Lin, Yi

Abstract Overall Survival estimates from diagnosis are valuable for guiding treatment, but do not consider the years already survived. Conditional survival (CS) provides dynamic survival predictions over time. This study was conducted to estimate CS at 1–8 years from diagnosis and the impact of baseline prognostic factors on CS in multiple myeloma (MM) patients. This is a retrospective study including 2556 MM patients diagnosed between 2004–2019. CS (t|s) was defined as the probability of surviving t years given survival of s years. Median age was 64 years. Median follow-up was 6.2 years and median overall survival from diagnosis was 7.5 years. The 5-year CS estimates at s = 0, 1, 2, 3, and 5 years were 0.64, 0.61, 0.61, 0.61, and 0.58, respectively. On multivariate analysis, age ≥ 65 and proteasome inhibitor + immunomodulatory-based induction were associated with decreased survival and increased survival, respectively, retained at 5 years. The adverse impact of 1q gain/amplification, high-risk IgH translocation, and ISS-3 was significant at 1 and 3 years but not 5 years. Chromosome 17 abnormality was associated with decreased survival only at 1 year. Among MM patients, 5-year CS was stable at 1–5 years from diagnosis. The prognostic impact of high-risk cytogenetic factors decreased with additional years survived.

PURPOSE:High-dose methotrexate (HDMTX; > 500 mg/m2) is an important component of lymphoma therapy. Serum MTX monitoring at 48 hours is the standard approach to identify those at increased risk of developing MTX toxicity. Our aim was to characterize the incidence of complications and their association with MTX levels.METHODS:A retrospective review of our institutional electronic medical record was conducted to identify patients with lymphoma who received HDMTX between January 1, 2002, and December 31, 2018. We characterized the incidence of acute kidney injury (AKI), intensive care unit (ICU) admission, length of hospital stay (LOS), and 30-day mortality across 48-hour MTX levels. To establish an association between 48-hour MTX levels and the complications listed, we performed chi-square analysis for dichotomous variables and Kruskal-Wallis for nonparametric data. Receiver operator characteristic curve analysis was performed to identify the MTX level where AKI grade ≥ 2 was more likely. Multivariate logistic regression analysis was performed to identify risk factors for this MTX level.RESULTS:We identified 642 patients with 2,804 cycles of HDMTX. The incidence of AKI was 19.1% with AKI grade ≥ 2 making up 21% of cases. Rates of AKI, ICU admission, and 30-day mortality are associated with elevated 48-hour MTX levels. There was a significant increase in median LOS with elevated MTX levels ( P < .001). Receiver operator characteristic curve analysis for AKI grade ≥ 2 demonstrated a 48-hour MTX level threshold of 1.28 μmol/L. Multivariate logistic regression analysis revealed age, male sex, elevated body surface area, higher MTX dose, monotherapy, and first cycle as independent factors.CONCLUSION:Elevated MTX levels are associated with a significant increased rate of AKI, ICU admission, prolonged LOS, and 30-day mortality. Elevated 48-hour MTX levels, particularly > 1.28 μmol/L, should alert clinicians for complications and to initiate measures to reduce MTX levels.

AbstractPatients with multiple myeloma (MM) have a lower efficacy from COVID‐19 vaccination and a high rate of mortality from COVID‐19 in hospitalized patients. However, the overall rate and severity of COVID‐19 infection in all settings (including non‐hospitalized patients) and the independent impact of plasma cell‐directed therapies on outcomes needs further study. We reviewed the medical records of 9225 patients with MM or AL amyloidosis (AL) seen at Mayo Clinic Rochester, Arizona, and Florida between 12/01/2019 and 8/31/2021 and identified 187 patients with a COVID‐19 infection (n = 174 MM, n = 13 AL). The infection rate in our cohort was relatively low at 2% but one‐fourth of the COVID‐19 infections were severe. Nineteen (10%) patients required intensive care unit (ICU) admission and 5 (3%) patients required mechanical ventilation. The mortality rate among hospitalized patients with COVID‐19 was 22% (16/72 patients). Among patients that were fully vaccinated at the time of infection (n = 12), two (17%) developed severe COVID‐19 infection, without any COVID‐related death. On multivariable analysis, treatment with CD38 antibody within 6 months of COVID‐19 infection [Risk ratio (RR) 3.6 (95% CI: 1.2, 10.5), p = .02], cardiac [RR 4.1 (95% CI: 1.3, 12.4), p = .014] or pulmonary comorbidities [RR 3.6 (95% CI 1.1, 11.6); p = .029] were independent predictors for ICU admission. Cardiac comorbidity [RR 2.6 (95% CI: 1.1, 6.5), p = .038] was an independent predictor of mortality whereas MM/AL in remission was associated with lower mortality [RR 0.4 (95% CI: 0.2–0.8); p = .008].

Two Letters to Blood address the risks of COVID-19 in populations with precursors of hematological disease. In the first article, Miller and colleagues report on whether clonal hematopoiesis of intermediate potential (CHIP) is associated with adverse outcomes with COVID-19, finding no association between CHIP and 28-day mortality while providing data indirectly linking IL-6 signaling and patient outcomes. In the second article, Ho and colleagues investigate the outcomes of patients with monoclonal gammopathy of undetermined significance (MGUS) with COVID-19, reporting that one-fourth had a severe infection and that on multivariable analysis, adverse outcomes are more likely if immunoparesis is present.

Abstract Background: ZUMA-1 is a pivotal, multicenter trial of axi-cel, an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy, for the treatment of patients with refractory, aggressive NHL. The objective response rate (ORR) was 82% with a 54% rate of complete response and 44% of responses were ongoing at the time of the primary analysis (Locke et al. AACR 2017. #9986). Grade ≥ 3 cytokine release syndrome (CRS) and neurologic events (NE) occurred in 13% and 28% of patients, respectively. A safety expansion cohort was added to further characterize mechanisms underlying CRS and NE associated with CAR T cell therapy and to evaluate the impact of prophylactic use of tocilizumab and levetiracetam on the rates of these adverse events (AEs). Methods: Patients (≥ 18 years) must have had an Eastern Cooperative Oncology Group performance status of 0-1 and refractory or relapsed transplant ineligible disease. Patients received low-dose conditioning of 500 mg/m2 cyclophosphamide and 30 mg/m2 fludarabine for 3 days followed by axi-cel at a target dose of 2 × 106 CAR T cells/kg. Patients also received prophylactic treatment with 750 mg of levetiracetam twice a day on day 0 and 8 mg/kg of tocilizumab on day 2 post axi-cel infusion. To evaluate the mechanisms of NE, paired serum and cerebrospinal fluid (CSF) were obtained for all patients prior to conditioning chemotherapy and after axi-cel infusion (day 5). Results: As of April 26, 2017, 31 patients received axi-cel. Median age was 51 years (range, 21-74), 52% were male, 65% had stage III-IV disease, 74% were refractory to ≥ second-line therapy, and 19% relapsed ≤ 12 months after autologous stem cell transplant. Most patients (97%) experienced at least 1 grade ≥ 3 AE. The most common grade ≥ 3 AEs were neutropenia/neutrophil count decreased (71%), anemia (55%), thrombocytopenia/platelet count decreased (52%), leukopenia/white blood cell count decreased (35%), febrile neutropenia (29%), encephalopathy (23%), and hypotension (23%). One patient (3%) experienced a grade ≥ 3 (grade 4) CRS. Grade 3 and 4 NE occurred in 29% and 6% of patients, respectively. One patient died of cerebral edema; there were no other deaths due to AE. Updated efficacy, safety, subgroups, and paired blood/serum/CSF biomarker associative analyses will be presented. Conclusions : Early use of tocilizumab may reduce the incidence of severe CRS but not NE in patients treated with CAR T cell therapy. These data provide evidence that the underlying pathophysiology of NE may differ from that of CRS. Understanding the mechanisms of NE may help to further improve the benefit:risk profile for CAR T cell therapy. Drs Locke and Neelapu contributed equally to this work. Disclosures Locke: Kite Pharma: Consultancy; Cellular Biomedicine Group Inc: Consultancy. Neelapu: Kite Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Poseida: Research Funding; Cellectis: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Jacobson: Pharmacyclics, LLC: Consultancy; Kite Pharma: Consultancy. Braunschweig: Kite Pharma: Equity Ownership. Oluwole: Kite Pharma: Consultancy. Siddiqi: Seattle Genetics: Speakers Bureau; Juno: Other: Steering committee for JCAR017; Pharmacyclics, an AbbVie Company: Other: Steering committee for ibrutinib, Speakers Bureau. Timmerman: Celgene: Consultancy; Seattle Genetics: Consultancy; Kite Pharma: Research Funding; ImmuneGene: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Genmab: Consultancy, Equity Ownership. Reagan: Seattle Genetics: Research Funding. Bot: Kite Pharma: Employment, Equity Ownership. Rossi: Kite Pharma: Employment, Equity Ownership. Sherman: Kite Pharma: Employment, Equity Ownership. Navale: Kite Pharma: Employment, Equity Ownership. Jiang: Kite Pharma: Employment, Equity Ownership. Aycock: Kite Pharma: Employment, Equity Ownership. Elias: Kite Pharma: Employment, Equity Ownership. Wiezorek: Kite Pharma: Employment, Equity Ownership. Go: Kite Pharma: Employment, Equity Ownership. Miklos: Pharmacyclics, LLC: Consultancy, Other: Travel expenses, Patents & Royalties, Research Funding; Kite Pharma: Consultancy, Other: Travel expenses, Research Funding; Adaptive Biotechnologies: Consultancy, Other: Travel expenses; Roche: Research Funding; Genentech: Research Funding; Novartis: Research Funding; Janssen: Consultancy, Honoraria, Other: Travel expenses; Sanofi: Honoraria.