Abstract: Hintergrund Die über die letzten Jahre/Jahrzehnte ausgebaute und optimierte gefäßchirurgische Grundversorgung hat auch das Fallaufkommen von Sekundärkomplikationen wie das Nahtaneurysma (NA) wesentlich erhöht. Ziel Darstellung der sekundären Versorgungsdiagnose NA in ihrem/r Fallaufkommen, Ätiopathogenese, Symptomatologie, Diagnostik, periinterventionellem/-operativem Management und Outcome, basierend auf selektiven Referenzen der medizinisch-wissenschaftlichen Literatur und eigenen klinischen Versorgungserfahrungen. Methode Narratives Review Ergebnisse Schlussfolgerung Das NA als relevante Versorgungsgröße ist inzwischen längst mit in den Fokus eines basalen gefäßchirurgischen/-interventionellen Betreuungsprofils gerückt, dem sich der Gefäßchirurg/-interventionalist aufgrund der bestehenden Herausforderung hinsichtlich des anspruchsvollen diagnostischen und therapeutischen Managements mit seiner ganzen fachspezifischen Kompetenz widmen muss.

Abstract: Introduction: Smoking is a potential risk factor for the development of non-Hodgkin lymphoma (NHL), and prior studies have reported inferior survival in tobacco users with certain subtypes of the disease (Taborelli et al, BMC Cancer, 2017; Ollberding et al, Br J Haematol, 2013). For instance, tobacco smokers with NHL had an inferior overall survival (OS) compared to non-smokers in a series of 471 patients who were managed up front with either chemotherapy (68%), radiation (27%), or observation, and this appeared to be most pronounced in patients with follicular lymphoma and in those with a 20+ pack year smoking history (Geyer et al, Cancer, 2010). The impact of tobacco use on survival specifically in patients with mantle cell lymphoma (MCL) has not been well studied. We conducted a multicenter study in MCL and evaluated the prognostic impact of tobacco use. Methods: We included patients with MCL from 12 sites who were ≥18 years old and for whom smoking status was known at the time of diagnosis. Cases were evaluated for reported smoking status at the time of diagnosis (active smoker, prior smoker, or never smoker) and standard baseline clinical prognostic data were obtained for each patient. Descriptive statistics were generated for these characteristics and were then compared across smoking status using chi-squared tests, Fisher's exact tests, or ANOVA, where appropriate. Overall survival (OS) and progression free survival (PFS) were estimated using the Kaplan-Meier method, and were compared using log-rank tests. Results: Of 946 included patients, 456 (48.2%) reported never using tobacco, 360 (38.7%) reported prior tobacco use, and 130 (13.7%) reported active tobacco use at the time of diagnosis. Median age was 59 in the active smoker group, 65 in prior smokers, and 61 in never smokers (p 〈 0.001). Any major medical comorbidity (defined as the presence of CAD, CHF, diabetes, CKD, ESRD, COPD, DVT, prior malignancy, or cirrhosis) was present in 59 (45.4%) of the active smokers, 143 (39.7%) of the prior smokers, and 140 (30.7%) of the never smokers (p = 0.002). Intensive induction regimens were used in 58.2% of active smokers, 47.2% of prior smokers, and 58.4% of never smokers (p=0.007). There were no significant differences between groups in regards to sex, race, ECOG performance status, Ann Arbor stage, time to first treatment, and use of auto transplant in first remission. Patients with no prior history of tobacco use were less likely to have a high risk MIPI score at diagnosis (26% high risk) compared to prior smokers (39.5%) and active smokers (32.5%, p=0.019). With a median follow up of 3.5 years after diagnosis, there was no significant difference between the 3 groups with regards to PFS or OS (Figure 1). Five-year OS in the never smoker group was 79.8% (95% CI: 74.8%, 83.9%) vs 75.1% (64.5%, 82.9%) in the active smoker group, and 80.6% (74.6%, 85.3%) in the prior smoker group (log rank p = 0.4079). Five- year progression free survival was 50.4% (44.6%, 56.0%) in the never smoker group, 42.5% (32.2%, 52.5%) in the active smoker group, and 50.2% (43.5%, 56.6%) in the prior smoker group (log rank p= 0.3595). Conclusions: Our data suggest that active or prior smoking does not significantly impact OS or PFS in patients with MCL. This study is limited by the fact that amount of current or former tobacco use was not available and it is not known how many current tobacco users ultimately stopped smoking during the course of their treatment. Future studies should incorporate more specific information regarding smoking history including pack-years and time between discontinuation of tobacco use and date of diagnosis. While tobacco use and other modifiable cardiovascular risk factors should be addressed as appropriate for all patients with MCL, current and former tobacco users can still achieve prolonged PFS and OS and may be candidates for intensive treatments after consideration of their other comorbidities and disease-specific risk factors. Disclosures Calzada: Seattle Genetics: Research Funding. Kolla:Amgen: Equity Ownership. Bachanova:Gamida Cell: Research Funding; GT Biopharma: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Celgene: Research Funding; Novartis: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees. Gerson:Seattle Genetics: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Mundipharma: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Takeda: Research Funding; Merck: Research Funding; Mundipharma: Honoraria; Bayer: Consultancy, Research Funding; Seattle Genetics: Honoraria, Research Funding. Danilov:Celgene: Consultancy; Abbvie: Consultancy; TG Therapeutics: Consultancy; Bayer Oncology: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Janssen: Consultancy; AstraZeneca: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Bristol-Meyers Squibb: Research Funding; MEI: Research Funding; Pharmacyclics: Consultancy; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Curis: Consultancy; Takeda Oncology: Research Funding; Seattle Genetics: Consultancy. Grover:Seattle Genetics: Consultancy. Karmali:Astrazeneca: Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Hill:Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; AstraZeneca: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celegene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ghosh:Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Speakers Bureau; Genentech: Research Funding; Celgene: Consultancy, Research Funding, Speakers Bureau; Forty Seven Inc: Research Funding; Gilead/Kite: Consultancy, Speakers Bureau; Spectrum: Consultancy, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; Astra Zeneca: Speakers Bureau. Park:BMS: Consultancy, Research Funding; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; G1 Therapeutics: Consultancy; Teva: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Epperla:Pharmacyclics: Honoraria; Verastem Oncology: Speakers Bureau. Hamadani:Pharmacyclics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Merck: Research Funding; Celgene: Consultancy; Janssen: Consultancy; Medimmune: Consultancy, Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Otsuka: Research Funding; Takeda: Research Funding. Kahl:TG Therapeutics: Consultancy; BeiGene: Consultancy; Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy, Research Funding. Martin:Janssen: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Teneobio: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy. Flowers:Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Spectrum: Consultancy; AstraZeneca: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Acerta: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Optimum Rx: Consultancy; Millenium/Takeda: Research Funding; Eastern Cooperative Oncology Group: Research Funding; National Cancer Institute: Research Funding; V Foundation: Research Funding; BeiGene: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; TG Therapeutics: Research Funding. Cohen:Genentech, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; LAM Therapeutics: Research Funding; UNUM: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding.

Abstract: Background Limited data are available on the clinical activity of venetoclax (ven) in mantle cell lymphoma (MCL). In 2 small retrospective studies of patients (pts) with MCL previously treated with BTK inhibitors (BTKi), ven resulted in overall response rates (ORRs) of 50-53% and median overall survival (OS) of 9-14 months (Eyre et al, Haematologica 2019; Zhao et al, Am J Hematol 2020). We sought to report the clinical activity of ven and identify factors associated with outcomes in a larger cohort of pts. Methods We included pts with relapsed MCL from 12 US medical centers treated with ven alone or in combination with an antiCD20 monoclonal antibody (mAb) or a BTKi. Response was determined by the local investigator. We defined OS as time from start of ven to death. Pts not experiencing an event were censored at their last known follow up. OS was determined using the Kaplan-Meier method, and univariable (UVA) and multivariable (MVA) models were developed to identify predictors of response and OS. Results Eighty-one pts were included. Pt characteristics (Table) at diagnosis (dx) were: median age 64 years (yrs) (range 38-87), male 79%, stage III/IV 95%, Ki67 & gt;30% in 61% (available n=62), blastoid/pleomorphic histology 29% (available n=75) and ≥3 cytogenetic abnormalities 34% (available n=62). BCL2 expression was present in 93% (available n=40). Frontline treatment (tx) included intensive chemotherapy [defined as including high-dose cytarabine and/or autologous transplant (ASCT) in first remission] in 52% with ASCT in first remission in 32%. Median number of therapies prior to ven was 3 (range 1-8) including antiCD20 mAb 99%, alkylator 93%, BTKi 91%, anthracycline 58%, cytarabine 56%, and lenalidomide 37%. 55% were refractory (defined as stable (SD) or progressive disease (PD)) to last tx prior to ven. ORR to BTKi prior to ven (n=70) was 66% (complete response (CR) 20%) with median duration of tx of 6.4 months (range 0.5-69). BTKi was stopped due to PD 82% and toxicity 18%. Median time from dx to start of ven was 3.9 yrs (range 0.2-17.8). Ven was given as monotherapy in 62% (n=50) and in combination with BTKi 20% (n=16), antiCD20 mAb 14% (n=11), or other 5% (n=4). Ten pts treated with ven in combination with BTKi received prior tx with BTKi with ORR to BTKi of 40% (all PR). Ven highest dose received was 20-100 mg in 12% (n=9), 200 mg 11% (n=8), 400 mg 61% (n=46), and 800 mg 17% (n=13). Median duration of tx with ven was 2.8 months (range 0.1-30). The best response to ven was CR 18%, partial response (PR) 24%, SD 11%, and PD 47% with ORR of 42%; 19 pts (23%) did not have available data for response. ORR was not significantly different with ven monotherapy 36% (13/36) vs ven + antiCD20 mAb 56% (5/9) vs ven + BTKi 43% (6/14) (p=.559), or with ven monotherapy 36% vs combination therapy 50% (13/26) (p=.274). Ven was stopped due to PD 69%, toxicity 9%, allogeneic transplant 3% or other reasons 19%. Laboratory tumor lysis syndrome (TLS) occurred in 10 pts (12%) including 3 (3.7%) with clinical TLS. 38 pts received post-ven tx with median time from stopping ven to next tx of 0.24 months (range 0-2.2); for the 33 pts with available data, the best response to post-ven tx was CR 24%, PR 27%, SD 9% and PD 39% with ORR of 51%. For the 75 pts with available data, median OS was 12.5 months (95% CI 6-17) with 3-year OS of 13.1% (95% CI 1.4-38.0%) (Figure A). Median OS was numerically longer with ven combination (28.7 months, 95% CI 4-not reached) vs monotherapy (8.6 months, 95% CI 4.7-14.4), p=.0825 (Figure B). Median OS did not significantly differ based on response (CR/PR vs SD/PD) to prior tx with BTKi (14.4 vs 9.5 months, p=.53, Figure C) or last tx prior to ven (16.7 vs 12.4 months, p=.14, Figure D). In MVA for response, achieving CR/PR with BTKi prior to ven (vs SD/PD) was associated with response to ven (odds ratio 3.48, 95% CI 1.01-12.05, p=.049). In MVA for OS, ven combination vs monotherapy (HR 0.13, 95% CI 0.03-0.53; p=.006), longer time from dx to start of ven ( & gt;4 vs ≤4 yrs) (HR 0.08, 95% CI 0.02-0.36; p=.001), and higher dose of ven (≥400 mg vs & lt;400) (HR 0.17, 95% CI 0.04-0.72; p=.016) were associated with superior OS, while longer duration of tx with BTKi ( & gt;6 vs ≤6 months) (HR 3.47, 95% CI 1.10-10.99; p=.038) was associated with inferior OS. Conclusions In these high-risk and heavily pretreated pts with MCL, ven resulted in low response rate and poor OS. Ven may have a better role in MCL in earlier lines of therapy and when combined with other agents such as BTKi and/or antiCD20 mAbs. Disclosures Kamdar: Roche: Research Funding. Greenwell:Lymphoma Research Foundation: Research Funding; Acrotech Biopharma LLC, Kyowa Kirin: Consultancy. Hess:ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS, AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Portell:Acerta/AstraZeneca: Research Funding; Kite: Consultancy, Research Funding; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; AbbVie: Research Funding; TG Therapeutics: Research Funding; Infinity: Research Funding; Roche/Genentech: Consultancy, Research Funding; Xencor: Research Funding. Goldsmith:Wugen Inc.: Consultancy. Grover:Genentech: Research Funding; Tessa: Consultancy. Riedell:Morphosys: Research Funding; Celgene/Bristol-Myers Squibb Company: Honoraria, Research Funding; Verastem Oncology: Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Kite Pharmaceuticals/Gilead: Honoraria, Research Funding; Bayer: Honoraria; Karyopharm Therapeutics: Honoraria. Karmali:BeiGene: Speakers Bureau; AstraZeneca: Speakers Bureau; Karyopharm: Honoraria; Takeda: Research Funding; Gilead/Kite: Honoraria, Other, Research Funding, Speakers Bureau; BMS/Celgene/Juno: Honoraria, Other, Research Funding, Speakers Bureau. Kumar:AbbVie: Research Funding; Kite Pharmaceuticals: Honoraria, Other: Honoraria for Advisory Board; Astra Zeneca: Honoraria, Other: Honoraria for Advisory Board; Celgene: Honoraria, Other: Honoraria for Advisory Board; Seattle Genetics: Research Funding; Pharmacyclics: Research Funding; Celgene: Research Funding; Adaptive Biotechnologies,: Research Funding. Hill:Abbvie: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding. Kahl:AstraZeneca Pharmaceuticals LP: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Consultancy; AbbVie: Consultancy; Genentech: Consultancy; Pharmacyclics LLC: Consultancy; Roche Laboratories Inc: Consultancy; BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cohen:Genentech, BMS, Novartis, LAM, BioInvent, LRF, ASH, Astra Zeneca, Seattle Genetics: Research Funding; Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo: Consultancy. OffLabel Disclosure: Venetoclax is not licensed for use in mantle cell lymphoma

Abstract: Checkpoint inhibitor (CPI) therapy with anti–PD-1 antibodies has been associated with mixed outcomes in small cohorts of patients with relapsed aggressive B-cell lymphomas after CAR-T failure. To define CPI therapy efficacy more definitively in this population, we retrospectively evaluated clinical outcomes in a large cohort of 96 patients with aggressive B-cell lymphomas receiving CPI therapy after CAR-T failure across 15 US academic centers. Most patients (53%) had diffuse large B-cell lymphoma, were treated with axicabtagene ciloleucel (53%), relapsed early (≤180 days) after CAR-T (83%), and received pembrolizumab (49%) or nivolumab (43%). CPI therapy was associated with an overall response rate of 19% and a complete response rate of 10%. Median duration of response was 221 days. Median progression-free survival (PFS) and overall survival (OS) were 54 and 159 days, respectively. Outcomes to CPI therapy were significantly improved in patients with primary mediastinal B-cell lymphoma. PFS (128 vs 51 days) and OS (387 vs 131 days) were significantly longer in patients with late ( & gt;180 days) vs early (≤180 days) relapse after CAR-T. Grade ≥3 adverse events occurred in 19% of patients treated with CPI. Most patients (83%) died, commonly because of progressive disease. Only 5% had durable responses to CPI therapy. In the largest cohort of patients with aggressive B-cell lymphoma treated with CPI therapy after CAR-T relapse, our results reveal poor outcomes, particularly among those relapsing early after CAR-T. In conclusion, CPI therapy is not an effective salvage strategy for most patients after CAR-T, where alternative approaches are needed to improve post–CAR-T outcomes.

Abstract: To report the activity of venetoclax in patients with relapsed mantle cell lymphoma (MCL), we identified 81 patients treated with venetoclax monotherapy (n = 50, 62%) or in combination with a Bruton tyrosine kinase inhibitor (BTKi) (n = 16, 20%), an anti-CD20 monoclonal antibody (n = 11, 14%), or other active agents at 12 US academic medical centers. Patients had high-risk disease features including Ki67  & gt;30% (61%), blastoid/pleomorphic histology (29%), complex karyotype (34%), and TP53 alterations (49%), and received a median of 3 prior treatments including BTKis in 91%. Venetoclax alone or in combination resulted in an overall response rate (ORR) of 40% and median progression-free (PFS) and overall survival (OS) of 3.7 and 12.5 months, respectively. The receipt of ≤3 prior treatments was associated with higher odds of response to venetoclax in a univariable analysis. In a multivariable analysis, having a high-risk Mantle Cell Lymphoma International Prognostic Index score before receiving venetoclax and disease relapse or progression within 24 months of diagnosis were associated with inferior OS whereas the use of venetoclax in combination was associated with superior OS. Although most patients (61%) had low risk for tumor lysis syndrome (TLS), 12.3% of patients developed TLS despite the implementation of several mitigation strategies. In conclusion, venetoclax resulted in good ORR but short PFS in patients with MCL who are at high risk, and may have a better role in earlier lines of treatment and/or in conation with other active agents. TLS remains an important risk in patients with MCL who initiate treatment with venetoclax.

Abstract: Background: Hematopoietic cell transplantation (HCT) is the only curative therapy for many patients with hematologic malignancies. In matched related donor (MRD) and matched unrelated donor (MUD) transplants, absolute lymphocyte count (ALC) recovery has been used as a surrogate marker for immune reconstitution, and a faster rate of ALC recovery is associated with improved overall survival (OS), relapse-free survival (RFS), and transplant-related mortality (TRM). Higher ALC counts have also been associated with higher rates of graft-versus-host disease (GVHD). For patients that do not have an HLA-matched donor available, haploidentical transplant (haplo-HCT) is now a viable option. Less is known about the impact of ALC recovery on outcome in the setting of haploidentical transplant with post-transplant cyclophosphamide (PTCy). Methods: In this study we retrospectively evaluated all patients who underwent haplo-HCT with post-transplant cyclophosphamide (PTCy) at our institution between June 2009 and January 2016. ALC and total white blood cell (WBC) count at days 30, 100, 180, and 365 post-transplant were collected along with demographics, treatment details, and outcome measures (OS, RFS, NRM, acute GVHD, and severe chronic GHVD). Since ALC is a component of total WBC used to assess for immune reconstitution, we performed additional analysis to assess if a high ALC relative to total WBC Ð or conversely, a low ALC relative to total WBC Ð had an effect on outcomes. At each time point, patients were divided into subgroups based on percentile of total WBC. Individual survival curves were generated for each subgroup for comparison. Cox proportional hazard models were used to measure the association between ALC and each outcome. The proportional hazards assumptions and functional assessment of ALC values were carried out using the K-S test and simulated martingale residuals. ALC was analyzed on a log scale to improve the fit of these models. Results: Of 141 evaluable patients, 128 survived to day 30 and were included in analysis. Clinical characteristics are summarized in table 1. At day 30, 100, 180 and 365 there were128, 99, 78 and 48 patients were alive, respectively. A high ALC at day 180 following transplant was associated with improved OS (mean ALC 915, HR 0.61, 95% CI 0.39-0.953; p = 0.030) and RFS (mean ALC 912, HR 0.593, 95% CI 0.422-0.834, p = 0.003). Furthermore, a higher ALC at day 100 was found to be associated with improved TRM (mean ALC 528, HR 0.54, 95% CI 0.35-0.84, p = 0.006). ALC was not associated with acute GVHD at any of the four time points. Severe chronic GVHD only occurred in 4 patients and therefore was not modeled. While a high ALC remained a significant predictor of improved OS, RFS, and TRM, there was no statistically significant difference between subgroups adjusted for percentile of WBC at each time point. Conclusions: ALC recovery is associated with improved OS, RFS, and TRM. Our results suggest that ALC is a useful prognostic marker for patients undergoing haploidentical HCT with post-transplant cyclophosphamide. Further studies examining immune reconstitution in this setting are planned, including the recovery of various T cell and NK cell subsets and their potential impact on outcomes after haplo-HCT using PTCy. Table 1 Clinical and demographic characteristics of patients undergoing haplo-HCT with PTCy. Table 1. Clinical and demographic characteristics of patients undergoing haplo-HCT with PTCy. Figure 1 Months to outcome or last follow-up by ALC, adjusted for percentile of total WBC. Figure 1. Months to outcome or last follow-up by ALC, adjusted for percentile of total WBC. Disclosures No relevant conflicts of interest to declare.