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Background The Woven EndoBridge (WEB) device is a novel intrasaccular flow disruptor tailored for bifurcation aneurysms. We aim to describe the degree of aneurysm occlusion at the latest follow-up, and the rate of complications of aneurysms treated with the WEB device stratified according to rupture status. Methods Our data were taken from the WorldWideWeb Consortium, an international multicenter cohort including patients treated with the WEB device. Aneurysms were classified into two groups: ruptured and unruptured. We compared clinical and radiologic outcomes of both groups. Propensity score matching (PSM) was done to match according to age, gender, bifurcation, location, prior treatment, neck, height, dome width, daughter sac, incorporated branch, pretreatment antiplatelets, and last imaging follow-up. Results The study included 676 patients with 691 intracranial aneurysms (529 unruptured and 162 ruptured) treated with the WEB device. The PSM analysis had 55 pairs. In both the unmatched (85.8% vs 84.3%, p=0.692) and matched (94.4% vs 83.3%, p=0.066) cohorts there was no significant difference in the adequate occlusion rate at the last follow-up. Likewise, there were no significant differences in both ischemic and hemorrhagic complications between the two groups. There was no documented aneurysm rebleeding after WEB device implantation. Conclusion There was no significant difference in both the radiologic outcomes and complications between unruptured and ruptured aneurysms. Our findings support the feasibility of treatment of ruptured aneurysms with the WEB device.

e19533 Background: Pneumocystis pneumonia (PJP) is a catastrophic infection seen in the context of low CD4 counts. Brentuximab vedotin (BV) is a drug antibody conjugate targeting CD30 and is used to treat patients with Hodgkin’s lymphoma (HL) and T-cell lymphoma (TCL). PJP prophylaxis is not currently recommended for patients receiving BV-based treatment despite co-expression of CD30 on CD4 cells. The frequency of PJP following BV remains poorly defined. Methods: We evaluated patients who received BV between January 1, 2011 and October 31, 2021 at Mayo Clinic for the development of PJP. Patient demographics and clinical characteristics including underlying disease, chemotherapy regimen, absolute lymphocyte count (ALC), and steroid exposure were collected. Patients who developed PJP more than 3 months after their last BV exposure were excluded. Results: Of 402 BV recipients identified, 63 received PJP prophylaxis and were omitted. Fourteen of the 339 (4.1%) not on prophylaxis developed PJP following BV. Those infected had a median age of 61 (22-87), 71% were male. The most common diagnoses were HL, TCL, and primary mediastinal B-cell lymphoma at rates of 57%, 21%, and 14% respectively. Therapy regimens included BV monotherapy, BV-CHP, and BV-AVD at rates of 43%, 21%, and 14% respectively. BV represented median 2nd line of therapy (1-10) and patients received median of 3 doses (1-10) prior to PJP diagnosis. Patients with PJP had median ALC of 620 (370-3500). 71.4% (10/14) had an ALC less than 750 and among those with ALC greater than 1000, 75% (3/4) had underlying diagnosis of HL. Three patients had CD4 count measured at time of PJP diagnosis with median value of 157 (5-175). 57.1% (8/14) had no steroid exposure beyond the treatment regimen. 14.3% (2/14) were on chronic doses of 5mg prednisone for autoimmune conditions. Short bursts of steroids (prednisone 40 mg) prior to PJP were seen in 21.4% (3/14) with median exposure of 8 days (7-10). One patient had prolonged steroid exposure but was weaned off 17 days prior to PJP diagnosis. 71.4% were older than 50 years at time of PJP. Conclusions: We observed rates of PJP above the commonly accepted threshold of 3.5% for recommending prophylaxis. Among patients with an ALC greater than 1000, 75% had HL raising the question of a qualitative defect in immunity. Close ALC monitoring is recommended for patients receiving BV with a low threshold to institute PJP prophylaxis, especially amongst those older than 50 or with a diagnosis of HL.[Table: see text]

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.

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 Brandner, CF, Harty, PS, Luedke, JA, Erickson, JL, and Jagim, AR. Sport differences in fat-free mass index among a diverse sample of NCAA Division III collegiate athletes. J Strength Cond Res 36(8): 2212–2217, 2022—Fat-free mass index (FFMI) is becoming a popular metric to determine an athlete's potential for future fat-free mass accrual or to identify athletes who may be at risk for low fat-free mass (FFM). The aim of the current study was to examine sport-specific differences in FFMI among a cohort of collegiate athletes. NCAA Division III male ( n = 98; age: 20.1 ± 1.6 years, height: 1.82 ± 0.06 m, body mass: 92.7 ± 17.5 kg, %BF: 15.6 ± 8.8%) and female ( n = 92; age: 19.45 ± 1.1 years, height: 1.68 ± 0.06 m, body mass: 65.16 ± 11.04 kg, %BF: 22.71 ± 5.9%) athletes completed a body composition assessment using air displacement plethysmography. Fat-free mass index was calculated by dividing FFM by height squared. The mean ± SD FFMI was significantly higher ( p < 0.05) for males (23.37 ± 2.41 kg·m −2 ) compared with females (17.54 ± 1.8 kg·m −2 ). There was a significant main effect for sport category. Post hoc analysis indicated that throwers had a higher ( p < 0.001) FFMI (mean difference, 95% confidence interval) compared with sprinters and soccer athletes (4.17, 2.03–6.32 kg·m −2 ), endurance and weight-sensitive athletes (4.91, 2.67–7.14 kg·m −2 ), and court sport athletes (4.39, 1.97–6.81 kg·m −2 ), respectively, among female athletes. Post hoc analysis indicated that football players had a higher ( p < 0.01) FFMI than distance runners (3.89, 2.15, 5.62) and wrestlers (2.23, 0.78, 3.68), among male athletes. These findings indicate that sex differences in FFMI exist, with differences identified between sports. These findings can guide strength and nutritional programming decisions by providing sport-specific normative data profiles.

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.

Abstract Multiple myeloma (MM) is an incurable form of plasma cell cancer in which primary and secondary chromosomal translocations routinely juxtapose oncogenes to plasma cell-specific super-enhancers. Coincidentally, drugs which target super-enhancers have had success clinically. For example, immunomodulatory imide drugs (IMiDs) degrade super-enhancer-binding pioneer factors IKAROS and AIOLOS, while glucocorticoids (Dexamethasone) and proteasome inhibitors (Bortezomib) have the ability to transrepress or block the processing of super-enhancer-forming NF-κB proteins, respectively. Currently, alternative enhancer-targeting drugs are also in clinical development, like p300 inhibitors which target the acetyl-binding bromodomains and/or histone acetyl transferase activity of the chromatin-regulating coactivator homologs CBP and EP300. Despite showing therapeutic promise, our understanding of how these drugs function, alone or together, remains incomplete. Case in point, we find that IMiD-induced degradation of its target proteins IKAROS and AIOLOS does not guarantee a therapeutic response in vitro, and patients successfully treated with IMiDs eventually relapse; meanwhile, coactivator-targeting therapies like p300 inhibitors are often too toxic in vivo, and lack a therapeutic window. To improve the outcomes of MM patients we need to understand the heterogeneous genetics and transcription-factor milieus of the myeloma enhancer landscape, as well as how to increase the precision of enhancer-disrupting drugs. To accomplish this, our lab utilizes more than 60 human myeloma cell lines that have been extensively characterized at the genetic, proteomic, and drug-therapeutic-response levels. Additionally, we have generated a highly-predictive immunocompetent mouse model (Vk*MYC hCRBN+) that develops human-like MM and is sensitive to both IMiDs and a new class of therapeutics termed "degronimids" (normal mice do not respond to IMiDs or degronimids). Our central hypothesis is that combining a broad coactivator-targeting drug (e.g., the p300 inhibitor GNE-781), with a MM-specific transcription factor-targeting drug (e.g., IMiDs) restricts toxicities to myeloma cells and thus improves the therapeutic window. Currently, we are testing a variety of coactivator-targeting compounds alongside traditional IMiD therapies and other preclinical transcription factor-targeting drugs both in vivo and in vitro. We show that Vk*MYC hCRBN+ mice are exquisitely sensitive to GNE-781, requiring one fourth of the dose needed to treat other cancers and therefore avoiding the neutropenia and thrombocytopenia seen at higher doses. Second, we show that although IMiDs and GNE-781 induce an effective but transient response in vivo as single agents, the combination of the two drugs proved curative, with a progressive deepening of the anti-tumor response occurring even after therapy is discontinued. Ongoing experiments aim to determine how this drug combination, and other coactivator + transcription factor-targeting combinations, permanently disrupt myeloma-specific super-enhancers. Disclosures Neri: BMS: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Bahlis: Sanofi: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Genentech: Consultancy. Boise: AstraZeneca: Honoraria, Research Funding; AbbVie/Genentech: Membership on an entity's Board of Directors or advisory committees. Chesi: Abcuro: Patents & Royalties: Genetically engineered mouse model of myeloma; Pi Therapeutics: Patents & Royalties: Genetically engineered mouse model of myeloma; Pfizer: Consultancy; Novartis: Consultancy, Patents & Royalties: human CRBN transgenic mouse; Palleon Pharmaceuticals: Patents & Royalties: Genetically engineered mouse model of myeloma.