Citations

AbstractBackgroundCertain autoimmune bullous dermatoses are mediated by autoantibodies of the IgG4 subclass. We determined the diagnostic impact of adding IgG4 to our conventional direct immunofluorescence (DIF) panel.MethodsFor all cases submitted to our referral laboratory for DIF over 1 month (n = 630), we performed IgG4 testing and collected consecutive biopsy specimens showing definite or indeterminate linear or cell‐surface deposition of IgG, IgG4, and/or C3. On retrospective blinded review, we classified the pattern and whether the findings were definite, indeterminate, or negative. When present, substantial background staining was recorded.ResultsSeventy DIF specimens met the inclusion criteria. Of 22 (31.4%) specimens equivocal for linear or cell‐surface deposition, 9 (40.9%) had definitive IgG4 findings, either linear (3 of 14 equivocal linear cases; 21.4%) or cell‐surface (6 of 8 equivocal cell‐surface cases; 75.0%). Background deposition was substantial in 14 cases (20.0%) for IgG but in none for C3 or IgG4.ConclusionIgG4 allowed the classification of over 40% of DIF cases that were otherwise equivocal by IgG and C3. IgG4 staining showed lower levels of non‐specific background staining than IgG or C3. IgG4 appears to contribute most value in cases with cell‐surface deposition or with equivocal linear IgG deposition and negative C3 results.

Abstract Background Multiple myeloma (MM) evolves from monoclonal gammopathy of undetermined significance (MGUS), a clinically detectable but asymptomatic premalignant phase seen in ~3% of the general population 50 years of age or older. The prevalence of MGUS has not been described in a population at high risk of developing MM, specifically Black/African American (AA) individuals or first-degree relatives of patients with hematologic malignancies (HM). In 2019, we launched the first nationwide US screening study for individuals at high risk of MM to help better identify what population would benefit most from screening and early intervention for precursor MM stages. We aim to assess the prevalence of MGUS in a population at high risk of MM and characterize clinical variables of individuals who screen positive. Here, we report interim screening data on the first 2,960 participants. Methods Individuals aged 40 or older with an additional MM risk factor are eligible to be screened in the PROMISE Study. High-risk individuals include Black/AAs and those with a first-degree relative diagnosed with a hematologic malignancy or a precursor condition to MM. Blood from all participants was analyzed via serum protein electrophoresis, immunofixation, and Optilite® to measure the serum free light chains (sFLC), IgG, IgA and IgM. Results were returned to all participants, and those who tested positive for a monoclonal gammopathy (MGUS/SMM) were referred to a hematologist for clinical follow-up and invited to periodically complete epidemiologic exposure and psychosocial questionaries, including a 4-item cancer worry questionnaire and the RAND 36-item Short Form Survey (SF-36). To investigate the use of the higher-sensitivity matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) with the Optilite® IgG, IgA, IgM and sFLC results as a screening test for all participants, we rescreened 1,092 samples from PROMISE. The Binding Site Group proprietary software was used for the analysis of the combined MS/Optilite® results, allowing for the detection and quantification of M-protein. Heavy-Chain MGUS (HC-MGUS) was defined by the presence of one or more paired heavy and light chain monoclonal peaks detected by MS. Pairing was based on mass to charge ratio of identified peaks. To enrich the PROMISE cohort with Black/AA individuals, we identified and screened 1,868 Black/AA additional individuals from the Mass General Brigham (MGB) Biobank who met the PROMISE enrollment criteria. Screening was performed by MS/Optilite®, and results have not been returned to participants. Results We screened 2,960 participants with the combined MS/Optilite® approach. We report here the prevalence of HC-MGUS and plan on presenting the estimated rate of light chain MGUS in our cohort, at the meeting. We detected HC-MGUS in 9.6% (95% CI: 8.6-11%) of our cohort, with a prevalence of 10% (95% CI: 8.3-12%) in the PROMISE cohort and 9.4% (95% CI: 8.1-11%) in the MGB cohort (Table 1 and Figure 1). HC-MGUS prevalence increased with age in high-risk individuals from 4.9% (CI: 3.3-6.9%) for participants aged 40-49 to 13% (CI: 10-17%) in the 70-79 range (P < 1.2E-5). Among monoclonal HC-MGUS, we found 65% IgG, 18% IgM, and 18% IgA. M-spike was quantified in 97% of samples. Median M-spike concentration was, 0.058g/dL (max. 2.6g/dL) for IgG, 0.0043g/dL (max. 0.6g/dL) for IgM, and 0.067g/dL (max. 0.8g/dL) for IgA. In the Promise cohort, no significant change in cancer worry was observed across the pre- and post-screening interval among participants who screened positive (P = 0.52). Health-related quality of life, as measured by the SF-36, was not significantly different in screen-positive vs. screen-negative individuals for any of the eight subscales (all P > 0.20). Conclusions We present the largest dataset on monoclonal gammopathy prevalence and screening in individuals at high risk for MM, and more specifically the largest cohort of Black/AA, using a novel high-sensitivity testing approach. Our results confirm that older adults who are Black/AA or have a first-degree relative with an HM have a high prevalence MGUS and may benefit from precision screening approaches to allow for early detection and clinical intervention. Preliminary data on cancer worry and quality of life indicates that the psychosocial burden of screening in this population is likely minimal. Figure 1 Figure 1. Disclosures Sakrikar: The Binding Site: Current Employment. Krause: The Binding Site: Current Employment. Barnidge: The Binding Site: Current Employment. Bustoros: Takeda: Consultancy, Honoraria; Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau. Perkins: The Binding Site: Current Employment. Harding: The Binding Site: Current Employment, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Kapoor: Ichnos Sciences: Research Funding; Amgen: Research Funding; Pharmacyclics: Consultancy; Takeda: Research Funding; Sanofi: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; BeiGene: Consultancy; Sanofi: Research Funding; Karyopharm: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy. Mo: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy; Eli Lilly: Consultancy; Janssen: Honoraria; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees. Murray: The Binding Site: Patents & Royalties: Potential Royalties for use of mass spectrometry in M-protein detection. Getz: Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees; IBM, Pharmacyclics: Research Funding. Marinac: JBF Legal: Consultancy; GRAIL Inc: Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Abstract Introduction: TP53 aberrations, including mutations and deletion of 17p (del17p), are important adverse prognostic markers in chronic lymphocytic leukemia (CLL). Prevalence of TP53 aberrations ranges from 7-11% in untreated CLL and increases with disease progression and treatment. Among CLL patients with TP53 aberrations, co-occurrence of TP53 mutations with del(17p) is common. CLL patients with TP53 mutations or del(17p) have significantly worse outcomes when compared to wild-type patients. Previous studies, focusing on CLL patients at time of treatment, are mixed as to whether a single or more than one TP53 aberration impacts outcomes. TP53 is less well studied in monoclonal B-cell lymphocytosis (MBL), an asymptomatic pre-malignant state of CLL. Del(17p) occurs in 3-4% of MBL individuals, and a study of 54 MBL individuals reported a 2% mutation frequency in TP53. Here we estimated prevalence and evaluated the impact of TP53 aberrations in a large cohort MBL or untreated CLL individuals. Methods : Patients with CLL or MBL diagnosed between 2000 and 2019 from the Mayo Clinic CLL Resource with pre-treatment peripheral blood mononuclear cells (PBMC) collected within two years of diagnosis were considered. DNA was extracted from PBMCs with purity >80% or with sorted CD5+/CD19+ clonal cells. The entire coding regions of 59 CLL driver genes were paired end sequenced. Median coverage depth was >1000x per nucleotide, allowing for detection of mutations with variant allelic fraction (VAF) as low as 1%. Somatic mutations were called using MuTect2 in tumor-only mode, and high impact mutations (frameshift, nonsense, and splicing variants) and missense mutations in CLL hot spots were selected. Somatic mutations and FISH del(17p) were used to define TP53 state for each patient: 1) wild-type [no TP53 mutations and normal del(17p)], 2) single-hit [one TP53 mutation or del(17p)], or 3) multi-hit [multiple TP53 mutations or TP53 mutation and del(17p)]. Time to first treatment (TTFT) and overall survival (OS) were analyzed by TP53 state. TTFT and OS were defined as time from sample collection to first treatment or death, respectively, or last follow-up date. Median TTFT and OS was estimated by the Kaplan-Meier method. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals for TTFT and OS associations. The models were adjusted for known adverse prognostic factors including clinical diagnosis (CLL or MBL), age at diagnosis, Rai stage, b2 microglobulin, and IGHV mutation status. Results: Individuals with CLL (N=597) or MBL (N=285) were analyzed for prevalence of TP53 mutations and del(17p). We found 58 CLL patients (9.7%) and 15 MBL individuals (5.3%) had TP53 mutations. The median VAF in CLL was 30.9% (<10% VAF, n=21) and in MBL was 13.5% (<10% VAF, n=7). Del(17p) was present in 37 patients with CLL (6.2%) and 7 individuals with MBL (2.7%). In total, 86 CLL/MBL patients had a TP53 mutation and/or del(17p): 56.8% (48 patients) were single-hit and 44.2% (38 patients) were multi-hit (Fig. 1a). Patients with any TP53 aberration had shorter TTFT than wild-type patients (median 2.3 vs 9.4 years). Among patients with TP53 aberrations, median TTFT was shorter in multi-hit patients (20 events, 1.8 years) compared to single-hit patients (24 events, 3.2 years) (Fig. 1b). In Cox regression, single-hit (HR = 1.7 [1.1-2.6]) and multi-hit (HR = 1.8 [1.1-2.9]) patients had shorter TTFT compared to wild-type patients after adjusting for covariates (Fig. 1c). Multi-hit patients also had shorter OS compared to wild-type patients, while OS in single-hit patients did not significantly differ from wild-type patients (Fig. 1d). Median OS was 5.5 years in multi-hit patients (22 deaths) compared to 15.1 years in wild-type patients (196 deaths) and 14.3 years in single-hit patients (15 deaths). In the OS model adjusted for covariates, multi-hit patients had a significant increased risk (HR = 2.6 [1.6-4.1]), but single-hit patients did not (HR = 1.4 [0.8-2.5]) compared with wild-type patients (Fig. 1e). OS HRs remained stable after censoring at time of treatment. Both TTFT and OS HRs were consistent when mutations with VAF < 10% were excluded. Conclusions: This study suggests single versus multi-hit TP53 aberrations may be important for prognostic outcomes in untreated CLL and MBL patients. Prognostic metrics may need to consider single versus multi-hit TP53 aberrations and include TP53 mutations with low VAF. Figure 1 Figure 1. Disclosures Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: MEI Pharma: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees.

Abstract Background :COVID-19 adversely affects individuals with cancer. Several studies have found that seroconversion rates among patients with hematologic malignancies are suboptimal when compared to patients without cancer. Among patients with hematologic malignancies, seroconversion rates also appear to be influenced by recent treatment and the type of treatment they have received. Patients with non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) are immunocompromised due to impaired humoral and cellular immunity in addition to prescribed immunosuppressive therapy. Chimeric antigen receptor T-cell (CAR T) therapy is now widely used for NHL and MM, but little is known about seroconversion rates after COVID-19 vaccination among these populations. Current national guidelines recommend COVID-19 vaccination to be offered to CAR T recipients as early as three months thereafter. We retrospectively evaluated SARS-CoV-2 spike-binding IgG antibody levels following COVID-19 vaccination among NHL and MM CAR T therapy recipients. Methods:This retrospective study was conducted at three Mayo Clinic sites on NHL and MM patients that received CAR T infusions from Sept 2016 to June 2021. Baseline characteristics were ascertained from medical records. All NHL and MM patients who had received CAR T at any point and were alive at the time that the COVID-19 vaccine first became available were eligible for inclusion for antibody response evaluation. For antibody response to vaccination, antibody spike values > 0.80 U/mL were considered positive. Results: Out of 104 CAR T infusions, 73 patients are alive at the time of this submission. We have had 7 patients with known COVID-19 pre-CAR T and all 7 are currently alive (5 have antibody titers and 2 have not been tested yet). Nineteen patients developed known COVID infection post-CAR T (13 alive and 6 deceased). The mortality of COVID post-CAR T in our sample was 31.5%. Furthermore, of the 13 patients that survived COVID-19, they received CAR T an average of 416 days prior to COVID-19 infection (median = 337, range = 54 - 1406); the 6 patients who died from COVID-19 had received CAR T an average of 250 days prior to COVID-19 infection (median = 164, range = 7 - 846). All 6 deceased patients did not receive COVID-19 vaccination pre-CAR T. Out of 17 CAR T patients tested for antibody spike titers post COVID-19 vaccination, 76.4% were able to mount an antibody response. More patients with MM had a higher titer response to the vaccine (>250 U/mL) compared to the NHL counterparts (0.80-249 U/mL). All patients that received the vaccine, regardless of antibody response, were alive at the time of this submission. Conclusions:The majority of CAR T recipients with NHL and MM are able to mount an antibody response following COVID-19 vaccination in our relatively small sample. The frequency of seroconversion among CAR T recipients seems to be similar to patients with hematologic malignancy who had received a hematopoietic cell transplant reported elsewhere. These findings are limited by our small sample size and may be influenced by the timing of vaccination relative to CAR T. Furthermore, almost half of our patients received IVIG post CAR T which could potentially cause false positive antibody results as pooled immunoglobulin preparations may contain COVID-19 antibodies from vaccinated healthy donors. To better understand the characteristics of the immunologic response against SARS-CoV-2 in patients post-CAR T, larger multicenter studies exploring both humoral and cellular immunity will be needed. JEWN, MI and JM are co-first authors and PV, HM and AR are co-senior authors. Figure 1 Figure 1. Disclosures Munoz: Physicians' Education Resource: Honoraria; Seattle Genetics: Honoraria; Bayer: Research Funding; Gilead/Kite Pharma: Research Funding; Celgene: Research Funding; Merck: Research Funding; Portola: Research Funding; Incyte: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Research Funding; Janssen: Research Funding; Millennium: Research Funding; Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Pharmacyclics/Abbvie, Bayer, Gilead/Kite Pharma, Pfizer, Janssen, Juno/Celgene, BMS, Kyowa, Alexion, Beigene, Fosunkite, Innovent, Seattle Genetics, Debiopharm, Karyopharm, Genmab, ADC Therapeutics, Epizyme, Beigene, Servier: Consultancy; Targeted Oncology: Honoraria; OncView: Honoraria; Kyowa: Honoraria. Bergsagel: Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; GSK: Consultancy, Honoraria. Wang: Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; InnoCare: Research Funding; Novartis: Research Funding; MorphoSys: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Fonseca: Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy; Amgen: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Mayo Clinic in Arizona: Current Employment; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy. Palmer: Sierra Oncology: Consultancy, Research Funding; CTI BioPharma: Consultancy, Research Funding; Protagonist: Consultancy, Research Funding; Incyte: Research Funding; PharmaEssentia: Research Funding. Dingli: Novartis: Research Funding; GSK: Consultancy; Apellis: Consultancy; Alexion: Consultancy; Sanofi: Consultancy; Janssen: Consultancy. Kapoor: Sanofi: Research Funding; AbbVie: Research Funding; Takeda: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding. Kumar: Roche-Genentech: Consultancy, Research Funding; Oncopeptides: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Merck: Research Funding; Carsgen: Research Funding; KITE: 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, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; Sanofi: Research Funding. Paludo: Karyopharm: Research Funding. Bennani: Kymera: Other: Advisory Board; Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Verastem: Other: Advisory Board. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Lin: Kite, a Gilead Company: Consultancy, Research Funding; Merck: Research Funding; Gamida Cell: Consultancy; Takeda: Research Funding; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Sorrento: Consultancy; Legend: Consultancy; Vineti: Consultancy. Murthy: CRISPR Therapeutics: Research Funding.

Abstract Background: Pts with previously treated R/R aggressive LBCL have compromised health-related QOL (HRQOL). Liso-cel is an autologous, CD19-directed, defined composition, 4-1BB CAR T cell product administered at equal target doses of CD8 + and CD4 + CAR + T cells. In a prespecified interim analysis of TRANSFORM (NCT03575351), a randomized, open-label, pivotal trial, liso-cel demonstrated statistically significant and clinically meaningful improvement in the primary endpoint of event-free survival and key secondary endpoints (complete response rate and progression-free survival) in adults with R/R LBCL after failure of first-line (1L) immunochemotherapy compared with SOC, with no new safety signals. Here we present results of the pt-reported outcomes (PRO) analysis from TRANSFORM. Methods: Adults (age ≤ 75 yrs) with R/R LBCL (≤ 12 mo after 1L therapy), who were eligible for autologous stem cell transplantation (ASCT), were randomized to receive either SOC (3 cycles of salvage chemotherapy [CT] and BEAM + ASCT for responding pts) or liso-cel after lymphodepletion. Crossover to receive liso-cel was allowed in the SOC arm for pts who failed treatment. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire - 30 items (EORTC QLQ-C30) and the Functional Assessment of Cancer Therapy - Lymphoma Subscale (FACT-LymS) were administered at randomization (baseline) and on Days 29 (infusion of liso-cel or 2 cycles of salvage CT), 64 (1 mo post liso-cel or completion of CT), 126 (3 mos post liso-cel or 2 mos post ASCT), and Mo 6 and other prespecified timepoints up to Mo 36 or end of study. No PRO data were collected after crossover. The analysis was based on the PRO-evaluable population (pts with a baseline and ≥ 1 post-baseline assessment). Predefined thresholds determined clinically meaningful changes. Global health/QOL (GH/QOL), physical functioning, cognitive functioning, fatigue, pain, and FACT-LymS were the primary domains of interest based on their relevance to the study population and treatment. A linear mixed model for repeated measures (MMRM) analysis was performed to assess the between-treatment difference in overall least squares (LS) mean change from baseline for each primary domain, using data collected up to Day 126 for visits with a sample size per arm ≥ 10. Proportions of pts with meaningful change from baseline were assessed for each primary domain up to Mo 6. All analyses were descriptive only. Results: Of 184 randomized pts, 90 (49%) and 85 (46%), respectively, were included in the PRO-evaluable population for the EORTC QLQ-C30 (SOC vs liso-cel n=43 vs 47) and FACT-LymS (n=40 vs 45, respectively). The PRO assessment completion rate from baseline up to Mo 6 was ≥ 45%, which was lower than expected primarily due to operational challenges during the COVID-19 pandemic but was comparable for both arms. In the MMRM analysis, the liso-cel arm had more favorable overall LS mean changes from baseline to Day 126 than the SOC arm in most of the EORTC QLQ-C30 domains and FACT-LymS. In particular, the between-treatment differences for cognitive functioning (−2.09 vs 2.21) and fatigue (3.75 vs −1.95) for SOC versus liso-cel, respectively, exceeded the prespecified minimal important difference threshold (Table); in those domains, the SOC arm deteriorated while the liso-cel arm improved. In individual-level analyses, the proportion of pts with meaningful improvement for fatigue and GH/QOL was higher, while deterioration was lower, in the liso-cel arm versus SOC arm from baseline up to Mo 6 (Figure). At Mo 6, a higher proportion of pts experienced worsened fatigue (71% vs 18%) and a lower proportion experienced improved fatigue (29% vs 47%) in the SOC arm compared with the liso-cel arm; for GH/QOL, a higher proportion of pts worsened (57% vs 18%) and lower proportion improved (14% vs 53%), respectively. For the other primary domains, the proportions of pts with improvement or deterioration favored liso-cel or were similar between arms. Conclusions: Compared with SOC, liso-cel showed favorable improvement in most primary PRO domains, particularly EORTC QLQ-C30 cognitive functioning and fatigue and more pts showed PRO improvements and fewer showed deterioration by Mo 6 with liso-cel. The results were achieved despite only responders remaining in the SOC arm after salvage CT. HRQOL was either improved or maintained after liso-cel treatment in pts with R/R LBCL after failure of 1L therapy. Figure 1 Figure 1. Disclosures Abramson: Bristol-Myers Squibb Company: Consultancy, Research Funding; Morphosys: Consultancy; C4 Therapeutics: Consultancy; Kite Pharma: Consultancy; Kymera: Consultancy; Incyte Corporation: Consultancy; Bluebird Bio: Consultancy; Astra-Zeneca: Consultancy; Allogene Therapeutics: Consultancy; Novartis: Consultancy; EMD Serono: Consultancy; Genmab: Consultancy; Seagen Inc.: Research Funding; AbbVie: Consultancy; Karyopharm: Consultancy; Genentech: Consultancy; BeiGene: Consultancy. Arnason: Juno/BMS: Honoraria. Glass: BMS: Consultancy; Roche: Consultancy, Research Funding, Speakers Bureau; Riemser: Research Funding; Kite: Consultancy; Novartis: Consultancy; Helios Klinik Berlin-Buch: Current Employment. Crotta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Montheard: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Previtali: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Liu: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Braverman: BMS: Current Employment, Current equity holder in publicly-traded company. Guo: Daiichi Sankyo: Consultancy; UCB: Consultancy; Janssen: Consultancy; Gilead: Consultancy; Bristol Myers Squibb: Consultancy; EMD Serono: Consultancy; Evidera: Current Employment. Shi: Bristol Myers Squibb: Consultancy. Kamdar: ADC Therapeutics: Consultancy; Adaptive Biotechnologies: Consultancy; TG Therapeutics: Research Funding; Genentech: Research Funding; AbbVie: Consultancy; KaryoPharm: Consultancy; Kite: Consultancy; AstraZeneca: Consultancy; SeaGen: Speakers Bureau; Celgene: Other; Genetech: Other; Celgene (BMS): Consultancy.

Abstract Introduction: Chronic lymphocytic leukemia (CLL) is characterized by multiple copy number alterations (CNA) and mutations that are central to disease pathogenesis, prognosis, risk-stratification, and identification of response or resistance to therapies. Fluorescence in situ hybridization (FISH) is gold standard in the clinical laboratory for detecting prognostic CNAs in CLL (e.g. deletion 17p13 (del(17p), deletion 11q23 (del(11q), deletion 13q14 (del(13q), and trisomy 12). Most clinical FISH assays have high specificity and sensitivity, but the technique can detect a limited number of alterations per assay. Importantly, next-generation sequencing (NGS) techniques have become more readily available for clinical applications and are increasingly being used for screening not only mutations, but also copy number abnormalities in multiple genes and chromosomal regions of interest in hematologic malignancies. Here, we evaluated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using a custom targeted NGS assay for detecting common prognostic chromosomal alterations in CLL and high-count monoclonal B-cell lymphocytosis (MBL), the precursor to CLL. Methods : We designed a SureSelect DNA targeted sequencing panel, covering all exons of 59 recurrently CLL mutated genes and additional amplicons across regions affected by clinically relevant CNAs. All CLL (N=534) and MBL (N=162) patients had pre-treatment peripheral blood mononuclear cells (PBMC) collected within two years of diagnosis. DNA was extracted in cases with purity >80% of CD5+/CD19+ cells. Clinical FISH data was available within 100 days of NGS in all untreated CLL and MBL cases. PatternCNV was used to detect clinically relevant CNAs in chromosomes 11, 12, 13 and 17. We performed a principal component analysis on the CNA calls, excluding chromosomes 11, 12, 13, and 17 to identify clusters of samples. Each cluster was then independently rerun with PatternCNV and the results from chromosomes 11, 12, 13, and 17 were extracted and further analyzed. We excluded samples with low tumor metrics identified by FISH (less than 20% of cells with del(17p), del(11q), trisomy 12 and del(13q)). Results: We sequenced a total of 696 patients of whom 162 were MBL and 534 were untreated CLL. The most commonly mutated genes were NOTCH1 (11.0%), TP53 (8.7%), SF3B1 (7.7%), ATM (4.1%), and CHD2 (3.8%). Based on CNA analyses from the NGS data, we identified 59 (9.1%) individuals with del(17p), 88 (13.4%) individuals with del(11q), 128 (20.0%) individuals with trisomy 12, and 329 (53.0%) individuals with del(13q). All 696 individuals had FISH panels conducted, with 39 (5.6%) individuals with del(17p), 68 (9.8%) individuals with (11q), 119 (17.1%) with trisomy 12, and 295 (42.4%) with del(13q). When we compared our CNA analyses with the FISH data, we found high concordance 95.0% for del(17p), 92.7% del(11p), 94.3% for trisomy 12, and 88.2% for del(13q). For del(17p) we found a sensitivity of 93.9%, specificity of 95.4%, PPV of 52.5%, and NPV of 99.7%. Del(11q) revealed a sensitivity of 88.1%, specificity of 94.0%, PPV of 59.1%, and NPV 98.8%. We found a sensitivity of 93.8%, specificity of 95.6%, PPV 82.0%, and NPV of 98.6% for trisomy 12 and for del(13q) we found a sensitivity of 92.6%, specificity of 90.9%, PPV of 91.7%, and NPV of 93.8%. We found lower PPVs in del(17p) and del(11q) likely due to lower prevalence of these chromosomal abnormalities. Conclusion: Here we show a high sensitivity, specificity, and NPV when comparing targeted sequencing with FISH. FISH panel testing is widely used in clinical practice to characterize highly prognostic chromosomal abnormalities in CLL. Comprehensive genetic profiling with NGS has become increasingly important in the work up of hematologic malignancies and provides additional prognostic and predictive information, including clinically relevant mutations such as TP53, SF3B1, and NOTCH1, tumor mutation load and mutations associated with resistance to chemo-immunotherapy and targeted therapies, such as BTK or BCL2 inhibitors, that FISH cannot offer. We show that NGS can infer clinically relevant CNA in cases without FISH testing while also providing additional clinically relevant information. Figure 1 Figure 1. Disclosures Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: Genentech: Research Funding; MEI Pharma: Research Funding; Sunesis: Research Funding; Acerta Pharma: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees.

Abstract BACKGROUND Validation of the 2016 LANO MRI scorecard for leptomeningeal metastasis failed for multiple reasons. The objective of this joint EORTC Brain Tumor Group and RANO effort was to validate the feasibility of the revised MRI scorecard for assessing response in leptomeningeal metastasis. METHODS Coded paired cerebrospinal MRI of 20 patients with leptomeningeal metastases from solid cancers at baseline and follow-up after treatment and instructions for assessment were provided via the EORTC imaging platform. The kappa coefficient (K) was used to evaluate inter-observer pairwise agreement. Statistical analyses were performed using SAS V9.4 software (Cary, NC). The sponsor of the study was the University Hospital Zurich (2018-00192). RESULTS Thirty-five raters participated, including 9 neuroradiologists, 17 neurologists, 4 radiation oncologists, 3 neurosurgeons and 2 medical oncologists. Among leptomeningeal metastases-related items at baseline, the best median concordance was noted for hydrocephalus (K=0.63), and the worst median for spinal linear enhancing disease (K=0.46). The median concordance for overall response was moderate (K=0.44). Notably, the interobserver agreement for the presence of parenchymal brain metastases at baseline was minimal (K=0.29). Significant differences were observed when considering the specialty of the raters. Only 394 of 700 ratings (56%) were fully completed. Among 394 fully completed ratings, perfect concordance was noted in 293 ratings (74%) when comparing the overall response according to the guidelines provided in the scorecard and the overall response provided by the raters. The main discordances were noted for partial response according to the rater versus stable disease according to the guidelines (n=44), followed by progression according to the raters versus stable disease according to the guidelines (n=23). CONCLUSION Electronic case report forms with "blocking solutions" are probably required to enforce completeness and quality of scoring. These results confirm the necessity of central review and the need for training of MRI assessment in clinical trials.

Abstract The number of patients with primary cutaneous lymphoma (PCL) relative to other non-Hodgkin lymphomas (NHLs) is small and the number of subtypes large. Although clinical trial guidelines have been published for mycosis fungoides/Sézary syndrome, the most common type of PCL, none exist for the other PCLs. In addition, staging of the PCLs has been evolving based on new data on potential prognostic factors, diagnosis, and assessment methods of both skin and extracutaneous disease and a desire to align the latter with the Lugano guidelines for all NHLs. The International Society for Cutaneous Lymphomas (ISCL), the United States Cutaneous LymphomaConsortium (USCLC), and the Cutaneous Lymphoma Task Force of the European Organization for the Research and Treatment of Cancer (EORTC) now propose updated staging and guidelines for the study design, assessment, endpoints, and response criteria in clinical trials for all the PCLs in alignment with that of the Lugano guidelines. These recommendations provide standardized methodology that should facilitate planning and regulatory approval of new treatments for these lymphomas worldwide, encourage cooperative investigator-initiated trials, and help to assess the comparative efficacy of therapeutic agents tested across sites and studies.

OBJECTIVE To describe the impact of obesity on disease severity and outcomes of coronavirus disease 2019 (COVID-19) among hospitalized children. METHODS This retrospective cohort study from the Society of Critical Care Medicine Viral Respiratory Illness Universal Study registry included all children hospitalized with COVID-19 from March 2020 to January 2021. Obesity was defined by Centers for Disease Control and Prevention BMI or World Health Organization weight for length criteria. Critical illness definition was adapted from National Institutes of Health criteria of critical COVID. Multivariate mixed logistic and linear regression was performed to calculate the adjusted odds ratio of critical illness and the adjusted impact of obesity on hospital length of stay. RESULTS Data from 795 patients (96.4% United States) from 45 sites were analyzed, including 251 (31.5%) with obesity and 544 (68.5%) without. A higher proportion of patients with obesity were adolescents, of Hispanic ethnicity, and had other comorbidities. Those with obesity were also more likely to be diagnosed with multisystem inflammatory syndrome in children (35.7% vs 28.1%, P = .04) and had higher ICU admission rates (57% vs 44%, P < .01) with more critical illness (30.3% vs 18.3%, P < .01). Obesity had more impact on acute COVID-19 severity than on multisystem inflammatory syndrome in children presentation. The adjusted odds ratio for critical illness with obesity was 3.11 (95% confidence interval: 1.8–5.3). Patients with obesity had longer adjusted length of stay (exponentiated parameter estimate 1.3; 95% confidence interval: 1.1–1.5) compared with patients without obesity but did not have increased mortality risk due to COVID-19 (2.4% vs 1.5%, P = .38). CONCLUSION In a large, multicenter cohort, a high proportion of hospitalized children from COVID-19 had obesity as comorbidity. Furthermore, obesity had a significant independent association with critical illness.

Introduction: Retinal imaging is a non-invasive tool to study both retinal vasculature and neurodegeneration. In this exploratory retinal curcumin-fluorescence imaging (RFI) study, we sought to determine whether retinal vascular features combined with retinal amyloid burden correlate with the neurocognitive status. Methods: We used quantitative RFI in a cohort of patients with cognitive impairment to automatically compute retinal amyloid burden. Retinal blood vessels were segmented, and the vessel tortuosity index (VTI), inflection index, and branching angle were quantified. We assessed the correlations between retinal vascular and amyloid parameters, and cognitive domain Z-scores using linear regression models. Results: Thirty-four subjects were enrolled and twenty-nine (55% female, mean age 64 ± 6 years) were included in the combined retinal amyloid and vascular analysis. Eleven subjects had normal cognition and 18 had impaired cognition. Retinal VTI was discriminated among cognitive scores. The combined proximal mid-periphery amyloid count and venous VTI index exhibited significant differences between cognitively impaired and cognitively normal subjects (0.49 ± 1.1 vs. 0.91 ± 1.4, p = 0.006), and correlated with both the Wechsler Memory Scale-IV and SF-36 mental component score Z-scores (p < 0.05). Conclusion: This pilot study showed that retinal venular VTI combined with the proximal mid-periphery amyloid count could predict verbal memory loss. Future research is needed to finesse the clinical application of this retinal imaging-based technology.