e16569 Background: Diet can modulate the gut microbiome and may affect ICB efficacy. In a cohort of pts with mUC on ICB, we previously reported associations of longer PFS with high dietary fiber and low dietary fructose. These associations were independent of clinical factors. However, observational studies can be affected by confounding, so we sought to determine if confounding by predictors of metabolic health explained our prior findings. Methods: In a retrospective analysis of a prospectively collected cohort, we leveraged dietary data collected with the Harvard Willett Food Frequency Questionnaire from pts with mUC initiating ICB at Memorial Sloan Kettering to assess for associations between PFS and baseline BMI, daily caloric intake (cal/d), and dietary glucose. These were treated as continuous variables and log transformed if skewed. Associations with PFS were assessed by univariate (UV) & multivariable (MV) Cox proportional hazards regression. Results: From 2/2021-6/2022, 38 pts eligible for analysis enrolled. Median follow-up was 10.4 months with 27 PFS events. Median (with interquartile range) for each variable of interest: fiber 17 g/day (13-22); fructose 15 g/day (12-31); BMI 26.5 kg/m2 (23.4-30.4); glucose 15 g/day (11-25); cal/d 1,597 (1,091-1,939). Visceral metastases were present in 21 (55%) pts, and 5 (13%) had prior ICB. BMI, glucose, and cal/d were not associated with PFS in UV models (BMI HR 0.27, 95% CI 0.02-3.29, p=0.31; glucose HR 1.46, 95% CI 0.74-2.86, p=0.27; cal/d HR 0.74, 95% CI 0.30-1.79, p=0.50), models adjusted for tumor mutational burden, Bellmunt risk factors, and prior ICB (BMI HR 0.34, 95% CI 0.02-4.96; p=0.43; glucose HR 1.3, 95% CI 0.63-2.64, p=0.49; cal/d HR 0.51, 95% CI 0.19-1.40, p=0.19), nor models adjusted for fiber and fructose intake (BMI HR 0.27, 95% CI 0.02-3.11; p=0.29; glucose HR 0.51, 95% CI 0.06-4.61, p=0.55; cal/d HR 0.67, 95% CI 0.13-3.45, p=0.63). Associations of fiber and fructose intake with PFS persisted after adjusting for BMI, glucose, and cal/d (Table 1). Conclusions: In mUC, BMI, cal/d, and dietary glucose were not associated with PFS on ICB. Confounding by these variables did not account for associations of high dietary fiber and low dietary fructose with longer PFS. Hazard ratios (HR) with 95% confidence intervals (CI) for PFS. All MV models included fiber & fructose. Dietary variable UV models Model for fiber & fructose together Adjusted for BMI Adjusted for glucose intake Adjusted for cal/d Fiber, g/day 0.98 (0.94-1.02); p = 0.28 0.90 (0.84-0.97); p = 0.005 0.91 (0.85-0.97); p = 0.004 0.91 (0.84-0.97); p = 0.008 0.91 (0.84-0.996); p = 0.04 Fructose, log(g/day) 1.66 (0.89-3.09); p = 0.11 5.02 (2.06-12.23); p = 0.0004 5.06 (2.08-12.32); p = 0.0004 8.65 (1.16-64.30); p = 0.035 5.44 (2.08-14.18); p = 0.0005

355 Background: Hospitalized patients with advanced cancer face a challenging post-discharge care transition due to their high symptom burden. Post-discharge interventions are needed to address the unique needs of this population. Methods: We conducted a randomized controlled trial of CONTINUUM (Continuity of Care Under Management by video visits), a post-discharge telehealth intervention for patients with advanced solid tumors. The primary aim was to assess the effect of CONTINUUM on the Patient Activation Measure-13 (PAM-13), a measure of patients’ confidence in managing their health condition, which is associated with decreased health care utilization. From 12/2021-01/2025, we approached English-speaking patients with advanced solid tumors during their first unplanned hospitalization since advanced cancer diagnosis who were preparing for discharge to home without hospice. Enrolled patients were randomized 1:1 to CONTINUUM or usual care. Those assigned to CONTINUUM received a telehealth visit with an oncology nurse practitioner within 3 business days of hospital discharge to address symptoms, in addition to usual scheduled oncology appointments. Patients in the control group attended their usual appointments. Participants completed questionnaires at baseline and 10-20 days post-discharge. Secondary outcomes included physical symptoms (Edmonton Symptom Assessment System-physical [ESAS-p]), psychological distress (Patient Health Questionnaire-4[PHQ-4]), satisfaction with communication (Consumer Assessment of Healthcare Providers and Systems Communication Subscale [CAHPS]), and 30-day hospital readmissions. We used analysis of covariance to assess the between-group differences in post-discharge outcomes, adjusting for baseline scores, and Fisher’s exact test to compare the proportion with hospital readmission. Results: Of 286 enrolled patients (mean age: 64.5 years; 50.0% female; 85.3% White; 46.2% gastrointestinal cancers), the most common reason for admission was symptom management (62.5%). Patient activation declined between time points in both groups, but post-discharge PAM-13 scores did not differ between intervention and control group (adjusted mean: 62.5 vs. 65.3, respectively, p = 0.162). Physical and psychological symptoms did not differ between groups (ESAS-p adjusted mean: 26.6 vs. 25.1, P = 0.368; PHQ-4 adjusted mean: 2.7 vs. 2.3, p = 0.245). CAHPS scores were similar between groups (unadjusted mean: 18.9 vs. 18.8, p = 0.839). We found no significant difference in the 30-day hospital readmission rates (27.7% vs. 29.2%, p = 0.794). Conclusions: CONTINUUM did not improve patient-reported outcomes or hospital readmission rates in recently hospitalized patients with advanced cancer. Future studies should explore targeted home-based and longitudinal interventions to enhance post-discharge care for this patient population. Clinical trial information: NCT05142345 .

11003 Background: Patients with cancer receiving curative treatment often endure substantial symptoms and utilize significant healthcare resources. Symptom monitoring interventions and hospital at home care models represent a promising approach for improving these patients’ outcomes. Methods: We conducted a randomized trial of a Supportive Oncology Care at Home intervention versus usual care in adult patients receiving treatment with curative intent (chemotherapy and/or chemoradiation) for pancreatic, rectal, gastroesophageal, and head and neck (H&N) cancer, as well as non-Hodgkin lymphoma, who resided in-state, within 50 miles of our hospital. Patients were randomized to receive the Supportive Oncology Care at Home intervention or usual care within two weeks of initiating therapy and remained on trial for up to 6 months. The intervention entailed: 1) remote monitoring of daily patient-reported symptoms, vital signs, and body weight; 2) a hospital at home care model for symptom assessment and management; and 3) structured communication with the oncology team. The primary outcome was the proportion of patients requiring inpatient hospital admission or emergency department (ED) visits during the study period. Secondary outcomes included urgent visits to the clinic, treatment delays, and longitudinal changes in monthly assessments of quality of life (QOL; Functional Assessment of Cancer Therapy-General), symptoms (Edmonton Symptom Assessment System [ESAS] and Hospital Anxiety and Depression Scale [HADS]), and activities of daily living (ADLs). Results: We enrolled 50.8% (199/392) of potentially eligible patients. One patient withdrew consent and 2 became ineligible following consent, resulting in 196 participants (median age=65.8 [range: 21.1-92.0], 39.8% female, cancer types: 34.2% pancreatic, 27.0% H&N, 16.3% lymphoma, 12.8% rectal, 9.7% gastroesophageal). The proportion of patients requiring hospital admission or ED visit did not differ significantly between the intervention and usual care groups (37.1% v 35.7%, p=.87). Intervention participants were less likely to require an urgent visit (7.2% v 24.5%, p<.01), but there were no differences in rates of treatment delays >7 days (29.9% v 33.0%, p=.62). Compared to baseline assessments, intervention participants had greater improvement in ESAS symptoms (p<.01) and ADLs (p=.04) over time. QOL and HADS depression/anxiety symptoms did not differ longitudinally between groups. Conclusions: Although this Supportive Oncology Care at Home intervention did not have a significant impact on rates of hospital admissions or ED visits, we found encouraging results for reducing urgent visits to the clinic and substantial improvement in symptom burden and ADLs, underscoring the potential utility of this novel care model for enhancing care delivery and outcomes for patients with cancer receiving curative treatment. Clinical trial information: NCT04544046 .

e17009 Background: Black and Latino men face disproportionately higher risks prostate cancer (PC) and PC-related mortality compared to White men. Moreover, Black and Latino men taking androgen deprivation therapy (ADT) for PC report relatively lower quality of life (QOL), partially due to ADT side effects. While physical activity ameliorates ADT side effects and improves QOL, few interventions exist to increase physical activity and help manage ADT side effects for these groups. The aim of this study was to develop and refine a culturally-responsive, cognitive-behavioral intervention, PROWESS (PROstate cancer Wearables Exercise and Structured Supports) to increase physical activity, manage ADT side effects, and improve QOL for Black and Latino men with PC on ADT. Methods: We conducted a single-arm open pilot trial (n=16) of a cognitive-behavioral intervention for English- or Spanish-speaking Black and Latino men with PC on ADT to explore the intervention's feasibility and participants' satisfaction. Participants attended a once-weekly, six-session telehealth intervention led by a psychologist to enhance physical activity, symptom management, and QOL in groups of 3-5 men. They completed online questionnaires, including the Client Satisfaction Questionnaire-3 (CSQ-3, Range: 4-12), post-intervention and an optional exit interview. Participants received a Fitbit for the duration of the program to set physical activity goals and monitor progress. Results: We enrolled 16 of 33 approached patients (48.5%). Of 16 enrolled patients (median age=70.0 years; 84.6% Black, 23.1% Latino), 13 (81.3%) participated in the intervention. Three groups were conducted in English, and one was conducted in Spanish. Twelve out of 13 participants (92.3%) attended at least 4 sessions, and 6 (46.2%) attended all 6 sessions. Twelve out of 13 participants (92.3%) completed post-intervention surveys. Participants found the intervention acceptable, as indicated by high median CSQ-3 scores (11.0, Inter-Quartile Range 10.5-12.0). Out of 12 participants who agreed to use a Fitbit, 9 (75.0%) wore their Fitbit at least once, and 3 (25.0%) wore the Fitbit all 12 weeks. Exit interview data showed high satisfaction with the group format, especially the opportunity to meet other men from similar backgrounds going through PC treatment. Participants noted gaining knowledge and skills regarding side effect management and coping. They did not, however, find the Fitbit or focus on increasing physical activity as helpful as the other intervention targets. Conclusions: The high proportion of intervention completion and satisfaction with PROWESS supports further testing of the intervention in a randomized trial. Exit interview data highlight the importance of social connection, coping skills, and side effect management for improving QOL for Black and Latino men on ADT. Clinical trial information: NCT05755490 .

To assess patient characteristics associated with acceptability of a hypothetical hospital at home (HaH) program in patients hospitalized with cancer and describe associated caregiver characteristics and clinical needs. A cross-sectional survey assessing acceptability of a hypothetical HaH program was completed by 250 patients and 33 caregivers. Eligible patients were English-speaking adults (18 + years), admitted to the medicine service at a cancer hospital. Unpaid adult caregivers were surveyed as well. The median age of patients was 63, 134 (54

To break the cycle of "rehabbed to death" in oncology, we must focus on improving communication and care coordination.

11088 Background: Patients with cancer using post-acute care facilities have poor outcomes, including delayed return home and increased health care utilization. However, little is known about post-acute care use and outcomes among patients with cancer undergoing surgery. Methods: We examined Medicare claims of 100% of fee-for-service Medicare beneficiaries from 2010-2022, to identify patients who underwent inpatient cancer-directed surgery and were thus eligible for a post-acute facility stay. We used billing codes within 3 days of hospital discharge to identify post-acute facility stays, defined as skilled nursing facility (SNF), long-term acute care hospital (LTACH), or inpatient rehabilitation facility (IRF) stays. We used logistic regression to identify patient sociodemographic and clinical factors associated with post-acute care facility use. We also compared hospital readmissions within 30 days and days at home (defined as days not in an acute or post-acute facility) in the 90 days after discharge by setting, using Chi-square and Wilcoxon rank sum tests. Results: We studied 1,637,792 Medicare beneficiaries who underwent inpatient cancer surgery from 2010 to 2022. About half (48.9%) were women; median age was 73.0 years. The most common cancer diagnoses were colorectal (28.4%), lung (14.4%), and prostate (12.1%), and 22.7% had a Charlson comorbidity index (CCI) of ≥3. Overall, 16.0% of patients were discharged to a post-acute care facility (11.4% SNF, 4.5% LTACH/IRF). Discharge to post-acute care was greater among patients who were aged ≥80 vs 65-69 (Adjusted Odds Ratio[AOR] 3.85, 95% Confidence Interval[CI] 3.79,3.90), had CCI ≥3 versus 0 (AOR 2.92, 95%CI 2.88,2.95), were dual-eligible (AOR 2.01, 95%CI 1.99,2.04), or had metastatic cancer (AOR 1.26, 95%CI 1.24,1.28). Patients undergoing brain or spinal surgeries for primary or metastatic cancers had highest odds of PAC facility utilization. Compared to those discharged home, patients discharged to post-acute care facilities had a higher 30-day hospital readmission rates (18.6% vs. 9.5%, p<0.0001), and fewer days at home in the 90 days after discharge from their index surgical admission (median 68 vs. 90 days, p<0.0001). Conclusions: Patients with cancer undergoing inpatient surgery who are older, have comorbidities, or have advanced disease have higher rates of post-acute care facility use, and such post-acute care is associated with higher hospital readmissions and fewer post-operative days at home. Further work is needed to improve pre-operative decision-making and optimization as well as to develop supportive care and rehabilitative interventions that can improve post-operative outcomes for patients who need post post-acute care.

Context Patients with advanced cancer are at increased risk for multiple hospitalizations and often have considerable needs post-discharge. Interventions to address patients’ needs after transitioning home are lacking. Objectives We sought to demonstrate the feasibility and acceptability of a post-discharge intervention for this population. Methods We conducted a single-arm pilot trial (n=54) of a post-discharge intervention, consisting of a video visit with an oncology nurse practitioner (NP) within three days of discharge to address symptoms, medications, hospitalization-related issues, and care coordination. We enrolled English-speaking adults with advanced breast, gastrointestinal, genitourinary, or thoracic cancers experiencing an unplanned hospitalization and preparing for discharge home. The intervention was deemed feasible if ≥70% of approached patients enrolled and ≥70% of enrolled patients completed the intervention within three days of discharge. Two weeks after discharge, patients rated the ease and usefulness of the video technology on a 0-10 scale (higher scores indicate greater ease of use). NPs completed post-intervention surveys to assess protocol adherence. Results We enrolled 54 of 75 approached patients (77.3%). Of enrolled patients (median age=65.0 years), 83.3% participated in the intervention within three days of discharge. The median ease of participating in the intervention was 9.0 (IQR: 6.0-10.0) and the median usefulness of the intervention was 7.0 (IQR: 4.5-8.0). The majority of visits focused on symptom management (85.7%), followed by post-hospital medical issues (69.0%). Conclusion An oncology NP-delivered intervention immediately after hospital discharge is a feasible and acceptable approach to providing post-discharge care for hospitalized patients with advanced cancer.

1548 Background: Hospital at Home (HaH) is part of a comprehensive patient-centered model that delivers multidisciplinary acute medical care in the home. While HaH has mainly been tested in general medical patients, uncertainties persist regarding the feasibility and acceptability of this model within oncology populations. This study assessed patient and caregiver characteristics associated with acceptability of a hypothetical HaH program in persons hospitalized with cancer and described patient medical needs. Methods: A cross-sectional survey assessing acceptability of a hypothetical HaH program, home characteristics, and demographics was completed by 250 patients and 33 caregivers. Eligible patients were English-speaking adults (18+ years) admitted to the medicine service at a cancer hospital. Acceptability was measured on a 5-point Likert scale and defined as responses of “strongly agree” or “agree” to the statement, “I would consent to the use of my home for my hospital care” if such a program were available. Surveys were conducted in person or via telephone during the index hospitalization. Unpaid adult caregivers were surveyed in person and acceptability of the hypothetical HaH program was similarly assessed. Characteristics of the hospitalization were assessed via the electronic health record. Continuous variables were compared between acceptability groups using Wilcoxon rank sum test; categorical variables were compared using Fisher’s exact test and Pearson’s chi-squared test. Results: Median patient age was 63, 134 (54%) were female, 38 (16%) identified as Black and 21 (8.8%) as Hispanic, and 171 (72%) completed some college education or more. 208 patients (83%) rated participation in HaH as acceptable, as did 28 (85%) caregivers. Patients living with metastatic disease were more likely to accept HaH (p<0.05). Acceptability differed by race (p<.05) and was lowest among Black patients (74%) and those who preferred not to provide their race (70%). Of those who rated HaH acceptable, 137 (66%) had advanced imaging or a surgical procedure after the first day of admission and 21 (10%) had an absolute contraindication to being hospitalized at home such as a home member using illicit drugs at home (15, 7%). Conclusions: Over 80% of persons hospitalized with cancer and their caregivers would agree to HaH. Those with advanced disease were more likely to agree to home hospitalization compared to curative-intent patients, but Black patients were less likely to agree to be hospitalized at home compared to white patients. Many patients had hospitalization characteristics (e.g., imaging) that may be challenging to coordinate from home, but few patients had safety-related contraindications to HaH. These findings will inform future efforts to evaluate and target HaH programs in oncology to patients most likely to agree to and benefit from them, and address barriers to uptake in certain racially minoritized populations.

1544 Background: Half of patients with advanced cancer experience multiple hospital readmissions, which are burdensome to patients and their family members. During hospitalization, nurses provide assistance with medication administration, activities of daily living (ADLs), and other care needs. However, it is not known how nursing support required during hospitalization may relate to hospital readmissions. Using data from a post-discharge supportive care trial, we analyzed the association between nursing acuity on day of discharge to home and 30-day rehospitalization among patients with advanced cancer. Methods: The data for this exploratory analysis came from a single-arm pilot trial (n=54) of a nurse practitioner-led supportive care telehealth intervention at Massachusetts General Hospital (MGH). We enrolled English-speaking adults with advanced breast, gastrointestinal, genitourinary, or thoracic cancers who had an unplanned hospitalization and were being discharged home without hospice. MGH uses the Harris Healthcare AcuityPlus workload and productivity system to measure patients’ need for nursing care twice daily, in order to define nurse staffing levels. AcuityPlus groups patients into six levels of acuity (1=0-5 hours; 2=5-7 hours; 3=7-10 hours; 4=10-14 hours; 5=14-20 hours; 6=20+ hours). We conducted chart reviews to determine 30-day hospital readmission rates and analyzed the last AcuityPlus assessment before hospital discharge. We described rates of 30-day hospital readmissions by nursing acuity level. Results: From 01/07/21 to 05/28/21, we enrolled 54 patients (median age=65.0 years; 59.3% and 22.2% had advanced gastrointestinal or thoracic cancers, respectively). On day of discharge, no patients were classified as acuity level 1, while 25.9% of patients were classified as acuity level 2. 53.7% were in acuity level 3 and 20.4% were in acuity levels 4-6. Further, at discharge, 64.8% of patients received partial or extended assistance with ADLs, and 53.7% were assessed at least every 2 hours. At 30 days, 10 (18.5%) patients were readmitted to the hospital, all of whom were in acuity category 3 or higher on the day of discharge. No patients in acuity level 2 were readmitted. Conclusions: In this cohort of hospitalized patients with advanced cancer enrolled in a post-discharge supportive care study, overall need for nursing care, ADL support, and assessment was high, with over 70% of patients receiving at least 7 hours of nursing care on the day of discharge. While some nursing care received was influenced by inpatient nursing protocols, all readmitted patients had high nursing needs at discharge. These results support further study in larger cohorts of the relationship between inpatient nursing needs and likelihood of readmission in hospitalized patients with advanced cancer to improve support at home for recently hospitalized patients. Clinical trial information: NCT04640714 .

The majority of men with prostate cancer are diagnosed when they are older than 65 years; however, clinical trial participants are disproportionately younger and more fit than the real-world population treated in typical clinical practices. It is, therefore, unknown whether the optimal approach to prostate cancer treatment is the same for older men as it is for younger and/or more fit men. Short screening tools can be used to efficiently assess frailty, functional status, life expectancy, and treatment toxicity risk. These risk assessment tools allow for targeted interventions to increase a patient's reserve and improve treatment tolerance, potentially allowing more men to experience the benefit of the significant recent treatment advances in prostate cancer. Treatment plans should also take into consideration each patient's individual goals and values considered within their overall health and social context to reduce barriers to care. In this review, we will discuss evidence-based risk assessment and decision tools for older men with prostate cancer, highlight intervention strategies to improve treatment tolerance, and contextualize these tools within the current treatment landscape for prostate cancer.

Introduction: Chronic lymphocytic leukemia (CLL) commonly affects older adults. However, few studies have examined the relationship between baseline geriatric domains and clinical outcomes in this population. Here, we aim to evaluate the use of a comprehensive geriatric assessment in older (>65 years) untreated patients with CLL to predict outcomes.Materials and Methods: We conducted a planned analysis of 369 patients with CLL age 65 or older treated in a phase 3 randomized trial of bendamustine plus rituximab versus ibrutinib plus rituximab versus ibrutinib alone (A041202). Patients underwent evaluations of geriatric domains including functional status, psychological sta-tus, social activity, cognition, social support, and nutritional status. We examined associations among baseline geriatric domains with grade 3+ adverse events using multivariable logistic regression and overall survival (OS) and progression-free survival (PFS) using multivariable Cox regression models.Results: In this study, the median age was 71 years (range: 65-87). In the combined multivariable model, the following geriatric domains were significantly associated with PFS: Medical Outcomes Study (MOS) -social activities survey score (hazard ratio [HR] [95% confidence interval (CI)] 0.974(0.961, 0.988), p = 0.0002) and nutritional status (& GE;5% weight loss in the preceding six months: (HR [95% CI] 2.717[1.696, 4.354], p < 0.001). MOS -social activities score [HR (95% CI) 0.978(0.958, 0.999), p = 0.038] was associated with OS. No geriatric domains were significantly associated with toxicity. There were no statistically significant interactions between geriatric domains and treatment.Discussion: Geriatric domains of social activity and nutritional status were associated with OS and/or PFS in older adults with CLL. These findings highlight the importance of assessing geriatric domains to identify high-risk patients with CLL who may benefit from additional support during treatment.

Recent advances in cancer therapy have led to a decrease in cancer mortality and an increase in the number of patients living longer with advanced cancer. This chapter provides a broad overview of the phases of advanced cancer from diagnosis to end-of-life transitions to equip palliative care clinicians to optimally support their patients. It also presents evidence for impactful ways that palliative care clinicians can improve care delivery throughout the cancer trajectory. Finally, the chapter provides specific recommendations for discussion points to facilitate dialogue and collaboration between palliative care clinicians and oncology teams.

6578 Background: Previous work has shown that patients with solid tumors with an unplanned hospital admission have a median overall survival of approximately six months, and readmission rates are high within this patient population, especially near the end of life. However, the relationship between multiple unplanned hospital admissions and survival and whether patient characteristics are associated with differences in survival have not been studied in this patient population. Methods: We recorded all hospital admissions to an inpatient oncology unit for patients with solid tumors from October 1, 2021, through September 30, 2022 and categorized admissions as planned (chemotherapy administration or desensitization) or unplanned. For all unplanned admissions we reviewed the electronic health record for unplanned admissions in the previous six months. For patients with one or more prior unplanned admission, we captured demographics, admitting diagnosis, discharge disposition, and vital status including date of death. We examined median overall survival for patients with two unplanned hospital admissions within six months, median survival for patients with three or more unplanned hospital admissions within six months and 90-day survival in patients with two or more unplanned admission. We also used multivariate Cox proportional hazards models to evaluate whether patient demographics, cancer type, and hospital length of stay were associated with differences in survival. Results: There were 1,561 unplanned admissions during the period of analysis. Of these admissions, 692 (44%) were preceded by at least one unplanned admission within the prior six months. A total of 400 patients had two or more admissions. Forty-five percent of readmitted patients had a diagnosis of gastrointestinal malignancy. Median overall survival for patients after a second unplanned admission was 76 days (95% CI 60 - 110), and median overall survival after a third unplanned admission was 50 days (95% CI 35 - 99). Median overall survival was 49 days (95% CI 39 - 67) for readmitted patients with a length of stay of at least seven days. Ninety-day survival was 45% (95% CI 39 – 51) among patients with two admissions and 34% (95% CI 26 – 43) among patients with three or more admissions. In multivariable models, longer length of stay was associated with decreased survival (HR 1.03, 95% CI 1.01-1.05). Age and sex were not associated with differences in survival, and overall survival was similar across all disease groups except head and neck, which was associated with improved survival (HR 0.42, 95% CI 0.21-0.85). Conclusions: Patients with solid tumors with multiple unplanned hospital admissions in less than six months represent a distinct population with exceptionally poor outcomes, regardless of the primary tumor site and patient demographics. This easily identifiable population may benefit from targeted interventions to improve the quality of end-of-life care.

Background: Patients with lymphoma frequently experience hospital readmissions. Yet, limited data exist describing hospital readmissions in the lymphoma population. In this study, we sought to identify additional patient-specific characteristics associated with unplanned readmissions in patients with lymphoma at our institution. Methods: We conducted a retrospective, single-center study of patients with lymphoma who were age >18 and discharged from medical oncology wards from January-December 2019 (index admission). We categorized patients as having high-risk medications per the Institute for Safe Medication Practices, potentially inappropriate medications (PIMs) for older patients (age 65+) per the American Geriatric Society Beers Criteria, and polypharmacy and major polypharmacy as 5 or more and 10 or more scheduled medications on the discharge medication list, respectively. We performed univariate logistic regression to assess the association of with having an unplanned readmission within 30 days of discharge from index admission. The following factors, selected for clinical relevance, were assessed: age; gender; race; marital status; Charlson comorbidity score; lymphoma diagnosis and related parameters (stage, LDH, prior treatment ECOG PS); index hospitalization reason, duration, discharge disposition and prior healthcare utilization; activities of daily living (ADL) status; Morse fall score; laboratory values at time of discharge; discharge medication list; 30-day readmission status and readmission reason if applicable. Results: We included 207 patients (mean age 63.9 years, 38.6% female, 83.1% white race, 56.8% partnered), 65 (31.4%) of whom experienced a 30-day unplanned readmission. Patients experiencing a 30-day unplanned readmission were more likely to have ECOG PS >2 (36.9% vs 14.2%, p<0.001), higher age-adjusted IPI score (score 0, 3.3% vs 7.8%; score 1, 23.3% vs 35.7%; score 2, 55.0% vs 47.8%; score > 3, 18.3% vs 8.7%; p=0.012), received CAR T-cell therapy (9.2% vs 2.1%, p=0.032), index length of stay >5 days (55.4% vs 33.1%, p=0.003), been discharged to a skilled nursing facility (12.3% vs 3.5%, p=0.023), albumin <3.5 g/dL (78.5% vs 52.1%, p<0.001), and sodium <135 mEq/L (18.5% vs 8.5%, p=0.041). Patients discharged home were less likely to have a 30-day unplanned readmission (56.9% vs 76.8%, p=0.004). Age, sex, marital status, Charlson comorbidity score, aggressive versus non-aggressive lymphoma diagnosis, prior lymphoma treatment, discharge home with services or to inpatient rehabilitation, Morse fall score, bowel and/or bladder continence, independence in feeding or bathing, neutropenia (ANC<1.5 k/mcL), and Hgb <10 g/dL were not significantly associated with increased likelihood for unplanned readmission. Among medication-related factors, we found that patients with major polypharmacy on the index admission discharge medication list had a higher likelihood for unplanned readmission (56.9% vs 37.3%, p=0.009). Patients with discharge medication lists with polypharmacy (90.8% vs 81.7%, 00, long-acting opiates (10.8% vs 4.2%, p=0.082), and/or anticoagulants (26.2% vs 15.5%, p=0.071) had a higher likelihood for unplanned readmissions, but these differences did not reach statistical significance. Presence of PIMs was not associated with readmission. Conclusions: In this relatively large cohort of patients with lymphoma, we identified several risk factors for unplanned hospital readmissions. We found associations among unplanned readmissions and impaired performance status, receipt of prior CAR T therapy, higher age-adjusted IPI score, discharge location (home, skilled nursing facility, etc), lower albumin and sodium levels, as well as major polypharmacy on the discharge medication list. Future directions include further efforts to identify lymphoma patients at high risk for hospital readmissions and developing readmission prevention strategies in those patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

The burden of cancer and oncologic treatment is reflected not only through morbidity and mortality, but also through impacts on patient quality of life (QoL). However, QoL has not been historically measured or addressed with the same rigorous methodology as traditional disease-related outcomes such as overall survival and progression, as these are driven by objective measurements and events. Prostate cancer (PCa) is one of the most prevalent non-cutaneous cancers in men around the world. Both the cancer and its treatment significantly impact patients’ physical, emotional, sexual, social, and overall QoL. Ensuring assessment and integration of QoL in research and clinical care enables improvement in treatment outcomes that matter most to patients while also facilitating alignment of healthcare priorities with reimbursements. Great strides toward this end have been made over the last decade, but significant room for improvement remains. To ensure high quality, reliable data collection, QoL assessment tools must be psychometrically validated, standardized, widely implemented across trials, and regularly assessed to allow internal and external validity, longitudinal comparative effectiveness research, and quality control. Additional consideration should be taken for instruments used to measure the aspects of QoL specific to minority, caregiver, and elderly populations. Open clinical questions include how providers should weight changes in different QoL subscales and how clinically meaningful difference thresholds should be defined. Review of ongoing clinical trials encouragingly reveals an increased focus on measuring and improving QoL for men with PCa which will inform the way we utilize QoL assessments. However, additional efforts herein described are needed to fully optimize these processes. In summary, this review will explain the rationale for QoL assessments in PCa populations, discuss requirements for effective implementation, describe considerations for vulnerable and under-evaluated populations, and summarize ongoing clinical trials assessing patient QoL.

Background: Patients with breast cancer generally receive most of their care in an outpatient setting, but unplanned hospitalizations may occur to help manage uncontrolled symptoms. We sought to investigate healthcare utilization and symptoms among patients with breast cancer experiencing an unplanned hospitalization. Methods: We enrolled patients with cancer and unplanned hospitalizations from 9/2014 to 2/2017. The current study focuses on the patients with breast cancer in this cohort. Following hospital admission, we assessed patient-reported symptoms using the Edmonton Symptom Assessment System (ESAS). We reviewed the electronic health record to obtain information about patient demographics, clinical characteristics, healthcare utilization, and reasons for hospital admission (elicited from primary and secondary diagnoses listed on the hospitalization discharge summary). We examined the associations among patients’ symptoms, healthcare utilization (i.e., hospital length of stay and 90-day readmissions), and survival using regression models. Results: We identified 101 patients with breast cancer (median age=60 years [range 22-86]. In this cohort, 74% had metastatic breast cancer. Primary/secondary reasons for hospitalization included fever/infection (34%), pain (18%), dyspnea (12%), gastrointestinal diagnoses (constipation, diarrhea, bowel obstruction, biliary obstruction, ascites, 10%), nausea/vomiting (7%), failure to thrive (6%), pleural effusion (5%), renal failure (4%), blood clot (3%), cardiac diagnoses (atrial fibrillation, cardiomyopathy, 3%), lightheadedness/hypotension (3%), neurologic diagnoses (altered mental status, seizure, subdural hematoma, 3%), fracture (2%), lower extremity swelling (2%), and other (i.e., rash, ptosis, SVC syndrome, fall, 1% each). Table 1 describes the baseline ESAS symptoms collected upon hospital admission. The mean length of hospital stay was 6.2 days and 90-day readmission rates were 28%. Patient disposition post hospitalization included discharge to home (76%), post-acute care facility (12%), hospice (5%), and death in the hospital (6%). We found that patients’ ESAS-physical symptoms were associated with longer hospital length of stay (B=0.08, p=0.029), greater risk of death or readmission within 90-days (OR=1.07, p<0.001), and worse overall survival (HR=1.04, p=0.001). Similarly, patients’ ESAS-total symptoms were associated with longer hospital length of stay (B=0.07, p=0.013), greater risk of death or readmission within 90-days (OR=1.05, p=0.001), and worse overall survival (HR=1.02, p=0.003). Conclusions: In this cohort of hospitalized patients with breast cancer, the majority had metastatic disease and presented with a high symptom burden. Unplanned admissions in these patients with breast cancer commonly occurred for fever/infection, pain, dyspnea, and gastrointestinal reasons. We identified novel associations among patients’ symptoms upon admission with their hospital length of stay, risk of readmissions/death, and overall survival. These findings highlight the need for timely outpatient interventions that address patient symptoms when seeking to enhance health care utilization and survival outcomes in this population. Table 1.Baseline symptom% of patients with moderate or severe symptomsMedian ESAS scoreTiredness*90%8 (Severe)Pain*78%7 (Severe)Well-being76%5 (Moderate)Drowsiness*71%6 (Moderate)Lack of appetite*68%5 (Moderate)Anxiety61%5 (Moderate)Depression52%4 (Moderate)Nausea*45%2 (Mild)Shortness of breath*45%2 (Mild)Constipation*44%0 (None)Total ESAS scoreMedian score 47 Total ESAS_physical score. . Median score 34*components included in ESAS_physical score Citation Format: Neelima Vidula, Emilia Kaslow-Zieve, Carolyn Qian, Isabel Neckermann, Eva Gaufberg, Charu Vyas, Richard Newcomb, Patrick C Johnson, Daniel Lage, Jennifer Shin, Ryan Nipp. Healthcare utilization and symptoms among hospitalized patients with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-12-04.

295 Background: Patients with advanced cancer often experience frequent and prolonged hospitalizations, and the transition from hospital to home represents a critical period for these individuals, as they prefer to maximize time at home and avoid readmissions. We sought to demonstrate the feasibility and acceptability of a Supportive Oncology Care at Home intervention to address the post-discharge needs of recently hospitalized patients with advanced cancer. Methods: We conducted a single-arm pilot trial at Massachusetts General Hospital (MGH). We enrolled English-speaking adults with advanced solid tumors experiencing their second or later unplanned hospitalization, who were being discharged home without hospice services and residing within a 50 mile radius of MGH. The three-week intervention consisted of: 1) hospital in the home care model for proactive symptom assessment and management, including clinician visits to assess patients, draw labs, administer intravenous medications and hydration, and ensure optimal symptom management; 2) remote monitoring of daily patient-reported symptoms, vital signs, and body weight; and 3) structured communication with the oncology team. The primary endpoint of the study was feasibility, defined as ≥60% of approached and eligible patients enrolling and ≥60% of participants completing daily symptom assessments. After intervention completion, patients rated the helpfulness and convenience of the intervention and symptom monitoring technology. Results: From 12/2021-6/2022, we enrolled 40 out of 66 approached patients (60.6% enrollment rate). Enrolled patients (median age = 58.5 years, 50% female, 75% white, 68% married, 50% gastrointestinal cancers) completed 93.8% of daily symptom assessments. 12 patients (30%) did not complete the intervention due to withdrawal (5), hospice transfer (4), or death (3). Among enrolled patients, 20.0% were enrolled in hospice and 15.4% died at 30 days after hospital discharge. In exit interviews, 100% and 75% rated the intervention and symptom monitoring as helpful, respectively. 83% of patients found the in-home monitoring technology convenient. Conclusions: We found that a three-week Supportive Oncology Care at Home intervention is a feasible approach to providing post-discharge care for high acuity, seriously ill hospitalized patients with advanced cancer. These patients also found the intervention highly acceptable. Future studies will test the efficacy of the intervention for reducing hospital readmissions, improving symptom management and quality of life, and increasing days spent at home near the end of life. Clinical trial information: NCT04637035.

33 Background: Patients with advanced cancer are frequently hospitalized and experience burdensome transitions of care after discharge. Interventions to address patients’ symptoms, support medication management, and ensure continuity of care after discharge are lacking. We sought to demonstrate the feasibility and acceptability of CONTINUUM (CONTINUity of care Under Management by video visits) for this population. Methods: We conducted a single-arm pilot trial (n = 50) of CONTINUUM at Massachusetts General Hospital (MGH). The intervention consisted of a video visit with an oncology nurse practitioner (NP) within 3 business days of hospital discharge to address symptoms, medication management, hospitalization-related issues, and care coordination. Prior to discharge, we enrolled English-speaking adults with advanced breast, gastrointestinal, genitourinary, or thoracic cancers experiencing an unplanned hospitalization who were receiving ongoing oncology care at MGH and being discharged home without hospice services. We defined the intervention as feasible if ≥70% of approached and eligible patients enrolled and if ≥70% of enrolled patients completed the intervention within 3 business days of discharge. At 2 weeks after discharge, patients rated the ease of use of the video technology and stated whether they would recommend the intervention. NPs completed post-intervention surveys to assess fidelity to the intervention protocol. Results: From 01/07/21 to 05/28/21, we enrolled 50 patients (75% of patients approached). Of the enrolled patients (median age = 65 years; 62% and 22% had advanced gastrointestinal or thoracic cancers, respectively), 78% of enrolled patients received the intervention within 3 business days of discharge. Patient rating of the ease of use of video technology was a mean of 7.6 out of 10, with 72% stating they “agreed” or “strongly agreed” that they would recommend the intervention. NP post-intervention surveys revealed that visits primarily focused on symptom management (56%), followed by addressing post-hospital care issues (21%). Of the 30 patients with 30-day follow-up, 43% were readmitted within 30 days of discharge, and 17% died within 30 days of discharge. Conclusions: We found that CONTINUUM, which consists of an NP-delivered video visit soon after hospital discharge addressing patients’ symptoms, medications, and care coordination, represents a feasible and acceptable approach to provide post-discharge care for hospitalized patients with advanced cancer. Future studies will test the efficacy of the intervention for reducing hospital readmissions. Clinical trial information: NCT04640714.