 and were evaluated using established categories (0- <.2 [robust]; 0.2-<.35 [pre-frail]; 0.35+ [frail]) and as a continuous score. Associations between DAFI scores and toxicity and overall survival (OS) were evaluated with Fisher’s exact-testing and Kaplan Meier/cox proportional hazards, respectively. Results: The median age was 68 years (range 61, 82) and 72 years (range 61, 92) for those getting intensive (N=31) and less intensive therapy (N= 75), respectively. Individuals in the intensive study had a median pre-treatment DAFI score of 0.15 (range 0.05, 0.31) and were all categorized as robust (75%) or pre-frail (25%). There was no significant difference in median OS (14.6 vs. 14.7 months) or non-hematological grade 3+ adverse events (AEs; 85% vs. 89%) between robust vs. pre-frail individuals in this trial, respectively. However, pre-frail adults experienced a trend towards greater grade 4 non-hematological toxicity than robust individuals (67% vs 26%, p=0.05). In the non-intensive trial, the median DAFI score was 0.24 (range 0.04, 0.48) and most individuals were pre-frail (49.3%) or frail (17.3%). Non-hematologic grade 3+ AEs did not vary by DAFI group, 88% robust, 95% pre-frail, and 77% frail (p=0.15). Median OS was 7.4, 10.8, and 6.3 months for robust, pre-frail, and frail respectively (p=0.17). Adjusting for age, each 0.1 increase in DAFI score was associated with increased mortality hazard (HR 1.8, 95% CI 1.0-3.2). Conclusions: DAFI score calculation provides a potential novel strategy for categorization of frailty in AML. In our assessment, higher DAFI scores were associated with toxicity during intensive induction and mortality in the less intensive setting. This method should be studied in larger samples randomized by treatment intensity. Support: UG1CA189823; Bayer Healthcare/Berlex (CALGB 11001); NCT01253070 (CALGB 11001). Clinical trial information: NCT01253070, NCT01420926.

5554 Background: A better understanding regarding the burden of treatment side effects in patients with gynecological malignancies could help guide symptom interventions and oncologic therapy decision-making. We aim to inform understanding of symptom burden in epithelial ovarian cancer (EOC) by analyzing patient-reported symptom data from patients treated for this condition over a 16-month period. Methods: Patients receiving medical oncology care at Mayo Clinic Rochester and at Midwest Mayo Clinic Health System community sites have received symptom-focused surveys prior to each medical oncology visit since March 28, 2019 through the Enhanced Electronic Health Record Facilitated Cancer Symptom Control Study (E2C2). These surveys, administered either through the electronic medical record portal or on a clinic tablet prior to each oncology office visit, no more frequently than every 2 weeks, include six linear analogue scales measuring sleep disturbance, pain, anxiety, emotional distress, and fatigue (SPADE), as well as physical dysfunction on a scale of 0 (none) to 10 (as bad as you can imagine). Scores of 0-3 were considered mild symptoms, 4-6 moderate symptoms, and 7-10 severe symptoms. We collected survey results from March 28, 2019 to July 20, 2020 for patients with EOC and reviewed the number of surveys per patient in addition to the average symptom scores. Results: From March 2019 to July 2020, for patients with EOC, there were 2974 encounter-based surveys from 762 patients. The number of surveys completed by each patient ranged from 1-20. The following number of patients returned the correlating number of surveys: 1 survey:240 patients; 2 surveys:145; 3 surveys:79; 4 surveys:56; 5 surveys:58; 6 surveys:45; 7 surveys:38; 8 surveys:27; 9 surveys:22; ≥10 surveys:52. The average score from all surveys for each symptom was: 2.41 for sleep disturbance, 2.03 for pain, 2.32 for anxiety, 1.97 for emotional distress, 3.26 for fatigue, and 2.50 for physical dysfunction. Please see the table for the proportion of surveys that reported symptoms as mild, moderate, or severe. Conclusions: Fatigue and physical dysfunction were reported most frequently in patients with EOC, while emotional distress and pain were reported least frequently. 20% of surveys reported moderate to severe emotional distress, while 40% reported moderate to severe fatigue. A targeted approach to symptom management is needed for patients undergoing EOC evaluation and treatment. Our next steps in this analysis include an assessment of potential predictors of greater symptom burden (e.g., specific treatments, age, and other clinical and sociodemographic characteristics). Clinical trial information: NCT03892967. [Table: see text]