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Introduction T-cell prolymphocytic leukemia (T-PLL) is a rare and aggressive malignancy with limited treatment options, frequent relapse, and poor long-term survival. Allogeneic hematopoietic cell transplantation (allo-HCT) is reported to be effective in T-PLL yielding durable remissions and improved survival. Rates of survival and non-relapse mortality vary; data is scant and limited to small retrospective series. Whether regimen intensity - a modifiable factor- is associated with outcomes is unknown. Here, we report an analysis of patients with T-PLL undergoing allo-HCT in 87 centers using data reported to the Center for International Blood and Marrow Transplant Research (CIBMTR). Methods A retrospective multicenter study was conducted utilizing the CIBMTR dataset, which captures all consecutive patients transplanted in participating centers. The study population included patients aged 18 or older with T-PLL who underwent allo-HCT between 2008 and 2018. All donor types, graft sources, and conditioning intensities are summarized (Table 1). Cox regression analysis was used to assess overall mortality, treatment-related mortality (TRM), relapse or progression, disease-free survival (DFS) and acute and chronic graft-versus-host disease (GVHD). Due to the strong correlation between regimen intensity and patients' age, a combined variable was constructed, and in all models, interactions between age/regimen and significant covariates were examined. Results A total of 266 pts were identified and included in this analysis (Table 1). Median follow up of survivors was 49 months (range 3-117); the completeness of survival data out to four years was 95%. In univariate analysis, the 4-year overall survival (OS) rate was 30% (95% confidence interval [CI]: 23.8-36.5%). The 4-year DFS, relapse, TRM rates were 25.72% (95%CI: 20-32%), 41.9% (95%CI: 35.5-48.4%), and 32.4% (95%CI: 26.4-38.6%), respectively. Cumulative incidences of grade 2-4 acute GVHD at day +180 and chronic GVHD at 1-year were 22.5%% (95%CI: 16.8- 28.9%) and 38.3% (95%CI: 32.9-44.9%), respectively. Multivariate analyses was performed using age (Age >60 vs Age ≤60) and conditioning intensity (myeloablative [MAC] vs. reduced intensity/non-myeloablative [RIC/NMA]) as main effect (Table 2). Poor performance status was associated with inferior TRM, DFS and OS. Compared to MAC/Age ≤ 60, RIC/NMA/Age≤ 60 correlated significantly with less TRM (hazard ratio [HR] 0.28, 95% CI 0.14-0.55, p= 0.0022, superior DFS [HR 0.53, 95% CI 0.35-0.81, p= 0.0029; (Figure 3) and OS HR 0.49, 95% CI 0.32-0.75, p= 0.0009; (Figure 2). Similar trend was observed for RIC/NMA/ Age> 60 for all 3 outcomes but did not reach statistical significance. Remission status at time of allo-HCT (stable disease or progression vs. complete remission) correlated with relapse (hazard ratio [HR] of relapse=2.13, 95%CI 1.23-3.71, p=0.0072), however degree of response (partial response vs. complete remission did not significantly correlate with relapse (HR of relapse=1.41, 95%CI 0.91-2.17, p=0.1257). In vivo T cell depletion with ATG (N=47) or alemtuzumab (N=2) was associated with worse TRM [HR 1.82, 95% CI 1.08-3.08, p= 0.0255] and inferior DFS [HR of death or progression=HR 1.50, 95% CI 1.05-2.15, p= 0.0276]. The most common cause of death was disease relapse (52%) followed by infection (15%) and GVHD (13%). Conclusion This CIBMTR study, with the largest cohort of allo-HCT in T-PLL to date, demonstrates allo-HCT is effective in providing durable remissions. MAC and poor performance status were predictive of inferior TRM and OS. Disease relapse was most common cause of death, and pre-allo-HCT remission inversely correlated with relapse rate. The data suggest that reduced intensity conditioning and avoidance of post-transplant ATG/alemtuzumab may be beneficial. Novel strategies are needed both pre and post-allo-HCT to further improve outcomes. Disclosures Dholaria: J&J: Research Funding; bms: Research Funding; Takeda: Research Funding; Poseida: Research Funding; Angiocrine: Research Funding. Jagadeesh:Verastem: Membership on an entity's Board of Directors or advisory committees; Debiopharm Group: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; MEI Pharma: Research Funding; Regeneron: Research Funding. Oran:Celgene: Consultancy; ASTEX: Research Funding; Arog Pharmaceuticals: Research Funding. Nakamura:Viracor: Consultancy; Celgene: Other: Support on seminar; Magenta Therapeutics: Other: Advisory board meeting; NapaJen Pharma: Consultancy; Alexion: Other: Support on a meeting presentation; Merck: Other: advisory board meeting; Kadmon Corporation: Other: Advisory board meeting; Kyowa-Kirin: Other: Support on a meeting presentation. Sauter:Spectrum Pharamaceuticals: Consultancy; Sanofi-Genzyme: Consultancy, Research Funding; Gamida Cell: Consultancy; Novartis: Consultancy; Genmab: Consultancy; Precision Biosciences: Consultancy, Research Funding; Kite - a Gilead Company: Consultancy; Celgene: Consultancy, Research Funding; GSK: Consultancy; Bristol-Myers Squibb: Research Funding; Juno Therapeutics: Consultancy, Research Funding. kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy.

Background CD47 is an innate immune checkpoint that binds signal regulatory protein alpha (SIRPα) and delivers a "do not eat" signal to suppress macrophage phagocytosis. Overexpression of CD47 can allow tumor cells to escape immune surveillance. TTI-621 (SIRPαFc) is a fusion protein consisting of the CD47 binding domain of human SIRPα linked to the Fc region of human IgG1, designed to enhance phagocytosis and antitumor activity by blocking the CD47-SIRPα interaction between malignant cells and macrophages, and engaging Fcγ receptors. Here we report updates from the first-in-human study of TTI-621 (NCT02663518) in hematologic malignancies. Methods Study Part 1 tested increasing weekly intravenous doses of TTI-621 based on 3+3 escalation. The maximum tolerated dose was initially determined to be 0.2 mg/kg based on dose limiting toxicity (DLT) of thrombocytopenia [Grade (Gr) 4 of any duration]. Expanded testing followed in patients (pts) with hematologic malignancies, including leukemia, lymphoma, and multiple myeloma. In Part 2, most pts received 0.2 mg/kg. However, based on investigator discretion, a subset of pts received escalating doses up to 0.5 mg/kg. In Part 3, pts with T-cell lymphomas received stepwise dose escalations from 0.2 to 0.5 mg/kg over the first 5−8 weeks. In over 200 pts tested in Parts 1−3, thrombocytopenia did not increase with dose, typically recovered within 2−4 days, and was not associated with clinical sequelae. Part 4 was then undertaken to optimize TTI-621 dosing and is currently escalating doses in a 3+3 manner through pre-planned dose levels (0.5, 0.7, 1, and 1.4 mg/kg) in pts with cutaneous T-cell lymphoma (CTCL). The DLT criteria was modified to require Gr 4 thrombocytopenia lasting >72 hours. Safety monitoring includes weekly clinical laboratories and assessments of adverse events (AEs) per CTCAE v 4.03. Blood samples are obtained for pharmacokinetics (PK) and for pharmacodynamic (PD) assessments of receptor occupancy (RO) on normal peripheral T cells. Disease assessments are performed per Olsen's criteria. Results In Parts 1−3 (n=214), the most common related AEs were infusion-related reaction (IRR, 43%; 3% Gr ≥3), thrombocytopenia (30%; 22% Gr ≥3), chills (21%; 0% Gr ≥3), and fatigue (15%; 1% Gr ≥3). Objective responses to single agent TTI-621 were achieved in 14/71 (20%) NHL pts including CTCL (n=42, 1 CR, 7 PRs), PTCL (n=22, 2 CRs, 2 PRs) and DLBCL (n=7, 1 CR, 1 PR). In Part 4, as of July 10, 2020, 15 pts (9M/6F, median age 67 years) have enrolled into 4 dose cohorts (0.5−1.4 mg/kg). CTCL subtypes include mycosis fungoides (MF, n=10) and Sézary syndrome (n=5) with advanced (≥IIB) disease in 9 (60%) pts who received a median of 3 (range 1−12) prior systemic therapies. Related AEs have occurred in 11 (73%) pts including IRR (n=10) and thrombocytopenia (n=3); Gr ≥3 AEs have occurred in 4 (27%) pts including thrombocytopenia (n=3), IRRs (n=2), and exfoliative dermatitis (n=1). Thrombocytopenia generally occurred on dosing days, recovered in 2-4 days, and has not worsened with increasing doses. IRRs typically occurred during initial infusions. The Gr 3 IRR events occurred in 2 pts in the 1 and 1.4 mg/kg cohorts; low Gr IRRs have occurred across doses in 8 pts. IRRs typically resolved without recurrence and low Gr events often resolved allowing for completion of infusions. For initial infusions, the Gr 3 IRRs prompted increasing infusion times from 1 hour up to 4 hours and discretional use of steroid pre-medication. The exfoliative dermatitis occurred Day 80 and led to treatment discontinuation in 1 pt with MF whose underlying disease confounded the etiology. PK results reveal dose dependent increases in exposure; PD studies indicate ~60% RO at end of infusion up to 1 mg/kg. Antitumor activity to date includes 1 PR and 1 skin CR in 6 evaluable pts in the 1 mg/kg cohort; 2 responding pts bridged to allogeneic transplantation. The mean % change in mSWAT scores were -0.4%, -27%, and -37% for 0.5, 0.7 and 1 mg/kg cohorts, respectively. 1.4 mg/kg cohort results will be presented at the meeting. Conclusions In Parts 1−3, TTI-621 doses of 0.05 to 0.5 mg/kg were well-tolerated and demonstrated single agent activity in multiple hematologic malignancies. Preliminary data from Part 4 dose optimization indicate that weekly infusions of TTI-621 up to 1.4 mg/kg are well-tolerated without dose limiting or cumulative thrombocytopenia. Antitumor activity was seen at 1 mg/kg; dose escalation is continuing at 2 mg/kg. Disclosures Horwitz: Janssen: Consultancy; Verastem: Consultancy, Research Funding; Daiichi Sankyo: Research Funding; GlaxoSmithKline: Consultancy; ASTEX: Consultancy; Portola: Consultancy, Research Funding; C4 Therapeutics: Consultancy; Beigene: Consultancy; Myeloid Therapeutics: Consultancy; Vividion Therapeutics: Consultancy; Infinity/Verastem: Research Funding; Aileron: Consultancy, Research Funding; ADCT Therapeutics: Consultancy, Research Funding; Affirmed: Consultancy; Trillium: Consultancy, Research Funding; Corvus: Consultancy; Millenium/Takeda: Consultancy, Research Funding; Kyowa Hakka Kirin: Consultancy, Research Funding; Innate Pharma: Consultancy; Forty Seven: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Kura Oncology: Consultancy; Miragen: Consultancy; Mundipharma: Consultancy. Foran:Agios: Honoraria, Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Boehringer Ingelheim: Research Funding; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Revolution Medicine: Consultancy. Sawas:Flatiron Health: Current Employment; Gilead: Speakers Bureau; Seattle Genetics: Speakers Bureau; Daiichi Sankyo: Speakers Bureau; Affimed: Research Funding; Roche: Current equity holder in publicly-traded company. Feldman:AstraZeneca: Consultancy; Viracta: Research Funding; Trillium: Research Funding; Pfizer: Research Funding; Janssen: Speakers Bureau; Bayer: Consultancy, Honoraria; Kyowa Kirin: Consultancy, Research Funding; Eisai: Research Funding; Cell Medica: Research Funding; Amgen: Research Funding; Pharmacyclics: Honoraria, Other, Speakers Bureau; Abbvie: Honoraria; Takeda: Honoraria, Other: Travel expenses; Celgene: Honoraria, Research Funding; Kite: Honoraria, Other: Travel expenses, Speakers Bureau; BMS: Consultancy, Honoraria, Research Funding; Corvus: Research Funding; Rhizen: Research Funding; Seattle Genetics, Inc.: Consultancy, Honoraria, Other: Travel expenses, Research Funding, Speakers Bureau; Portola: Research Funding. Sokol:EUSA Pharma: Consultancy, Honoraria, Speakers Bureau; Kyowa/Kirin Inc.: Membership on an entity's Board of Directors or advisory committees; Kymera Therapeutics: Membership on an entity's Board of Directors or advisory committees. Mei:Sanofi: Consultancy; Morphosys: Membership on an entity's Board of Directors or advisory committees. Flinn:Gilead Sciences: Consultancy, Research Funding; F. Hoffmann-La Roche: Research Funding; Roche: Consultancy, Research Funding; Vincera Pharma: Consultancy; Agios: Research Funding; Iksuda Therapeutics: Consultancy; Great Point Partners: Consultancy; Genentech, Inc.: Research Funding; Forty Seven: Research Funding; Forma Therapeutics: Research Funding; ArQule: Research Funding; Kite Pharma: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Trillium Therapeutics: Research Funding; Triphase Research & Development Corp.: Research Funding; Curio Science: Consultancy; Constellation Pharmaceuticals: Research Funding; MorphoSys: Consultancy, Research Funding; Curis: Research Funding; Nurix Therapeutics: Consultancy; Novartis: Research Funding; Pfizer: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Portola Pharmaceuticals: Research Funding; Seattle Genetics: Consultancy, Research Funding; Teva: Research Funding; Loxo: Research Funding; BeiGene: Consultancy, Research Funding; Calithera Biosciences: Research Funding; Johnson & Johnson: Other; Rhizen Pharmaceuticals: Research Funding; Yingli Pharmaceuticals ≠: Consultancy, Research Funding; Verastem: Consultancy, Research Funding; Karyopharm Therapeutics: Research Funding; AstraZeneca: Consultancy, Research Funding; Incyte: Research Funding; Takeda: Consultancy, Research Funding; IGM Biosciences: Research Funding; Infinity Pharmaceuticals: Research Funding; Unum Therapeutics: Consultancy, Research Funding; Juno Therapeutics: Consultancy, Research Funding; Acerta Pharma: Research Funding; Celgene: Research Funding; Merck: Research Funding. Villa:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Research Funding; AZ: Consultancy, Honoraria, Research Funding; Kite/Gilead: Consultancy, Honoraria; Nano String: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Sandoz Canada: Consultancy, Honoraria; Immunovaccine: Consultancy, Honoraria; Purdue Pharma: Consultancy, Honoraria. Percival:Pfizer: Research Funding; Trillium: Research Funding; Nohla Therapeutics: Research Funding; Biosight: Research Funding; Oscotec: Research Funding; Cardiff Oncology: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Glycomimetics: Research Funding. Jagadeesh:Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Regeneron: Research Funding; Verastem: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Research Funding; Debiopharm Group: Research Funding. Savage:Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; BeiGene: Other: Steering Committee. Akilov:Mallinckrodt: Consultancy; Medivir: Consultancy; Seattle Genetics, Inc.: Consultancy; Kyowa Hakko Kirin: Consultancy; Soligenix: Honoraria; Pfizer: Research Funding; Actelion: Consultancy, Research Funding; Trillium Therapeutics Inc.: Consultancy, Research Funding. Diefenbach:Trillium: Research Funding; Millenium/Takeda: Research Funding; Seattle Genetics: Consultancy, Research Funding; Merck: Consultancy, Research Funding; MEI: Research Funding; LAM Therapeutics: Research Funding; Incyte: Research Funding; Genentech, Inc.: Consultancy, Research Funding; Denovo: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding. Kim:Kyowa-Kirin Pharma: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Medivir: Membership on an entity's Board of Directors or advisory committees; Horizon Pharma: Consultancy, Research Funding; Merck: Research Funding; miRagen: Research Funding; Trillium: Research Funding; Galderma: Membership on an entity's Board of Directors or advisory committees, Research Funding; Eisai: Membership on an entity's Board of Directors or advisory committees, Research Funding; Corvus: Research Funding; Elorac: Research Funding; Forty Seven Inc: Research Funding; Neumedicine: Consultancy, Research Funding; Innate Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Solingenix: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Portola: Research Funding. Lin:Trillium Therapeutics Inc.: Current Employment. Catalano:Trillium Therapeutics Inc.: Current Employment. Petrova:Trillium Therapeutics Inc.: Current Employment. Uger:Trillium Therapeutics Inc.: Current Employment. Molloy:Trillium Therapeutics Inc.: Current Employment. Large:Trillium Therapeutics Inc.: Current Employment. Shou:Trillium Therapeutics Inc.: Current Employment. Ansell:Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; Takeda: Research Funding; AI Therapeutics: Research Funding.

Hepatosplenic T-cell lymphoma (HSTCL) is a rare subtype of T-cell lymphoma associated with an aggressive clinical course and a worse prognosis. HSTCL develops in the setting of chronic immune suppression or immune dysregulation in up to 20% of cases and is most often characterized by spleen, liver, and bone marrow involvement. Diagnosis and management of HSTCL pose significant challenges given the rarity of the disease along with the absence of lymphadenopathy and poor outcome with conventional chemotherapy regimens. These Guidelines Insights focus on the diagnosis and treatment of HSTCL as outlined in the NCCN Guidelines for T-Cell Lymphomas.

e17539 Background: Chemotherapy with Docetaxel (D) or androgen pathway inhibition (API) with Abiraterone Acetate plus prednisone (AAP), Aplautamide(APA) and Enzalutamide(E) are acceptable, FDA approved treatment options for mCSPC. It is not clear whether the magnitude of benefit varies by the choice of initial agent [chemotherapy vs API] or by volume of disease [High vs Low]. Data is now available from all registration trials by volume status and motivated this analysis to inform initial treatment choice in mCSPC. Methods: We systematically searched MEDLINE(Ovid), Embase, and Scopus for randomized controlled trials of chemotherapy(D) or APIs (AAP, APA, ENZ) that had available hazard ratios (HRs) for overall survival (OS) and Progression Free Survival (PFS) according to patient’s volume of disease. We also reviewed abstracts and presentations from all major conference proceedings. We calculated the pooled overall survival HR and 95% CI by chemotherapy and APIs and by high volume(HVD) and low volume(LVD) using a random effect model, and tested for heterogeneity to assess the null hypothesis that no difference in the survival advantage exists by choice of initial agent and volume of disease. Results: Of 4456 studies identified in our search, there were 8 eligible randomized controlled trials that were included in the analysis. Both D and APIs significantly improved PFS [HR 0.48; 0.45-0.51] and OS [0.72; 0.64-0.81] when added to ADT, however the latter was associated with significantly higher improvement in PFS( P < 0.01) and OS (P = 0.03). In patients treated with D, patients with HVD derive significantly more benefit as compared to LVD( P = 0.046) and patients treated with APIs both HVD and LVD patients derive similar benefit( P = 0.80) (Table). Conclusions: mCSPC patients derive higher magnitude of survival benefit when treated with APIs as compared to D; however, D may be preferred in HVD patients. [Table: see text]

Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma (CTCL), and Sézary syndrome (SS) is a rare erythrodermic and leukemic subtype of CTCL characterized by significant blood involvement. Although early-stage disease can be effectively treated predominantly with skin-directed therapies, systemic therapy is often necessary for the treatment of advanced-stage disease. Systemic therapy options have evolved in recent years with the approval of novel agents such as romidepsin, brentuximab vedotin, and mogamulizumab. These NCCN Guidelines Insights discuss the diagnosis and management of MF and SS (with a focus on systemic therapy).

Abstract Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype. Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%. Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors. Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100% Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Abstract Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC. Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (&lt; BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points. Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume. Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time pointsT1T2T3npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offFullAll64734%0.662762334%0.701761134%0.6925Subset45334%0.6831133%0.7230534%0.72HR+/HER2-All26218%0.651924918%0.718225518%0.7519Subset13118%0.7124818%0.7120419%0.76HR+/HER2+All10636%0.642110538%0.62269634%0.7120Subset5332%0.668438%0.665740%0.73HR-/HER2+All5175%0.65204774%0.71204973%0.7116Subset3073%0.862871%0.872475%0.89HR-/HER2-All22842%0.682822243%0.751821143%0.6916Subset15940%0.7111137%0.7810540%0.75 Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-01.

6023 Background: The addition of trastuzumab (H) to a standard adjuvant therapy regimen (doxorubicin, cyclophosphamide, and paclitaxel; AC→T) is associated with a 52% reduction in risk (p < 0.0001) of disease recurrence in patients with HER2 positive operable breast cancer (Romond et al, NEJM 2005). A cost-effectiveness analysis was performed to assess the lifetime clinical and economic implications of this important clinical finding. Methods: A Markov model with three health states (disease-free survival [DFS], recurrence, and death) was used to estimate the likely cost-effectiveness (CE) for a 50 yr old woman. Efficacy results from both trials (NCCTG N9831/NSABP B-31) were used through 4 years, and projections of time to recurrence and death were based on the literature (EBCTCG, Lancet 2005). After 4 years, annual transition probabilities to recurrence and death are assumed to be the same in both arms. Cardiotoxicity was higher with H (Perez EA, ASCO 2005). Actual total dose of H was used which was lower than scheduled dose. Incremental costs associated with addition of H to adjuvant therapy were estimated using average wholesale prices, Medicare reimbursement rates and other published data. These costs included testing for HER2 status, drug and administration costs for H, cardiac monitoring, treatment of cardiotoxicity, treatment following recurrence, and end-of-life costs for dying patients. Utility estimates were derived from the literature. Results: Over a lifetime, the cost per quality-adjusted life year gained (QALY; discount rate 3%) is $27,800, with a range of $17,900 to $39,100 under multi-way sensitivity analysis. Projected life expectancy from the Markov model is 3 years longer for H patients (19.4 v 16.4 yrs). Over a 20-year horizon, addition of H to AC→T is estimated to cost an additional $46,300 on average, with an expected gain of 1.28 QALYs-a cost/QALY of $36,100. The key drivers of CE are the cost of treatment and the improvement in DFS. Conclusion: The model projects a cost-utility ratio that is below that of many treatments used for oncology patients. The use of trastuzumab in the adjuvant setting for HER2+ breast cancer is projected to be cost-effective. [Table: see text]

Objective: To describe reported outcomes of nonsurgical radiologic interventions for abdominal wall endometriosis in comparison with surgery where available. Data sources: A systematic search of Ovid Medline, Embase, PubMed, and Cochrane Controlled Register of Trials was performed from inception to January 2019 with no language restrictions. Study eligibility criteria: Studies were included if they evaluated a nonsurgical intervention in women with symptomatic abdominal wall endometriosis with both comparative and noncomparative study designs. Study appraisal and synthesis methods: Titles and abstracts were reviewed for relevance, and full-text articles were obtained and evaluated for inclusion, all in duplicate. Meta-analysis was performed when possible using a fixed effects model. Results: Of the 114 records reviewed, 16 full-text articles were assessed and 7 were included in analysis. The standard mean difference between pre- and post-intervention pain scores was similar between ultrasound-guided high-intensity focused ultrasound (USgHIFU) (−3.00; 95% confidence interval −3.34, −2.66) and cryoablation (−3.93; 95% confidence interval −5.73, −2.12). The mean percent decrease in lesion size following intervention was similar between USgHIFU (−61.38%; 95% confidence interval −78.64%, −44.11%), and cryoablation (−88.16%; 95% confidence interval −83.90%, −55.06%). When compared with surgical excision, mean length of stay was 2.78 days less in the nonsurgical intervention group (95% confidence interval −3.78, −1.79). Conclusions: Both USgHIFU and cryoablation are effective at reducing pain scores and lesion size in abdominal wall endometriosis. Mean length of stay was significantly less following a nonsurgical radiologic intervention for abdominal wall endometriosis compared with surgery. More studies are needed comparing complication and recurrence rates between nonsurgical radiologic interventions for abdominal wall endometriosis and surgery.

Introduction: Rituximab-based high-dose therapy (HDT) is frequently prescribed to DLBCL patients (pts) undergoing auto-HCT. However data supporting the benefit of adding R to auto-HCT conditioning are not available. Herein, we report the impact of R-based conditioning on auto-HCT outcomes of DLBCL pts. Methods: Using the Center for International Blood and Marrow Transplant Research registry, 862 adult (≥18 years) DLBCL pts undergoing auto-HCT, between 2003-2017 were included. Analysis was limited to pts receiving BEAM (BCNU, etoposide, cytarabine, melphalan)-based HDT, as R was infrequently used with non-BEAM conditioning regimens. All pts received R-containing chemoimmunotherapy in the frontline setting and had chemosensitive disease prior to HCT. Early chemoimmunotherapy failure (ECitF) was defined as not achieving a complete remission (CR) after frontline chemoimmunotherapy or relapsing within 1 year of initial diagnosis. Primary outcome was overall survival (OS). Secondary outcomes included non-relapse mortality (NRM), relapse, progression-free survival (PFS) and infectious complications within 100 days post-HCT. Results: The study cohort was divided into 2 groups; BEAM (n=667) and R-BEAM (n=195). The baseline characteristics of the 2 cohorts were comparable including age at auto-HCT, disease stage, Karnofsky performance score, extranodal involvement, time from diagnosis to auto-HCT, number of prior therapies, remission status, and ECitF. However, significantly more R-BEAM cohort patients received R as part of last therapy line before auto-HCT (75% vs. 86%; P=0.001). Median follow-up of survivors was 48 (range 1-171) and 64 (range 3-142) months in the BEAM and R-BEAM cohorts, respectively. On univariate analysis, the 4 year cumulative incidence of relapse (41% vs 44%), NRM (11% vs 9%), PFS (48% vs 47%; Figure 1) and OS (58% vs 61%; Figure 2) were similar in the R-BEAM and BEAM groups, respectively (Table 1). On multivariate analysis, no significant difference was seen in OS (HR 0.81; 95% CI 0.81-1.31; P=0.83) or PFS (HR 0.94; 95% CI 0.76-1.18; P=0.61) (Table 1) between the two cohorts. Addition of R had no impact on risk of relapse (HR 0.83; 95% CI 0.65-1.07; P=0.15) or NRM (HR 1.43; 95% CI 0.909-2.26; P=0.12). Variables independently associated with lower OS included older age (HR 3.05; 95% CI 1.81-5.13; P&lt;0.001), not being in CR at auto-HCT (HR 1.67, 95% CI 1.39-2.07; P&lt;0.001) and presence of ECitF (HR 1.52, 95% CI 0.54-3.26; P&lt;0.001). Older age (HR 2.26, 95% CI 1.48-3.45; P&lt;0.0002) and not being in CR at auto-HCT (HR 1.78, CI 1.47-2.14; P&lt;0.0001) were also associated with inferior PFS. There was no significant difference in the 100-day cumulative incidence of bacterial, viral or fungal infections between the two cohorts. Disease relapse was the main cause of death in both BEAM and R-BEAM cohorts (66% vs 55%). Conclusion: In this large registry analysis of DLBCL pts undergoing auto-HCT, adding R to BEAM conditioning had no impact on transplantation outcomes. Older age, absence of CR and ECitF were associated with inferior survival. Disclosures Majhail: Mallinckrodt: Honoraria; Incyte: Consultancy; Nkarta: Consultancy; Anthem, Inc.: Consultancy; Atara Bio: Consultancy. Sureda:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Gilead: Honoraria; Amgen: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Speakers Bureau; Novartis: Honoraria; BMS: Honoraria; Roche: Honoraria; Sanofi: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy. Hamadani:ADC Therapeutics: Consultancy, Research Funding; Merck: Research Funding; Takeda: Research Funding; Pharmacyclics: Consultancy; Celgene: Consultancy; Medimmune: Consultancy, Research Funding; Janssen: Consultancy; Otsuka: Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau.