Pritchett, Joshua C.

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.

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 Background: Despite the promise of targeted agents in hematology, the high price of cancer therapies is a rapidly evolving problem. Until now, the increase in price of targeted anti-cancer treatments used in common hematological malignancies has not been evaluated. Here, we report patterns in price changes from 2015-2019 for multiple in-class anticancer medications for common hematologic malignancies. Methods: We utilized the publicly available Medicare Part D provider utilization and payment database from 2015 to 2019. We extracted drug prices (using generic names) for commonly used targeted anticancer agents for acute myeloid leukemia, chronic myeloid leukemia, chronic lymphocytic leukemia, B-cell lymphomas, and multiple myeloma. The primary outcome was the correlation of average change in Medicare spending per dosage unit among the multiple brand-name medications within each class available. We additionally calculated compound annual growth rates (CAGRs) [i.e. mean annual growth rates over a specified period of time] for medication costs within each class, and compared it with the consumer price index (CPI) (a measure of the average change over time in the prices of consumer items) and inflation rate. Agents without in-class competitor were excluded. CPI and inflation rates came from U.S. Bureau of Labor Statistics. Results: The study included 6 BCR-ABL inhibitors (1 generic), 2 BTK inhibitors, 2 IDH inhibitors, 2 FLT3 inhibitors, 3 IMIDs, 3 PI, 2 PI3K inhibitors, and 5 anti-CD20 monoclonal antibodies. The median (range) Pearson correlation coefficient values for drugs within each class were -0.155 (-0.984-0.992) for BCR-ABLi, -0.362 for BTKi, 0.234 (0.215-0.999) for IMIDs, 0.899 (-0.034-0.988) for PIs, and 0.954 (0.847-0.999) for anti-CD20 antibodies. The median correlation coefficient for BCR-ABLi was 0.751 if generic imatinib was excluded. The correlation coefficient between 2 nd and 3 rd generation IMIDs was 0.999. Non-generic BCR-ABLi and anti-CD20 antibodies showed strong linear association in price increase between two drugs within the same class. Due to drug novelty, coefficient could not be calculated for therapies with 2 or fewer data points (midostaurin, gilteritinib, enasidenib, ivosidenib, idelalisib, duvelisib). There was no significant correlation between expenditure for BTKi, PIs, and IMIDs. The median CAGRs in costs over this 5-year period were: were 6.29% for BCR-ABLi, 18.36% for BTKi, 2.69% for IDHi, 4.23% for FLT3i, 10.63% for IMIDs, 5.11% for PIs, 5.79% for PI3Ki, and 5.85% for anti-CD20s. The median CAGR in costs for modern precision-driven cancer therapeutic classes outpaced CPI (2.26%/year), and the average inflation rate (1.90%/year). Conclusions: Increase in cost within the same class should be weighed against incremental clinical benefit for the patients. For non-generic BCR-ABLi and anti-CD20 antibodies, despite there being several agents, the rise in drug expenditures correlated closely, calling into question the true value of within-class competition. There is an urgent need for drug pricing reform given the average expenditure of Medicare part D, and ultimately out-of-pocket costs for our patients with cancer continues to trend upwards. Increased advocacy efforts are needed to ensure precision therapeutics remains an attainable and sustainable goal. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

7 Background: Despite the promise of precision oncology, the cost-effectiveness of targeted treatments is debated. Until now, the increase in price of oral targeted anti-cancer treatments used in common malignancies has not been evaluated. Here, we report patterns in price changes from 2015-2019 for multiple oral anti-cancer medications for common solid tumor malignancies. Methods: We utilized the publicly available Medicare Part D provider utilization and payment database from 2015 to 2019. We extracted drug prices (using generic names) for commonly used targeted oral anticancer agents for lung, breast, and prostate cancer. The primary outcome was the correlation of average change in Medicare spending per dosage unit among the multiple brand-name medications within each class available. We additionally calculated compound annual growth rates (CAGRs) [i.e. mean annual growth rates over a specified period of time] for medication costs within each class, and compared it with the consumer price index (a measure of the average change over time in the prices of consumer items). Results: The study included 6 EGFR inhibitors (1 generic), 5 ALK inhibitors, 2 BRAF inhibitors, 3 hormonal agents (1 generic), 3 CDK4/6 inhibitors, 2 PARP inhibitors, and 7 anti-androgen agents (2 generic). The median (range) Pearson correlation coefficient values for drugs within each 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 (-0.522-0.962) for anti-androgens. Except for anti-androgens, all other drug classes showed strong linear association in price increase between two drugs within the same-class. A coefficient could not be calculated for therapies with 2 or fewer data points ( i.e., generic erlotinib, dacomitinib, generic abiraterone, apalutamide, and darolutamide). There was no significant correlation between expenditure for anti-estrogen agents. The median (range) CAGRs in costs over this 5-year period were: were 4.56% for EGFRi, 6.40% for ALKi, 2.58% for BRAFi, 5.48% for hormonal agents, 5.21% for CDK4/6i, 27.29% for PARPi, and 34.8% for anti-androgen agents. Conclusions: The median CAGR in costs for modern oral precision driven cancer therapeutic classes mostly outpaced CPI (2.26%/year), and the average inflation rate (1.90%/year). Increase in cost within the same class should be weighed against incremental clinical benefit for the patients. For most classes despite there being multiple agents, the rise in drug expenditures correlated closely, calling into question the true value of within class competition. There is an urgent need for drug pricing reform given the average expenditure of Medicare part D, and ultimately out of pocket costs for our patients with cancer continues to trend upwards. Increased advocacy efforts are needed to ensure precision therapeutics remains an attainable and sustainable goal.

Background CD8+ T-lymphocyte subsets defined by killer lectin-like receptor G1 (KLRG1) and CD127 expression have been reported to have an important role in infection, but their role in the setting of lymphoid malignancies, specifically follicular lymphoma (FL), has not been studied. Methods To characterize the phenotype of KLRG1/CD127-defined CD8+ subsets, surface and intracellular markers were measured by flow cytometry and Cytometry by time of flight (CyTOF), and the transcriptional profile of these cells was determined by CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing). The functional capacity of each subset was determined, as was their impact on overall survival (OS) and event-free survival (EFS) of patients with FL. Results We found that intratumoral CD8+ cells in FL are skewed toward effector cell subsets, particularly KLRG+CD127- and KLRG1-CD127- cells over memory cell subsets, such as KLRG1-CD127+ and KLRG1+CD127+ cells. While effector subsets exhibited increased capacity to produce cytokines/granules when compared with memory subsets, their proliferative capacity and viability were found to be substantially inferior. Clinically, a skewed distribution of intratumoral CD8+ T cells favoring effector subtypes was associated with an inferior outcome in patients with FL. Increased numbers of CD127+KLRG1- and CD127+KLRG1+ were significantly associated with a favorable OS and EFS, while CD127-KLRG1- correlated with a poor EFS and OS in patients with FL. Furthermore, we demonstrated that interleukin (IL)-15 promotes CD127-KLRG1+ cell development in the presence of dendritic cells via a phosphoinositide 3-kinase (PI3K)-dependent mechanism, and treatment of CD8+ T cells with a PI3K inhibitor downregulated the transcription factors responsible for CD127-KLRG1+ differentiation. Conclusions Taken together, these results reveal not only a biological and prognostic role for KLRG1/CD127-defined CD8+ subsets in FL but also a potential role for PI3K inhibitors to manipulate the differentiation of CD8+ T cells, thereby promoting a more effective antitumor immune response.

PURPOSE: The benefit of routine pre-emptive screening for severe acute respiratory syndrome coronavirus 2 infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of patients with cancer who were diagnosed with COVID-19 by routine screening (RS) in comparison with those diagnosed on the basis of clinical suspicion or exposure history (nonroutine screening [NRS]). METHODS: A multisite prospective observational study was conducted at three major and five satellite campuses of the Mayo Clinic Cancer Center between March 18 and July 31, 2020. The primary outcome was COVID-19–related hospital admission. Secondary outcomes included intensive care unit admissions and all-cause mortality. RESULTS: Five thousand four hundred fifty-two patients underwent RS in the outpatient setting only, and 44 (0.81%) were diagnosed with COVID-19. RS detected 19 additional patients from the scheduled inpatient admissions for surgical or interventional procedures or inpatient chemotherapy. One hundred sixty-one patients were diagnosed with COVID-19 on the basis of NRS. COVID-19–related hospitalization rate (17.5% v 26.7%; P = .14), intensive care unit admission (1.6% v 5.6%; P = .19), and mortality (4.8% v 3.7%; P = .72) were not significantly different between the RS and NRS groups. In the multivariable analysis, age ≥ 60 years (odds ratio, 4.4; P = .023) and an absolute lymphocyte count ≤ 1.4 × 109/L (odds ratio, 9.2; P = .002) were independent predictors of COVID-19–related hospital admission. CONCLUSION: The COVID-19 positivity rate was low on the basis of RS. Comparing the hospital admission and mortality outcomes with the NRS cohort, there were no significant differences. The value of routine pre-emptive screening of asymptomatic patients with cancer for COVID-19 remains low.

PURPOSE: The goal of this study was to assess the impact of an interdisciplinary remote patient monitoring (RPM) program on clinical outcomes and acute care utilization in cancer patients with COVID-19. METHODS: This is a cross-sectional analysis following a prospective observational study performed at Mayo Clinic Cancer Center. Adult patients receiving cancer-directed therapy or in recent remission on active surveillance with polymerase chain reaction–confirmed SARS-CoV-2 infection between March 18 and July 31, 2020, were included. RPM was composed of in-home technology to assess symptoms and physiologic data with centralized nursing and physician oversight. RESULTS: During the study timeframe, 224 patients with cancer were diagnosed with COVID-19. Of the 187 patients (83%) initially managed in the outpatient setting, those who did not receive RPM were significantly more likely to experience hospitalization than those receiving RPM. Following balancing of patient characteristics by inverse propensity score weighting, rates of hospitalization for RPM and non-RPM patients were 2.8% and 13%, respectively, implying that the use of RPM was associated with a 78% relative risk reduction in hospital admission rate (95% CI, 54 to 102; P = .002). Furthermore, when hospitalized, these patients experienced a shorter length of stay and fewer prolonged hospitalizations, intensive care unit admissions, and deaths, although these trends did not reach statistical significance. CONCLUSION: The use of RPM and a centralized virtual care team was associated with a reduction in hospital admission rate and lower overall acute care resource utilization among cancer patients with COVID-19.

1503 Background: Patients with cancer and COVID-19 are at risk for poor clinical outcomes. An established multi-site remote patient monitoring (RPM) service was rapidly adapted to support a novel, interdisciplinary COVID-19 program for outpatient management of patients at high-risk for severe illness. The goal of this study was to assess the impact of the RPM program on clinical outcomes and acute care utilization in cancer patients diagnosed with COVID-19. Methods: This is a cross-sectional analysis following a multi-site prospective observational study performed at Mayo Clinic Cancer Center (MCCC). All adult patients with active cancer – defined as currently receiving cancer-directed therapy or in recent remission on active surveillance – and PCR-confirmed SARS-CoV-2 infection between March 18 and July 31, 2020 were included. RPM was comprised of in-home technology to assess symptoms and physiologic data with centralized nurse and physician oversight. Results: During the study timeframe 224 cancer patients were diagnosed with COVID-19 at MCCC. Initial management included urgent hospitalization (within 48 hours of diagnosis) in 34 patients (15%). Of the remaining 190 patients (85%) initially managed in the outpatient setting, those who did not receive RPM were significantly more likely to experience hospitalization than those receiving RPM (OR 3.6, 95% CI 1.036 to 12.01, P = 0.044). Following balancing of patient characteristics by inverse propensity weighting, rates of hospital admission for RPM and non-RPM patients were 3.1% and 11% respectively, implying that RPM was associated with an 8% reduction in hospital admission rate (-0.077; 95% CI: -0.315 to -0.019, P = 0.009). Use of RPM was also associated with lower rates of prolonged hospitalization, ICU admission, and mortality, though these trends did not reach statistical significance. Conclusions: In the midst of a global pandemic associated with inpatient bed, ventilator, and PPE shortages, the RPM program provided an effective strategy for outpatient clinical management and was associated with decreased rates of hospitalization, ICU admission, and mortality in cancer patients with COVID-19. This care model enabled simultaneous opportunity to mitigate the increased risks of exposure, transmission, and resource utilization associated with conventional care.