Citations

Follicular lymphoma (FL) is an indolent B-cell neoplasm of germinal center origin. Standard treatment regimens consist of anti-CD20 therapy with or without chemotherapy. While high response rates to initial therapy are common, patients ultimately relapse or have progressive disease. Clinical risk factors such as the Follicular Lymphoma International Prognostic Index (FLIPI) have been identified, but there is a need for prognostic and predictive biomarkers. We studied markers of lymphoma cells and tumor microenvironment by immunohistochemistry in tissue samples from patients enrolled in 1 of 4 phase 2 trials of anti–CD20-based biological therapy for previously untreated grades 1 to 2 or 3A FL. Results were correlated with progression-free survival (PFS) and PFS status at 24 months. The 4 trials included 238 patients (51.1% male, median age: 55 y) with stage III, IV, or bulky stage II disease. By FLIPI, 24.6% had low-risk, 56.8% had intermediate-risk, and 18.6% had high-risk disease. The outcome differed significantly for patients treated with lenalidomide and rituximab (CALGB 50803) compared with the other 3 trials (median: PFS not reached vs. 3.0 y, hazard ratio=3.47, 95% confidence interval: 2.11-5.72); therefore, data were stratified by clinical trial (CALGB 50803 vs. all others) and adjusted for FLIPI risk group. Among 154 patients with available tissue, interfollicular BCL6 positivity, interfollicular CD10 positivity, and elevated Ki67 proliferation index ≥30% within neoplastic follicles were each associated with inferior PFS and a high risk of the early event by PFS status at 24 months. We identify promising biomarkers for FL risk stratification that warrant further validation in phase 3 trials.

AbstractThe mechanisms through which tau and amyloid-beta (Aβ) accumulate in the brain of Alzheimer’s disease patients may differ but both are related to neuronal networks. We examined such mechanisms on neuroimaging in 58 participants with atypical Alzheimer’s disease (posterior cortical atrophy or logopenic progressive aphasia). Participants underwent Aβ-PET, longitudinal tau-PET, structural MRI and resting-state functional MRI, which was analyzed with graph theory. Regions with high levels of Aβ were more likely to be functional hubs, with a high number of functional connections important for resilience to cascading network failures. Regions with high levels of tau were more likely to have low clustering coefficients and degrees, suggesting a lack of trophic support or vulnerability to local network failures. Regions strongly functionally connected to the disease epicenters were more likely to have higher levels of tau and, less strongly, of Aβ. The regional rate of tau accumulation was associated with tau levels in functionally connected regions, in support of tau accumulation in a functional network. This study elucidates the relations of tau and Aβ to functional connectivity metrics in atypical Alzheimer’s disease, strengthening the hypothesis that the spread of the 2 proteins is driven by different biological mechanisms related to functional networks.

Abstract Alzheimer’s disease is characterized by the presence of amyloid-β and tau deposition in the brain, hippocampal atrophy and increased rates of hippocampal atrophy over time. Another protein, TAR DNA binding protein 43 (TDP-43) has been identified in up to 75% of cases of Alzheimer’s disease. TDP-43, tau and amyloid-β have all been linked to hippocampal atrophy. TDP-43 and tau have also been linked to hippocampal atrophy in cases of primary age-related tauopathy, a pathological entity with features that strongly overlap with those of Alzheimer’s disease. At present, it is unclear whether and how TDP-43 and tau are associated with early or late hippocampal atrophy in Alzheimer’s disease and primary age-related tauopathy, whether either protein is also associated with faster rates of atrophy of other brain regions and whether there is evidence for protein-associated acceleration/deceleration of atrophy rates. We therefore aimed to model how these proteins, particularly TDP-43, influence non-linear trajectories of hippocampal and neocortical atrophy in Alzheimer’s disease and primary age-related tauopathy. In this longitudinal retrospective study, 557 autopsied cases with Alzheimer’s disease neuropathological changes with 1638 ante-mortem volumetric head MRI scans spanning 1.0–16.8 years of disease duration prior to death were analysed. TDP-43 and Braak neurofibrillary tangle pathological staging schemes were constructed, and hippocampal and neocortical (inferior temporal and middle frontal) brain volumes determined using longitudinal FreeSurfer. Bayesian bivariate-outcome hierarchical models were utilized to estimate associations between proteins and volume, early rate of atrophy and acceleration in atrophy rates across brain regions. High TDP-43 stage was associated with smaller cross-sectional brain volumes, faster rates of brain atrophy and acceleration of atrophy rates, more than a decade prior to death, with deceleration occurring closer to death. Stronger associations were observed with hippocampus compared to temporal and frontal neocortex. Conversely, low TDP-43 stage was associated with slower early rates but later acceleration. This later acceleration was associated with high Braak neurofibrillary tangle stage. Somewhat similar, but less striking, findings were observed between TDP-43 and neocortical rates. Braak stage appeared to have stronger associations with neocortex compared to TDP-43. The association between TDP-43 and brain atrophy occurred slightly later in time (∼3 years) in cases of primary age-related tauopathy compared to Alzheimer’s disease. The results suggest that TDP-43 and tau have different contributions to acceleration and deceleration of brain atrophy rates over time in both Alzheimer’s disease and primary age-related tauopathy.

8038 Background: Bone marrow biopsies (BMB) are performed pre/post therapy to confirm complete response (CR) in patients (pts) with lymphoma on clinical trials. We evaluated 2 prior data sets and concluded that BMB impact response assessment in a minority of pts with follicular lymphoma (FL) (Rutherford BJH 2017; Rutherford ASH abstract 1605, 2018). We sought to establish if BMB add value in assessing response or identify distinct progression free (PFS) or overall survival (OS) outcomes in a large, multicenter, multi-trial cohort. Methods: Data were pooled from 7 trials of 580 pts with untreated FL conducted through the Alliance for Clinical Trials in Oncology and SWOG from 2002-2016. The proportion of pts with positive (+) baseline BMB, CR on imaging after treatment, and (+) repeat BMB was calculated using total pts enrolled as the denominator. We tested against the null hypothesis that the proportion was = 10%, the threshold below which BMB would be considered irrelevant for response assessment, versus (vs) the alternative hypothesis that this proportion was < 10%, using 1-sided exact binomial test. Response criteria were CT-based. Imaging was not used to assess BM involvement. Because confirmatory BMB were not completed in all indicated pts, landmark survival analyses compared PFS/OS of pts with CR on imaging and negative (-) BMB vs pts with CR on imaging without repeat BMB. Pts with CR on imaging were categorized as having (-) repeat BMB or no repeat BMB within 60 days of first CR on imaging. PFS and OS were calculated from time of first CR and estimated using Kaplan-Meier and Cox models adjusting for age, sex, stage, Follicular Lymphoma International Prognostic Index (FLIPI) score, and treatment type (targeted vs chemotherapy plus targeted therapy), and stratified by treatment arm. Results: Median age was 55 with 51% male, 96% stage III-IV, and 88% grade I-II. FLIPI scores were 113 low, 265 intermediate, and 199 high risk. 67% received chemotherapy-based regimens. Baseline BMB was (+) in 321 (55%). Only 5/580 (0.8%) had (+) baseline BMB, CR on imaging, and subsequent (+) BMB (p < 0.0001). Of pts with CR on imaging, PFS and OS were not different among pts with (-) BMB vs pts without repeat BMB (PFS: HR = 1.08, 95%CI 0.61-1.93, p = 0.783; OS: HR = 0.52, 95%CI 0.20-1.40, p = 0.199). Conclusions: BMB requirements may discourage pt participation in trials and add pain, expense and time without providing necessary information. We recommend eliminating BMB for response assessment from FL clinical trials. Clinical trial information: NCT00553501, NCT01145495, NCT01190449, NCT01286272, NCT01829568, NCT00822120, and NCT00770224 .

Abstract Alzheimer’s disease can present clinically with either the typical amnestic phenotype or with atypical phenotypes, such as logopenic progressive aphasia and posterior cortical atrophy. We have recently described longitudinal patterns of flortaucipir PET uptake and grey matter atrophy in the atypical phenotypes, demonstrating a longitudinal regional disconnect between flortaucipir accumulation and brain atrophy. However, it is unclear how these longitudinal patterns differ from typical Alzheimer’s disease, to what degree flortaucipir and atrophy mirror clinical phenotype in Alzheimer’s disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenotypes. We aimed to address these unknowns using a cohort of 57 participants diagnosed with Alzheimer’s disease (18 with typical amnestic Alzheimer’s disease, 17 with posterior cortical atrophy and 22 with logopenic progressive aphasia) that had undergone baseline and 1-year follow-up MRI and flortaucipir PET. Typical Alzheimer’s disease participants were selected to be over 65 years old at baseline scan, while no age criterion was used for atypical Alzheimer’s disease participants. Region and voxel-level rates of tau accumulation and atrophy were assessed relative to 49 cognitively unimpaired individuals and among phenotypes. Principal component analysis was implemented to describe variability in baseline tau uptake and rates of accumulation and baseline grey matter volumes and rates of atrophy across phenotypes. The capability of the principal components to discriminate between phenotypes was assessed with logistic regression. The topography of longitudinal tau accumulation and atrophy differed across phenotypes, with key regions of tau accumulation in the frontal and temporal lobes for all phenotypes and key regions of atrophy in the occipitotemporal regions for posterior cortical atrophy, left temporal lobe for logopenic progressive aphasia and medial and lateral temporal lobe for typical Alzheimer’s disease. Principal component analysis identified patterns of variation in baseline and longitudinal measures of tau uptake and volume that were significantly different across phenotypes. Baseline tau uptake mapped better onto clinical phenotype than longitudinal tau and MRI measures. Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment trials in Alzheimer’s disease are different for MRI and tau-PET and may differ across phenotypes, particularly for MRI. Baseline tau tracer retention showed the highest fidelity to clinical phenotype, supporting the important causal role of tau as a driver of clinical dysfunction in Alzheimer’s disease.

Initial therapy for MCL is effective, but most patients eventually relapse. Validated intermediate biomarkers for MCL are important to provide early assessment of treatment efficacy, prognostic information and potentially guide consolidation. The US-Canadian Intergroup trial E1411 randomly assigned patients (pts) to receive induction with BR ± bortezomib (V), followed by consolidation with R ± L. As a planned correlative, MRD was assessed after cycle 3 (I3), end of induction (EOI) and after 4 cycles of consolidation (C4) by two methods: a research version of clonoSEQ® a next generation sequencing (NGS) MRD assay, (Adaptive Biotechnologies, Seattle, WA) that leverages multiplex PCR followed by NGS to identify and track rearrangements of IgH, V-J, D-J and IgK/L loci as well as translocations in Bcl1/2-IgH, and flow cytometry (FC) (I3 and EOI only) at a central laboratory (Mayo Clinic). While outcomes by treatment arm remain blinded, we report here the results of the MRD assessments by each method and the associated progression free survival (PFS). In E1411, 373 pts, accrued between May 2012 - Sept. 2016, were randomly assigned (stratified by MIPI and age (&lt;/≥60)) to receive BR induction x 6 followed by R for 2 years, BVR followed by R, BR followed by LR or BVR followed by LR. Eligible pts were ≥ age 18 and had untreated MCL, ECOG PS 0-2, and adequate hematologic and organ function. Of the 373 pts, 296 (79%) consented to correlatives. Of these, 255 (86%) had baseline NGS samples, and 214 were analyzable. Excluded were 6 patients that were protocol ineligible, 20 without clinical follow-up; only 7 (2.7%) patients were ineligible due to inability to identify a dominant clone necessary to follow MRD by the NGS method. At baseline pre-treatment, NGS detected a dominant clone in bone marrow (BM) or peripheral blood (PB) in 92%, with only 17 (8%) requiring study of biopsy tissue. Of the 296, 240 had baseline FC data, 9 were protocol exclusions, leaving 231 analyzable. FC detected a non-MCL monoclonal B cell lymphocytosis clone in a small number of cases. While NGS may have higher sensitivity, as FC sensitivity is 10-4, for this analysis we used that cutoff for both NGS and FC. Cohen's Kappa statistic compares concordance between MRD pairs, and p-value is from exact McNemar's test. BR-based initial MCL therapy achieved early MRD negativity (&lt; 10-4) in a high proportion of patients. Analyzing PB at mid-induction (I3): by NGS 89% MRD-, 9% MRD+ and 2% indeterminate, whereas by FC 87% MRD-, 12% MRD+ and 1% indeterminate. Concordance was high with 127 MRD- by both methods, 13 MRD+ by both, and 6 NGS-/FC+ (Kappa Statistic = 0.79, p-value = 0.031). By NGS, of 12 pts MRD+ at I3, 7 became MRD- at EOI, and 4 remained MRD+ (1 indeterminate). Analyzing at EOI: MRD- rates were 91% by NGS analysis of PB (147/161) and 90% in BM (96/107), vs 95% (174/183) by FC in PB. As some were indeterminate, only 7% were MRD+ by NGS in BM, 3% by NGS in PB and 5% by FC. In 88 informative samples with EOI NGS in both BM and PB, concordance was high, with 81 negative in both, 1 positive in both and 6 BM+/PB- (Kappa Statistic = 0.23, p-value = 0.031). Of 101 pts with data at all 3 timepoints, I3, EOI, and C4: 7 were MRD+ at I3, 5 of these were MRD- at EOI, but 2 of these 5 were again MRD+ at C4. Of 2 MRD+ EOI, 1 became MRD- at C4. By FC, of 17 patients MRD+ at I3, 11 (65%) became MRD- at EOI. MRD status correlated with progression-free survival (PFS). Due to the low MRD+ rate at EOI and C4, we focus here on MRD status at I3 (10-4 cutoff for both NGS and FC), using a landmark analysis of 4 months on study. Median PFS (Figure) for pts MRD- at I3 mid-induction was 58.9 months by either NGS or FC, while for those MRD+ by NGS it was 26.9 months, vs 29.9 months MRD+ by FC. Conclusions: Both NGS and FC were feasible to assess MRD status in this multi-center trial. Results of NGS and FC are concordant at the 10-4 cutoff. NGS can be more sensitive when adequate material is available, and analysis of this subgroup is ongoing. The high MRD- rate (≥ 90%) at EOI in this BR-based trial and MRD correlation with PFS supports its use as a platform for MCL trials, although consolidation may confound PFS. Early interim MRD testing at cycle 3 identifies a high-risk population who may benefit from alternative treatment strategies. Analysis by treatment arm with longer follow-up, as well as comparison with centrally reviewed PET/CTs included in this study, will help define the most informative method(s), cutoff values, and timing for assessing degree of response in MCL. Figure. Disclosures Smith: Astra-Zeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; EUSA: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Parekh:Foundation Medicine Inc.: Consultancy; Celgene Corporation: Research Funding; Karyopharm Inc.: Research Funding. Martin:Sandoz: Consultancy; Karyopharm: Consultancy; Teneobio: Consultancy; Celgene: Consultancy; Janssen: Consultancy; I-MAB: Consultancy. Till:Mustang Bio: Patents & Royalties, Research Funding. Leonard:Gilead: Consultancy; Akcea Therapeutics: Consultancy; Bayer Corporation: Consultancy; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy; BeiGene: Consultancy; Celgene: Consultancy; Akcea Therapeutics: Consultancy; Nordic Nanovector: Consultancy; ADC Therapeutics: Consultancy; Sandoz: Consultancy; MorphoSys: Consultancy; Sutro Biopharma: Consultancy; Karyopharm Therapeutics: Consultancy; Karyopharm Therapeutics: Consultancy; Merck: Consultancy; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy; Epizyme, Inc: Consultancy; Gilead: Consultancy; AstraZeneca: Consultancy; Epizyme, Inc: Consultancy; Bayer Corporation: Consultancy; Miltenyi: Consultancy; Celgene: Consultancy; ADC Therapeutics: Consultancy; MorphoSys: Consultancy; Sandoz: Consultancy; Miltenyi: Consultancy; AstraZeneca: Consultancy; Nordic Nanovector: Consultancy; Merck: Consultancy; BeiGene: Consultancy; Sutro Biopharma: Consultancy. Friedberg:Bayer: Honoraria, Other: Data & Safety Monitoring Committee; Acerta: Other: Data & Safety Monitoring Committee. Kahl:TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy; BeiGene: Consultancy.

Background REGN1979 is an anti-CD20 x anti-CD3 bispecific IgG4 antibody (Ab) modified to reduce Fc binding. Engaging both targets results in CD20-specific, local T-cell activation and cytotoxicity, a mechanism of action distinct from standard anti-CD20 Abs. Dose escalation is complete and a recommended Ph 2 dose has been determined. We report Ph 1 safety and efficacy results of REGN1979 in patients (pts) with R/R B-NHL previously treated with anti-CD20 Abs, including pts with progressive disease after anti-CD19 CAR T-cell (CAR T) therapy. Methods Primary objectives are to determine safety, tolerability, and occurrence of dose limiting toxicities (DLTs). Other objectives are to assess antitumor activity, pharmacokinetics (PK), and pharmacodynamics. Eligible pts with R/R B-NHL must have received prior CD20-directed therapy. Treatment consists of 12 weekly intravenous doses of REGN1979 followed by every 2-week dosing for 12 doses (36 weeks total). Results As of June 3, 2019, 96 pts (diffuse large cell B-cell lymphoma [DLBCL] [n=53], follicular lymphoma [FL] grade [Gr] 1-3a [n=25], mantle cell lymphoma [n=6], marginal zone lymphoma [n=6], or other [FL Gr 3b, FL unknown, FL ungraded, or Waldenström macroglobulinemia ] [n=6]) were treated with REGN1979 0.03-320 mg and received a median of 9 doses (range 1-24). Pts had a median of 3 prior lines of therapy (range 1-11); 12 pts with prior CAR T therapy were included in the safety analysis of which 6 were included in the efficacy analysis. Twenty-four pts remain on treatment; 18 completed treatment; 54 discontinued early (35 due to progressive disease [PD]). No pts with B-NHL experienced a DLT. The most common treatment-emergent adverse events (AEs) were pyrexia (n=74), CRS (n=55), chills (n=49), infections and infestations (n=47), fatigue (n=36), increased C-reactive protein (n=32), and anemia (n=32). Seven pts experienced Gr 3 CRS. The severity of CRS symptoms declined through optimized pre-medication even with REGN1979 dose escalation. Most common Gr 3 or 4 AEs were anemia (n=19), decreased lymphocytes/lymphopenia (n=19), infections and infestations (n=18), decreased neutrophils/neutropenia (n=17), and hypophosphatemia/decreased blood phosphorus (n=16). No pts had seizures or grade 4/5 neurologic AEs. Gr 3 neurologic AEs included depressed level of consciousness (unrelated), somnolence, and syncope (n=1 each). Neurological events were transient and none required permanent treatment termination. Five pts discontinued due to AEs: Gr 3 hemolysis; Gr 3 fatigue; Gr 2 and Gr 3 pneumonia; and Gr 3 neck abscess (1 each). Eleven pts died on study: PD (n=6), gastric perforation (n=1), cardiac arrest (n=1), lung infection (n=1), multi-organ failure (n=1), pneumonia (n=1). The Table and Figure show efficacy and duration of response for R/R DLBCL by dose level. Pts who had opportunity for response assessment at Week 12 were included in the analysis of response. Emerging data suggest increasing efficacy with higher doses in R/R DLBCL, with 5 of 8 pts treated at 80/160/320 mg achieving CR; at these doses 2 of 3 pts achieved CR after failure of CAR T therapy. Data also suggest increasing efficacy with increasing doses in R/R FL, but maximum efficacy appears to be achieved at lower doses than in DLBCL; in pts with FL Gr 1-3a treated at ≥5 mg, the ORR was 93% (13/14), and the CR rate was 71.4% (10/14). REGN1979 concentrations in serum increased linearly with dose during the first five weeks. Elevated levels of serum cytokines were observed, mostly in week 1, and no correlation was observed with clinical efficacy. Immunohistological analysis of malignant lymph node tissue demonstrated that pts with high and low CD20 expression achieved clinical response. Relapse among responders was seen with either maintenance or loss of CD20 expression, suggesting antigen-dependent and independent disease escape mechanisms. Conclusions/Summary Tolerability of REGN1979 has been demonstrated at doses up to the final dose level of 320 mg weekly, with no observed DLTs in pts with B-NHL. No pts discontinued due to neurologic AE. Activity was observed broadly in heavily pretreated R/R B-NHL pts treated with REGN1979. With increasing dose, more resistant tumors such as R/R DLBCL are showing benefit, even in pts with prior CAR T therapy failure. Based on these efficacy findings, a global Ph 2 study is underway to evaluate REGN1979 monotherapy in R/R FL Gr 1-3a, R/R DLBCL, and other R/R B-NHL subtypes. Disclosures Bannerji: AbbVie, Inc: Consultancy, travel support; Gilead: Other: travel support; Gilead: Other: travel support; Pharmacyclics: Other: travel support; Merck: Other: travel support, Patents & Royalties: IP rights; AbbVie, Inc: Consultancy; Regeneron Pharmaceuticals, Inc.: Consultancy, Other: travel support, Research Funding; Regeneron Pharmaceuticals, Inc.: Consultancy, Other: travel support, Research Funding; Celgene: Consultancy; Celgene: Consultancy; Merck: Other: travel support, Patents & Royalties: IP rights; Pharmacyclics: Other: travel support. Allan:Acerta Pharma: Consultancy; Sunesis Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics LLC, an AbbVie company: Consultancy; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Consultancy; Verastem Oncology, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria. Arnason:Celgene/Juno: Consultancy; Regeneron Pharmaceuticals, Inc.: Consultancy. Brown:AstraZeneca: Consultancy; Acerta Pharma: Consultancy; Morphosys: Other: Data safety monitoring boards ; Sun Pharmaceuticals, Inc: Research Funding; Sun: Research Funding; Verastem: Consultancy, Research Funding; TG Therapeutics: Consultancy; Teva: Honoraria; Sunesis: Consultancy; Pharmacyclics: Consultancy; Pfizer: Consultancy; Janssen: Honoraria; Invectys: Other: other; Loxo: Consultancy, Research Funding; Novartis: Consultancy; Octapharma: Consultancy; Kite: Consultancy, Research Funding; Dynamo Therapeutics: Consultancy; Catapult Therapeutics: Consultancy; BeiGene: Consultancy; Gilead: Consultancy, Research Funding; Genentech/Roche: Consultancy. Advani:Kyowa Kirin Pharmaceutical Developments, Inc.: Consultancy; Seattle Genetics: Consultancy, Research Funding; Celmed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Forty-Seven: Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kura: Research Funding; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Research Funding; Gilead Sciences, Inc./Kite Pharma, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity Pharma: Research Funding; Janssen: Research Funding; Merck: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cell Medica, Ltd: Consultancy; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agensys: Research Funding; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Stanford University: Employment, Equity Ownership; Regeneron: Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ansell:Seattle Genetics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Mayo Clinic Rochester: Employment. O'Brien:Pfizer: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Acerta: Research Funding; Alexion: Consultancy; Amgen: Consultancy; Aptose Biosciences, Inc: Consultancy; Astellas: Consultancy; Celgene: Consultancy; Eisai: Consultancy; Gilead: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Kite: Research Funding; Janssen: Consultancy, Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Regeneron: Research Funding; Verastem: Consultancy; Sunesis: Consultancy, Research Funding; Vaniam Group LLC: Consultancy; TG Therapeutics: Consultancy, Research Funding. Chavez:Janssen Pharmaceuticals, Inc.: Speakers Bureau; Kite Pharmaceuticals, Inc.: Membership on an entity's Board of Directors or advisory committees; Genentech: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees. Duell:Regeneron Pharmaceuticals, Inc.: Research Funding. Martin:I-MAB: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Sandoz: Consultancy; Teneobio: Consultancy. Charnas:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Ambati:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Adriaens:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Ufkin:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Zhu:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Li:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Gasparini:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Ibrahim:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Jankovic:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Fiaschi:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Aina:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Zhang:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Deering:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Hamon:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Thurston:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Murphy:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Weinreich:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Yancopoulos:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Lowy:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Sternberg:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Topp:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Boehringer Ingelheim: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Regeneron Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: The data described in the abstract will report on use REGN1979 in a Phase 1 clinical trial of patients with B-NHL.

Introduction. The VES-13 is a simple, self-reported, function based tool originally developed to screen community-dwelling populations to identify persons age 65 years and older at risk of death and functional decline, including death in the next 12 months. The VES-13 items include patient's age, self-rated overall health status, functional limitations in physical activity, and functional disabilities in more complex activities of daily living. As part of the Lymphoma Epidemiology of Outcomes (LEO) cohort study, we collected self-reported VES-13 data at study enrollment on all participants regardless of age, and here we report on the prevalence of vulnerable status defined by the VES-13 and its association with 1-year mortality, overall, stratified at age 65 years, and in the subset of diffuse large B-cell lymphoma (DLBCL) treated with immunochemotherapy. Methods. From 7/2015 to 6/2017, 3253 participants with NHL were enrolled within 6 months of their diagnosis into the LEO cohort. 2004 were evaluable on VES-13, and 1183 (59%) completed it before the initiation of therapy. VES-13 scores range from a minimum of 0 (low risk for decline) to a maximum of 10 (greatest risk for decline), and a score ≥3 was classified as vulnerable. Clinical, pathology and treatment data were abstracted using a standard protocol, and participants were contacted every 6 months for the first three years and then annually thereafter to identify outcomes. Medical records were reviewed by LEO clinicians to classify cause of death according to a standard protocol. Therapy was determined by the treating physician, and this was independent of knowledge of the VES-13 score. The association of VES-13 with 1-year mortality from date of diagnosis was estimated using odds ratios (OR) and 95% confidence intervals (CI) from logistic regression models, which also provided model c-statistics. Results. The median age of the 2004 participants in this analysis was 62 years (range 18-94); 57% were male; 54% were ≥65 years; and 28% had a normal body mass index (BMI), 1% were underweight, 35% were overweight, and 36% were obese. Clinically, 59% of participants had an aggressive subtype, 65% were stage III-IV, 24% had B-symptoms, and 11% had a performance status (PS) of ≥2. Overall, 28% of participants were classified as vulnerable (95% CI 26%-30%), with a higher prevalence among those completing the survey after initiation of therapy (38%, 95% 34%-41%) versus before initiation of therapy (22%, 95% CI 20%-24%), and a higher prevalence for those ≥65 years (32%, 95% CI 29%-34%) versus &lt;65 (25%, 95% CI 22%-28%). During the first year of follow-up, there were 147 deaths, with 61% due to lymphoma, 14% therapy-related, 12% due to another malignancy, 3% other causes, and 10% unknown. Significant univariate predictors of 1-year mortality included vulnerable status, older age, PS 2+, stage III-IV, aggressive subtype, lower quality of life score, lower BMI, and 1 or more comorbidities, and were included the backward stepwise modeling. Vulnerable status (OR=3.26, 95% CI 2.15-4.96) was retained in the final model that also included age, PS, stage, and NHL subtype (Table), with a model c-statistic of 0.81. As shown in the Table, these associations were similar whether VES-13 was assessed before (c-statistic 0.77) or after (c-statistic 0.81) initiation of therapy. After adjustment for age, PS, stage and NHL subtype, vulnerable status predicted 1-year mortality in participants ≥65 years (OR=1.96, 95% CI 1.15-3.36; model c-statistic 0.80) as well as &lt;65 years (OR=6.38, 95% CI 3.07-13.3; model c-statistic 0.83). Finally, in the DLBCL patients treated with immunochemotherapy (N=521), vulnerable status (38% of patients) also predicted 1-year mortality (OR=2.11, 95% CI 1.05-4.26) after adjusting for age, PS and stage (model c-statistic 0.78). Conclusion. Based on a self-administered VES-13, 28% of newly diagnosed NHL patients in the LEO cohort were classified as vulnerable, including 25% of those &lt;65 years, and vulnerable status was a strong predictor of 1-year-mortality, even in the subset of DLBCL patients treated with presumed curative intent. These results highlight the potential value of screening for vulnerable status overall and across a wider age spectrum in order to optimize patient management and reduce early mortality. Disclosures Martin: Karyopharm: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Teneobio: Consultancy. Casulo:Gilead: Honoraria, Other: Travel, accommodation, expenses; Celgene: Research Funding; Roche: Other: Travel, accommodation, expenses. Cohen:Takeda Pharmaceuticals North America, Inc.: Research Funding; Bristol-Meyers Squibb Company: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; LAM Therapeutics: Research Funding; UNUM: Research Funding; Gilead/Kite: Consultancy; Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Genentech, Inc.: Consultancy, Research Funding. Farooq:Kite Pharma: Research Funding; Celgene: Honoraria. Friedberg:Acerta: Other: Data & Safety Monitoring Committee; Bayer: Honoraria, Other: Data & Safety Monitoring Committee. Kahl:Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; BeiGene: Consultancy; TG Therapeutics: Consultancy. Lossos:Janssen Scientific: Membership on an entity's Board of Directors or advisory committees; NIH: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Maurer:Nanostring: Research Funding; Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees. Nastoupil:Spectrum: Honoraria; Genentech, Inc.: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Honoraria, Research Funding; Novartis: Honoraria; TG Therapeutics: Honoraria, Research Funding; Bayer: Honoraria; Celgene: Honoraria, Research Funding. Rutherford:Heron: Consultancy, Honoraria; Janssen Scientific Affairs: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Juno Therapeutics Inc: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Verastem: Consultancy, Honoraria; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees. Flowers:National Cancer Institute: Research Funding; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Bayer: Consultancy; Spectrum: Consultancy; Karyopharm: Consultancy; Acerta: Research Funding; TG Therapeutics: Research Funding; Millenium/Takeda: Research Funding; AstraZeneca: Consultancy; Optimum Rx: Consultancy; V Foundation: Research Funding; Celgene: Consultancy, Research Funding; Burroughs Wellcome Fund: Research Funding; Denovo Biopharma: Consultancy; Gilead: Consultancy, Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding.

AbstractIntroductionFrontotemporal dementia disorders (FTDs) are heterogeneous phenotypical behavioral and language disorders usually associated with frontal and/or temporal lobe degeneration. We investigated their incidence in a population‐based cohort.MethodsUsing a records‐linkage system, we identified all patients with a diagnostic code for dementia in Olmsted County, MN, 1995–2010, and confirmed the diagnosis of FTD. A behavioral neurologist verified the clinical diagnosis and determined phenotypes.ResultsWe identified 35 FTDs cases. Overall, the incidence of FTDs was 4.3/100,000/year (95% CI: 2.9, 5.7). Incidence was higher in men (6.3/100,000, 95% CI 3.6, 9.0) than women (2.9/100,000; 95% CI: 1.3, 4.5); we observed an increased trend over time (B = 0.83, 95% CI: 0.54, 1.11, P < .001). At autopsy, clinical diagnosis was confirmed in eight (72.7%) cases.DiscussionWe observed an increased incidence and trends of FTDs over time. This may reflect a better recognition by clinicians and improvement of clinical criteria and diagnostic tools.