Citations

26 Background: We previously demonstrated that utilization of a Remote Patient Monitoring (RPM) program – characterized by the use of in-home technology for symptom and vital signs assessments with a centralized care team responding to alerts – is associated with a significant reduction in 30-day hospitalization rate among cancer patients with COVID-19. We have subsequently performed a 90-day comparative cost-of-care analysis in this prospectively enrolled, validated cohort of 71 patients who received RPM and 116 patients who received usual care without RPM. Methods: Primary outcomes included 90-day all-cause costs (categorized as hospital and outpatient costs) following the index date (date of COVID-19 diagnosis). Differences in patient characteristics and baseline costs (incurred 90 days prior to index date) were determined using Standardized Differences and controlled for using Inverse Probability Weighting (IPW). IPW balancing was based on baseline covariates known to be associated with poorer COVID-19 outcomes, as previously described. Association of costs with RPM was examined by generalized linear modeling while adjusting for relevant variables. Outcomes are reported as the average treatment effect on the treated (ATET). Results: Differences in patient characteristics and baseline costs were well-balanced following IPW modeling. The index ATET was found to be comparable among patients receiving RPM and usual care on the date of COVID-19 diagnosis -$89.75 (95% CI: -$144.33 to $323.84; p = 0.452). However, patients receiving RPM experienced a 90-day ATET of -$6,994 (95% CI: -$14,635 to $646; p = 0.073) when compared with patients receiving usual care. Conclusions: There was a trend towards decreased 90-day all-cause costs for cancer patients with COVID-19 who utilized the RPM program as compared with usual care. Larger studies are needed to understand the true cost (and cost savings) associated with this innovative model of care delivery which can be leveraged for cancer care beyond COVID-19.

PURPOSE: Financial hardship (FH) in cancer care is a growing challenge for patients, their caregivers, and health care providers with impact on morbidity and mortality. In this study, we report on a standardized approach to describe the prevalence and predictors for FH as part of routine clinical workflow. We also report on the association of FH with survival in our cancer patient population. METHODS: This study includes patients who completed a FH screen at least once between 2018 and 2020. Demographics, disease state, and mortality data were extracted from the medical records. Multivariable logistic regression models were used to examine association of sociodemographic and disease variables with FH. By using propensity score weighting to account for differences in demographic and clinical factors between patients with and without FH, we then fit Cox proportional hazards models to examine the relationship between FH and survival. RESULTS: The study cohort included 31,154 patients. FH was reported by 14% (n = 4,250) of the patients. A significantly higher likelihood of having FH ( P < .001 for all) was reported by racial/ethnic minority patients; those who were unemployed/disabled, single, or divorced; patients from disadvantaged neighborhoods; and those who were self-pay or had government insurance. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Patients who endorsed FH had a lower survival (hazard ratio for mortality 1.46). CONCLUSION: Our study identified key groups more likely to report FH in a relatively affluent population at a large cancer center and showed an adverse association between FH and survival. Further research is needed to develop clinical care pathways for patients at high risk for worse financial and clinical outcomes.

Abstract Introduction Patients with hematologic malignancies (HM) who are eligible for allogeneic hematopoietic cell transplant (allo-HCT) often lack an HLA-matched related donor (MRD) and rely on unrelated donors for a matched or mismatched unrelated donor (MUD or MMUD) or on umbilical cord blood (UCB). It is well known that racial minorities are underrepresented in donor registries. Objective Omidubicel, an advanced cell therapy for allo-HCT, demonstrated superior hematopoietic recovery and clinical outcomes compared with standard UCB (NCT02730299). We hypothesized the impact of omidubicel access on racial and ethnic health disparities in a projection model. Methods A model was developed to project allo-HCT access and clinical outcomes in a hypothetical population of 10,000 allo-HCT-eligible US patients with HM lacking an HLA-MRD. Outcomes associated with omidubicel, MUD, MMUD, haploidentical or UCB HCT, or no transplant were assessed by race/ethnic group. Model inputs, including clinical outcomes for each HCT type, were drawn from clinical trials, public CIBMTR and US Department of Health and Human Services data, and published studies. Increasing omidubicel use was modeled, with proportional reductions in other allo-HCT types or no transplant. Results In a modeled population of 10,000 patients, 5,956 (60%) received allo-HCT utilizing current donor sources (MUD, MMUD, haploidentical, UCB) with no omidubicel (status quo). While 80% of white patients underwent allo-HCT, only 40% of Hispanic, 32% of Asian, and 22% of Black patients underwent allo-HCT. Mean time from selecting graft to HCT was 11.5 weeks. Including those not transplanted, 1-year OS was 62% overall, ranging from 56% (Black) to 65% (White). Modeled increases in omidubicel use in eligible patients were associated with higher proportions of patients undergoing allo-HCT, decreased time to HCT, and increased 1-year OS. Improvements were greatest among racial minorities. Assuming 20% omidubicel use, the proportion of patients receiving allo-HCT increased by 71% in Black, 43% in Asian, 30% in Hispanic, and 5% in White patients. Modeled time to allo-HCT improved as well. Discussion Access to omidubicel is projected to decrease time to allo-HCT, improve outcomes overall, with greatest improvements among racial and ethnic groups underserved by the status quo, thus helping to reduce racial disparities and improving health equity in allo-HCT.

Abstract Background: Medical financial hardship, encompassing material, behavioral, and psychologic domains, is becoming an increasingly common consequence of illness in cancer patients. Identifying at-risk patients is the first step to develop proactive approaches to mitigate this problem. To try and address this need, Mayo Clinic Breast Disease Registry (MCBDR) is prospectively collecting data about financial concerns in addition to the usual sociodemographic and clinical information. Methods: We used data from Mayo Clinic Breast Disease Registry, a prospective cohort of consenting patients seen at Mayo Clinic Rochester within one year of initial breast cancer diagnosis. Participants completed baseline and annual follow-up surveys rating their financial concerns on a linear analogue scale from 0 (“none”) to 10 (“constant concerns”). We compared patient-reported financial concern at baseline to that on each patient’s most recent survey, with worsening concerns defined as a 1+-point increase. Logistic regression evaluated for predictors of worsening financial concerns. Results: 1,957 participants responded to financial concern questions on a baseline and at least one follow-up survey between 2015 and 2020. Mean age was 58.5 years (SD 12.5), and mean time between diagnosis and the most recent follow-up was 25.6 months (SD 16.2). 357 (18.2%) reported worsening financial concerns. Only lower baseline financial status was associated with a greater likelihood of worsening financial concerns (see Table). Conclusions: More than one in seven breast cancer survivors develop worsening financial concerns within 5-years of diagnosis, and those with less financial security at baseline appear to be most vulnerable. Funding: Breast Cancer Research Foundation (CLL) and NR015259 (KJR). Patient and tumor characteristics, compared by whether financial status worsened over time Full Cohort (n=1957) Worsening, ≥ 1-point change (n=357) Stable/Improved (n=1600) p value Full Cohort (n=1957) Worsening, ≥ 1-point change (n=357) Stable/Improved (n=1600) p value Age at diagnosis II or III 502 (25.7%) 98 (27.5%) 404 (25.3%) 0.239 ≤ 50 546 (27.9%) 105 (29.4%) 441 (27.6%) IV 67 (3.4%) 17 (4.8%) 50 (3.1%) 0.086 51-64 757 (38.7%) 136 (38.1%) 621 (38.8%) 0.562 Unknown 351 (17.9%) 65 (18.2%) 286 (17.9%) 0.536 ≥65 654 (33.4%) 116 (32.5%) 538 (33.6%) 0.506 ER and/or PR positive Race No/Unknown 482 (24.6%) 92 (25.8%) 390 (24.4%) White 1863 (95.2%) 337 (94.4%) 1526 (95.4%) Yes 1475 (75.4%) 265 (74.2%) 1210 (75.6%) 0.580 Non-white 24 (1.2%) 5 (1.4%) 19 (1.2%) 0.729 Her2 positive Other/Unknown/Choose not to respond 70 (3.6%) 15 (4.2%) 55 (3.4%) 0.478 No/Unknown 1746 (89.2%) 314 (88.0%) 1432 (89.5%) Educational status Yes 176 (9.0%) 37 (10.4%) 139 (8.7%) 0.321 Less than bachelor’s degree 880 (45.0%) 168 (47.1%) 712 (44.5%) Borderline 35 (1.8%) 6 (1.7%) 29 (1.8%) 0.898 Bachelor's degree or higher 1065 (54.4%) 187 (52.4%) 878 (54.9%) 0.384 Radiation Unknown 12 (0.6%) 2 (0.6%) 10 (0.6%) 0.832 No/Unknown 781 (39.9%) 140 (39.2%) 641 (40.1%) Financial status near time of diagnosis Yes 1176 (60.1%) 217 (60.8%) 959 (59.9%) 0.768 Pay bills, money for special things 1412 (72.2%) 244 (68.3%) 1168 (73.0%) Chemotherapy/targeted therapy Pay bills, no money for special things 367 (18.8%) 80 (22.4%) 287 (17.9%) 0.046 No/Unknown 1264 (64.6%) 221 (61.9%) 1043 (65.2%) Pay bills by making cuts 102 (5.2%) 19 (5.3%) 83 (5.2%) 0.729 Yes 693 (35.4%) 136 (38.1%) 557 (34.8%) 0.241 Unable to pay bills 56 (2.9%) 10 (2.8%) 46 (2.9%) 0.911 Hormone/endocrine therapy Unknown 20 (1.0%) 4 (1.1%) 16 (1.0%) 0.750 No/Unknown 710 (36.3%) 141 (39.5%) 569 (35.6%) Employment status at time of diagnosis Yes 1247 (63.7%) 216 (60.5%) 1031 (64.4%) 0.163 Employed full-time 462 (23.6%) 83 (23.2%) 379 (23.7%) Surgery type Employed part-time/unemployed/retired 525 (26.8%) 92 (25.8%) 433 (27.1%) 0.856 Lumpectomy 846 (43.2%) 145 (40.6%) 701 (43.8%) Not available 970 (49.6%) 182 (51.0%) 788 (49.3%) 0.716 Mastectomy 903 (46.1%) 165 (46.2%) 738 (46.1%) 0.535 Stage at time of diagnosis None/Unknown 208 (10.6%) 47 (13.2%) 161 (10.1%) 0.069 0 or I 1037 (53.0%) 177 (49.6%) 860 (53.8%) Citation Format: Michael H. Storandt, Urshila Durani, Daniela Stan, Nicole Larson, Charles Loprinzi, Fergus Couch, Janet E. Olson, Nandita Khera, Kathryn J. Ruddy. Financial hardship in breast cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1012.

6552 Background: Significant amounts of expensive oncology drugs are discarded resulting in waste and financial consequences for patients. Beginning in 2023, the Infrastructure Investment and Jobs Act (IIJA) will require drug manufacturers to refund Medicare for any single-use drugs where greater than 10% of the drug is wasted. We explored potential IIJA-associated savings through assessment of patterns in spending for discarded oncology agents between 2017-2020. Methods: We utilized the Medicare Part B Discarded Drug Units database from 2017-2020. Using J codes, we extracted spending and reimbursement data for discarded medications for antineoplastic and classical hematology therapies. The primary outcome was identification of therapies with high percentage of waste and the economic impact of retroactive application of the IIJA for discarded therapies. Results: Medicare Part B utilization data was extracted for a median 77 (64-152) oncologic therapies per year with median reimbursement for discarded treatments of $590 M ($566-616). From 2017-2020, bortezomib, romiplostim, and nab-paclitaxel were consistently among the top 5 therapies by value of wasted product. Pembrolizumab waste by value declined significantly after 2017 following transition to fixed dosing. In 2020, the top 5 therapies by value of wasted product were bortezomib, nab-paclitaxel, trastuzumab, romiplostim, and cabazitaxel with a value of $278 M. In 2020, the agents with the highest percentage of wasted product were bortezomib (27%), cabazitaxel (28%), decitabine (23%), topotecan (23%), and azacitidine (22%) with a collective discarded value of $160 M. Notably, these agents have weight-based dosing and single-use vials. Based upon the average number of drug claims per recipient and volume of product discarded, eliminating drug waste would allow an additional 6564 patients to receive treatment with discarded bortezomib. The number of additionally treated patients for the other top 5 agents: cabazitaxel (1216), decitabine (1509), topotecan (291), and azacitidine (2682). Retroactive application of IIJA policy would have impacted a median 20 (12-26) oncology agents resulting in median annual cost savings of $153 M (142-157) and the median annual spending on wasted oncology therapies would decline to $440 M (410-466). Conclusions: The IIJA would have yielded a median annual savings of $153 M in Medicare spending if applied retroactively. Given a 10% waste cutoff, a limited number of agents would be targeted by this legislation. In our study, we observe that drugs associated with weight-based dosing and single-use drug vials account for most drug waste. Strategies to minimize discarded units (through storage of unused product, approval of multi-dose vial formulations, or fixed-dose therapies) could yield substantial savings while enabling health equity in collaboration with communities with difficult access to these drugs.

1512 Background: In response to the COVID-19 pandemic, many cancer practices adopted telehealth, including telephone and video appointments. Following a period of initial expansion that began in March 2020, sustained telehealth integration has emerged across the Mayo Clinic Cancer Practice (MCCP) in 2021. The primary objective of this study was to identify factors associated with utilization of telehealth appointments. Methods: A cross-sectional, multi-site, retrospective analysis was conducted across MCCP – a multisite, multiregional cancer practice with tertiary referral campuses in Minnesota, Florida, and Arizona, as well as rural, community-based hospitals and clinics throughout the Upper Midwest. Multivariable models were used to examine the association of patient- and provider-level variables with telehealth utilization. Results: Outpatient appointments conducted in July – August 2019 (n = 32,932) were compared with those from 2020 (n = 33,662) and 2021 (n = 35,486). The rate of telehealth appointment utilization increased from <0.01% in 2019 to 11.0% in 2020 and 14.0% in 2021. The strongest provider-level predictor of telehealth utilization was female physician provider type (OR 1.06, 95% CI 1.01 to 1.11; P = 0.0297), a trend consistently observed across career stages, practice locations and settings in 2020 and 2021. Additionally, while the rate of telehealth utilization was not significantly different at referral and community-based campuses in 2020, providers at referral campuses were significantly more likely to utilize telehealth than community-based campuses in 2021 (OR 1.1, 95% CI 1.01 to 1.12; P = 0.0289). Regarding patient-level factors, rural residence (defined by Rural-Urban Commuting Area codes), which accounted for 44.2% of the patient population, was significantly associated with lower telehealth utilization as compared to patients with urban residences, particularly for video appointments (OR 1.04, 95% CI 1.02 to 1.07; P < 0.0001). Notably, the disparity in telehealth utilization between rural and urban populations was found to be less pronounced in 2021 as compared to 2020. Conclusions: Multivariable analysis across a multi-site, multi-regional cancer practice identified several factors associated with increased telehealth utilization. These included female physician provider type, referral-based campuses, and patients residing in urban settings. A detailed understanding of the factors that influence telehealth utilization – a method of care delivery which represents a “new normal” across many cancer practices – will be essential to enable continued equitable access to high-quality, high-impact, patient-centered cancer care.

PURPOSE: Precision oncology promises improved outcomes but the cost-effectiveness and accessibility of targeted therapies is debatable. We report price change patterns from 2015 to 2019 for several oral anticancer medications for common solid tumor malignancies. METHODS: We collected provider utilization and payment data from the public Medicare Part D database and extracted drug price information for commonly prescribed targeted oral anticancer agents for lung, breast, and prostate cancer. We then calculated median Pearson correlation coefficient values for various drugs (containing more than two data points) within each therapeutic class. We also calculated compound annual growth rates (CAGRs) for medication costs within each class and compared them with the consumer price index (CPI). RESULTS: Our study included six epidermal growth factor receptor inhibitors (EGFRi; one generic), five anaplastic lymphoma kinase inhibitors (ALKi), two B-Raf inhibitors (BRAFi), three hormonal agents (one generic), three cyclin-dependent kinases 4 and 6 inhibitors (CDK4/6i), two poly-ADP-ribose inhibitors (PARPi), and seven antiandrogen agents (two generic). The median (range) Pearson correlation coefficient values for cost of drugs within each therapeutic class were 0.967 (0.915-0.978) for EGFRi, 0.981 (0.966-0.989) for ALKi, 0.996 for BRAFi, 0.994 (0.992-0.999) for CDK4/6i, 0.855 for PARPi, and 0.442 (–0.522 to 0.962) for antiandrogens. Therapies with two or fewer data points (generic erlotinib, dacomitinib, abiraterone, apalutamide, and darolutamide) were excluded. The median CAGRs in costs over the 5-year period were 4.56% (EGFRi), 6.40% (ALKi), 2.58% (BRAFi), 5.48% (hormonal agents), 5.21% (CDK4/6i), 27.29% (PARPi), and 34.8% (antiandrogens). The CPI over 5 years was 2.26%/year, and the average inflation rate was 1.90%/year. CONCLUSION: The median CAGR in costs for modern oral precision-driven cancer therapeutic classes mostly outpaced CPI and the average inflation. Increase in cost within the same class should be weighed against incremental clinical benefit for the patients to ensure that rising costs do not limit access to targeted therapies.

Abstract With improvement in survival after hematopoietic cell transplantation (HCT), it has become important to focus on survivors' psychosocial issues in order to provide patient-centered care across the transplant continuum. The goals of this article are to describe updates in the literature on certain psychosocial domains (emotional/mental health and social/financial) in HCT survivors, offer a brief overview of the status of the screening and management of these complications, and identify opportunities for future practice and research. An evidence-based approach to psychosocial care can be broken down as primary (promoting health, raising awareness, and addressing risk factors), secondary (screening and directing early pharmacological and nonpharmacological interventions), and tertiary (rehabilitating, limiting disability, and improving quality of life) prevention. Implementing such an approach requires close coordination between multiple stakeholders, including transplant center staff, referring hematologist/oncologists, and other subspecialists in areas such as palliative medicine or psychiatry. Innovative models of care that leverage technology can bring these stakeholders together to fulfill unmet needs in this area by addressing barriers in the delivery of psychosocial care.