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237 Background: We performed plasma-based high-plex proteomic profiling for identifying classifiers of clinical outcomes in metastatic prostate cancer (PC). Olink Explore NGS-based proteome profiling platform was used for high-precision analysis of 736 cancer associated plasma proteins in plasma samples from non-metastatic stage prostate cancer (PC), metastatic hormone-sensitive PC (mHSPC) and metastatic castrate resistant PC (mCRPC) states. Methods: Plasma was collected prospectively in a cohort of 108 PC patients (24 with non-metastatic PC; 28 mHSPC; 56 mCRPC of which 37 patients were collected before starting any mCRPC treatments). Proteomic data were generated with Proximity Extension Assay (PEA) on the Olink platform from 100 µL plasma per sample. Levels of 736 cancer-associated protein assays were denoted as normalized protein expression (NPX) units through a QC and normalization process developed and provided by Olink. Data generation of NPX consists of normalization to the extension control, log2 -transformation, and level adjustment using the plate control (plasma sample). Temporal trends of differentially expressed assays in non-metastatic PC, mHSPC and mCRPC states were identified using linear mixed effects model (FDR with Benjamini-Hochberg (BH) adjustment; q-value

218 Background: Adolescents and young adults (AYAs; ages 18-39) with cancer report worries about costs and feeling uninformed about their insurance, which may impair their ability to navigate the health care system, use their insurance, and manage costs. We conducted a pilot randomized controlled trial (RCT) to assess a virtually delivered health insurance navigation intervention (“CHAT”) to improve health insurance literacy (HIL) and knowledge, increase awareness of insurance protections in the Affordable Care Act (ACA), and reduce financial toxicity and stress. Methods: CHAT is a 4-session program delivered by a patient navigator. Session content included learning about insurance, navigating your plan, insurance-related laws, & managing care costs. Eligible participants had access to a wireless device, were within their first year of cancer diagnosis, and were treated at oncology sites from the University of Utah Healthcare and Intermountain Healthcare systems. We assessed feasibility and preliminary efficacy of CHAT compared to usual navigation care, including HIL (9 items on confidence using insurance), insurance knowledge (13 items on terms such as deductible & copay), ACA protections (8 items), Perceived Stress Scale (PSS; 4 items), and COmprehensive Score for financial Toxicity (COST; 11 items) using t-tests. Results: From November 2020 to January 2022, 86 AYAs enrolled (46.2% approached consented); 68.6% were female, 72.1% white, 18.6% Hispanic, 34.9% age 18-25, 65.1% age 26-39, 83.7% had private insurance, and 10.5% public. Mean baseline HIL scores were 22.6 (range = 9-33, SD = 5.5). At baseline, 65.1% of participants were unaware of the ACA provision allowing appeals for coverage denials. 64.4% of intervention participants completed all 4 sessions; 86.0% completed the 5-month follow-up survey with data collection ongoing (74/86). At follow-up, compared to usual navigation care, CHAT participants had improvements in HIL, knowledge of insurance, and knowledge of ACA provisions (Table). While PSS improved more for CHAT than usual care, COST did not differ. Conclusions: Results support the feasibility and preliminary efficacy of CHAT with related improvements in HIL and knowledge of the ACA. Clinical trial information: NCT04448678. [Table: see text]

15 Background: We previously demonstrated that Huntsman at Home (HH), a novel oncology hospital at home program, was associated with reduced healthcare utilization and costs. HH was also linked to shorter hospital stays and fewer emergency room (ER) visits. In this study, we sought to understand the impact of HH in specific patient subgroups. Methods: We compared outcomes among 169 patients consecutively admitted to HH against 198 usual care patients. Five dichotomous subgroups were created based upon patient a) sex b) age c) area level median income d) Charlson Comorbidity Index (CCI), and e) current use of systemic therapy (ST). Outcomes included 30-day costs, unplanned hospitalizations (UH), length of hospital stays, and ER visits. HH and usual care were compared via inverse propensity weighted regression models. Treatment propensities were estimated via random forests based on age, race, stage, cancer site, presence of metastases, CCI, and area level median income.Results: The between group difference favoring HH achieved statistical significance (p < 0.05) for at least two out of the four outcomes in each subgroup except for patients with higher comorbid illnesses. While HH participants did not always experience statistically better outcomes than usual care, none of the outcomes examined favored usual care for any subgroup. Sex. Female and male HH patients experienced fewer UH and lower costs than usual care. Male HH patients also had shorter hospital stays and fewer ED visits. Age. When stratifying age at 65 years, older HH patients experienced fewer days in the hospital and fewer UH. Younger HH patients had lower costs, and fewer UH and ED visits. Area level Income. All outcomes were better for high and low income HH patients compared to usual care except for ED visits among those with low income. CCI. Among those with a low CCI score, all four outcomes were better among HH patients. In contrast, differences between groups with higher comorbid illness did not achieve statistical significance for any outcome. Systemic Therapy. HH participants on ST experienced shorter hospital stays and fewer UH compared to usual care. Among those not on ST, HH patients experienced lower costs, and fewer UH and ED admissions. Conclusions: In this exploratory analysis, we found that the utilization and cost benefit associated with HH was robust, favoring better outcomes in each subgroup including lower 30-day costs, shorter hospital length of stay and fewer unplanned hospitalizations or ER visits. While medically complex patients may not receive similar benefit from HH as other subgroups, no outcomes favored patients managed by usual care. Taken together, this suggests that health care utilization and cost reductions associated with HH occur across multiple subgroups, but patients with high comorbidity may require additional intervention to realize lower utilization and costs.

377 Background: Among patients diagnosed with mNSCLC, significant declines in fat and muscle mass are common, yet there is a paucity of data related to body composition, QoL, TD, and survival. Accordingly, we evaluated the relationship between body composition via routine CT scans, patient-reported outcomes (PROs), and overall survival (OS) among a convenience sample of mNSCLC patients. Methods: Data from 80 mNSCLC patients with initial CT scans and NCI PROMIS questionnaires within the first three months of diagnosis were analyzed. Body composition from CT scans (sliceOmatic software) extracted Skeletal muscle (SM), intermuscular adipose tissue (IAT), visceral VAT, and subcutaneous (SAT) in area (cm2) and a discovery set was expressed as HU. PROMIS PROs (pain, fatigue, anxiety, depression, and physical function) were collected in clinic using an iPad as an institutional quality initiative. Results: Median time to OS was 16 months. When stratified by sex, females had longer median survival time (female 25 months, male 14 months). When all body composition variables were considered together, greater amounts of skeletal muscle were linked with a 63% reduction in mortality risk 0.37 (95% CI 0.16, 0.87) in the adjusted model. Per one-unit increase in VAT (area cm2) was linked with a 0.04 unit decrease in pain (95% CI -0.08, -0.01). Associations between HU and clinical were also observed. Greater amount of VAT (mean HU) was linked with 2.57(95% CI 1.10, 6.01) times the odds of death in the crude model. Also, in crude model, one unit of increase in skeletal muscle (mean HU) was associated with 0.3 (95% CI 0.03, 0.57) unit increase in physical functionality, and -0.34(95% CI -0.63, -0.05)) unit decrease in fatigue. Conclusions: Body composition data can be collected from retrospective scans and appears to be prognostic of OS, PRO and TD.