Prospective Study Of An Emergency Department Febrile Neutropenia Pathway In Patients With Hematologic Malignancies

Abstract Background Febrile neutropenia (FN) is an oncologic emergency associated with high morbidity and mortality, particularly in patients (pts) with hematologic malignancies. Delays in antibiotic administration, which can occur in busy emergency departments (EDs), lead to worse outcomes. We instituted a FN pathway (FNP) in the Cleveland Clinic (CC) ED to reduce antibiotic delays. Methods This prospective study comparing patients from 06/12 - 06/13 to historical pts from 02/10 - 05/12, represented a collaboration among cancer center, ED, infectious disease, pharmacy, and electronic medical record representatives. Fever was defined as temperature >38°C either at home or in the ED, while neutropenia as absolute neutrophil count <0.5 x 109/L. All CC cancer pts received a special “Neutropenic Risk Hospital Medical Alert Card,” which they presented upon CC ED registration with fever. The pathway formally recognized “fever with a history of cancer” to be a distinct chief complaint and FN to be categorized as Emergency Severity Index level 2 (equivalent to stroke or myocardial infarction) for immediate triage and care. ED-specific electronic FN order sets were created to facilitate antibiotic, laboratory, and blood culture ordering, with antibiotics administered prior to return of neutrophil count. The primary goal of the FNP is administration of empiric broad-spectrum antibiotics within 120 minutes of ED presentation, per Infectious Diseases Society of America guidelines; and the primary outcomes measured were time intervals related to it, e.g. time to blood draw, physician assessment, and antibiotic order/administration. Group comparisons were made using the chi-square, Kruskal-Wallis, Wilcoxon rank-sum, and log rank tests, as appropriate. All reported times were from ED registration. Results In total, 137 consecutive FN episodes in 115 pts with hematologic malignancies occurred during the 12 month study period, 63 episodes in 44 pts in the historical cohort. All pts were triaged and treated using the ED FNP, but use of the specific FN order set was variable: episodes were thus classified as treated per the order set (n=53) or not (n=84 – pts still received antibiotics, but not necessarily per the order set). Overall 60% of pts (n=89) were male and the median age at the time of first ED encounter was 59 years (range 20-88). Cancers were: non-Hodgkin lymphoma (38%), acute myeloid leukemia (21%), other leukemias (15%), and myelodysplastic syndromes (8%). Compared to historical pts, FNP study pts had a higher median ANC (2.0 vs. 0.2, p<0.0001), were less likely to be on growth factors (26% vs. 41%, p=0.06) and more likely to have received prophylactic antibiotics (55% vs. 35%, p=0.006). For the outcome of interest, FNP study pts had significantly shorter time to having blood drawn (median 38.5 vs. 70 minutes, p<0.0001), seeing a doctor (median 44 vs. 71 minutes, p=0.0002) and to receiving antibiotics (median 79 vs. 228 minutes, p<0.0001). Time to admission was also shorter for FNP study pts (4.2 vs. 6.0 hours, p<0.0001), though study pts were less likely to be admitted than historical controls (83% vs. 97%, p=0.005). For FNP pts admitted to the hospital, there was a non-significant decrease in length of stay (median 3.8 vs 4.6 days, p=0.28), ICU admission (7% versus 11%, p=0.26), and length of ICU stay (median 1.9 vs 2.3 days, p=0.83) compared to historical controls. Comparing the two FNP groups treated or not treated per the order set, those treated using the order set had shorter times to antibiotics being ordered (median 28.0 vs. 60.5 minutes, p0.28). Conclusion The FNP significantly decreased time from ED registration to all set time-points, including time to antibiotics by almost three-fold, compared to historical controls in pts with hematologic malignancies. Rate of hospitalization was significantly lower, and ICU and length of stay numerically lower. The FNP is an effective clinical tool to provide prompt antibiotic administration to FN pts and likely represents a significant mechanism for improved outcomes and cost-savings to patients with hematologic malignancies presenting with FN. Disclosures: No relevant conflicts of interest to declare

The Evaluation and Treatment (Tx) of Burkitt Lymphoma (BL) in the Modern Era: Real World (RW) Outcomes and Prognostication across 26 US Cancer Centers (CC)

Introduction: Historically, outcomes for BL have improved in adults using dose intensive chemotherapy regimens and early CNS prophylaxis. More recent data using a less intensive regimen, DA-EPOCH, have been reported. We analyzed detailed patient (pt) & disease characteristics and treatment patterns across 26 US CCs over a recent 9 year (yr) period and also determined survival rates & prognostication. Methods: We conducted a large multicenter retrospective study of newly diagnosed (dx) adult BL pts (6/2009 - 6/2018). Dx was established by institutional expert pathology review; all cases were verified for BL based on 2016 WHO criteria (high grade B cell lymphoma, BL like, etc were excluded). Survival rates were estimated by Kaplan-Meier with differences assessed by log rank test. Univariate (UVA) associations were derived via Cox model with variables P ≤0.05 entered stepwise into a multivariate (MVA) model. Using significant factors from the MVA, a prognostic survival model was constructed. Results: Among N=557 verified BL cases, clinical features included: median age 47 yrs (17-88 yrs; 24% ≥60 yrs); male 76%; HIV+ 22%; ECOG PS 0/1 76%; B symptoms 51%; elevated LDH 78% (3, 5, & 10x elevation: 44%, 29% & 15%, respectively); hemoglobin 1 EN 43%; and 76% stage 3-4 disease (10% stage 1). Additionally, 16% and 3% of pts had baseline leptomeningeal (CSF or cranial nerve palsy) or parenchymal CNS involvement, respectively (see Zayac A et al. ASH 2019 for details). For MYC partner, 68% had t(8;14), 4% light chain, 5% negative FISH (otherwise classic BL) and 23% + break apart probe. HIV+ pts had several clinical differences: CSF+ 23% vs 12% P=0.003; CNS 19% vs 8% P1 EN 60% vs 38% P3x normal (Fig 1B/C). Notably, survival rates were not different based on HIV status (Fig 1D) or by the 3 most common Tx regimens (Fig 1E). However, there were important Tx differences based on presence of CNS involvement (see Zayac A et al. ASH 2019). Additionally, use of rituximab was associated with improved PFS & OS (Fig 1F), while outcomes were similar whether rituximab was given inpt vs outpatient (inpt PFS HR 1.25, P=0.19). Furthermore, Tx at an academic CC was associated with improved outcomes, which persisted on MVA (PFS HR 0.54, 95%CI 0.33-0.88 P=0.01; OS HR 0.50, 95%CI 0.29-0.87 P=0.01) & achievement of initial CR was strongly prognostic (Fig 1G). Baseline factors significant on UVA for PFS & OS were: age ≥40 yrs; PS 2-4; LDH >3x; anemia, low albumin; BM involvement; Stage 3-4; CSF+; & >1 EN. On MVA, factors associated with inferior survival were: age ≥40 yrs (PFS HR 1.57, P3x (PFS HR 2.28, P<0.0001; OS HR 1.96, P<0.0001). Collectively, these factors yielded a BL survival model (Fig 1H/I). Conclusions: Outcomes for adult BL in this contemporary, large, multicenter RW analysis appear inferior to smaller published series. Interestingly, despite increased adverse prognostic factors, survival rates appeared similar in HIV+ pts. In addition, use of rituximab, achievement of initial CR, and Tx at an academic CC were associated with improved survival. Finally, a novel BL-specific survival model identified pts with markedly divergent outcomes. Disclosures Evens: Seattle Genetics: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria; Tesaro: Research Funding; Verastem: Consultancy, Honoraria. Danilov:Janssen: Consultancy; Seattle Genetics: Consultancy; MEI: Research Funding; Abbvie: Consultancy; Pharmacyclics: Consultancy; Takeda Oncology: Research Funding; Janssen: Consultancy; TG Therapeutics: Consultancy; Curis: Consultancy; Pharmacyclics: Consultancy; Aptose Biosciences: Research Funding; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; AstraZeneca: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Bayer Oncology: Consultancy, Research Funding; Celgene: Consultancy; Bristol-Meyers Squibb: Research Funding; MEI: Research Funding; Gilead Sciences: Consultancy, Research Funding; Abbvie: Consultancy; Bristol-Meyers Squibb: Research Funding. Reddy:KITE Pharma: Consultancy; BMS: Consultancy, Research Funding; Celgene: Consultancy; Genentech: Research Funding; Abbvie: Consultancy. Farooq:Celgene: Honoraria; Kite Pharma: Research Funding. Khan:Janssen: Other: Educational Content/Symposium; Abbvie: Membership on an entity's Board of Directors or advisory committees; Bristol Myers: Other: Research Funds; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Yazdy:Genentech: Research Funding; Bayer: Honoraria; Abbvie: Consultancy; Octapharma: Consultancy. Karmali:Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau; Astrazeneca: Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution. Martin:Janssen: Consultancy; Teneobio: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy. Diefenbach:LAM Therapeutics: Research Funding; Incyte: Research Funding; Genentech: Consultancy, Research Funding; Trillium: Research Funding; Millenium/Takeda: Research Funding; Seattle Genetics: Consultancy, Research Funding; Merck: Consultancy, Research Funding; MEI: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Denovo: Research Funding. Epperla:Pharmacyclics: Honoraria; Verastem Oncology: Speakers Bureau. Feldman:Eisai: Research Funding; Amgen: Research Funding; Cell Medica: Research Funding; Roche: Research Funding; Corvus: Research Funding; Kyowa Hakko Kirin: Research Funding; Pfizer: Research Funding; Trillium: Research Funding; Viracta: Research Funding; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Other: Travel expenses, Speakers Bureau; AbbVie: Honoraria, Other: Travel expenses, Speakers Bureau; Pharmacyclics: Honoraria, Other: Travel expenses, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Kite Pharma: Honoraria, Other: Travel expenses, Speakers Bureau; Portola Pharma: Research Funding; Roche: Research Funding. 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. Naik:Celgene: Other: Advisory board. Kamdar:Celgene: Consultancy; AstraZeneca: Consultancy; Seattle Genetics: Speakers Bureau; University of Colorado: Employment; Pharmacyclics: Consultancy. Portell:AbbVie: Research Funding; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy, Research Funding; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding; TG Therapeutics: Research Funding; Xencor: Research Funding; Roche/Genentech: Research Funding; Infinity: Research Funding; Amgen: Consultancy. Olszewski:Spectrum Pharmaceuticals: Research Funding; TG Therapeutics: Research Funding; Genentech: Research Funding; Adaptive Biotechnologies: Research Funding. Alderuccio:Agios: Other: Immediate family member; Puma Biotechnology: Other: Immediate family member; Foundation Medicine: Other: Immediate family member; Targeted Oncology: Honoraria; Inovio Pharmaceuticals: Other: Immediate family member; OncLive: Consultancy

Outcomes of Patients with Newly-Diagnosed Burkitt Lymphoma (BL) and Central Nervous System (CNS) Involvement Treated in the Modern Era: A Multi-Institutional Real-World Analysis

Background: BL is associated with a high risk of primary or secondary CNS involvement, warranting intrathecal (IT) and/or systemic therapy that penetrates the blood-brain barrier (BBB). The lower-intensity DA-EPOCH-R regimen has recently shown high survival rates in BL (Dunleavy, NEJM 2013), but it omits drugs traditionally used for CNS prophylaxis (like high-dose methotrexate [HDMTX]). The objective of this multi-institutional retrospective study was to examine treatments, risk factors, and CNS-related outcomes among patients (pts) with BL. Methods: We collected data from 26 US centers on adult BL pts diagnosed (dx) in 6/2009-6/2018. Using institutional expert pathology review and 2016 WHO criteria, we excluded other high-grade lymphomas (including BL-like/unclassifiable), or cases with inadequate clinicopathologic data. We studied factors associated with baseline CNS involvement (CNSinv) using logistic regression reporting odds ratios (OR). Progression-free (PFS), overall survival (OS), and cumulative incidence function of CNS recurrence (in a competing risk analysis) were examined in Cox or Fine-Gray models reporting hazard (HR) or subhazard ratios (SHR), respectively. All estimates report 95% confidence intervals (in square brackets). Results: Among 557 BL pts (median age, 47 years [yr], 24% women, 23% HIV+), 107 (19%) had CNSinv at dx, including 89 (16%) with leptomeningeal, and 15 (3%) with parenchymal CNS disease. In a multivariable model, factors significantly associated with CNSinv at dx included stage 3/4 (OR, 11.2 [1.47-85.9]), poor performance status (PS; OR, 2.12 [1.22-3.69]), ≥2 extranodal sites (OR, 3.77 [2.02-7.03]), or marrow involvement (OR, 2.44 [1.35-4.39]), whereas intestinal involvement conferred low risk of CNSinv (OR, 0.27 [0.11-0.65]). CNSinv at dx was not significantly associated with use of specific chemotherapy regimens (Fig. A,P=.75) or receipt of IT chemotherapy (91% vs 84%, P=.065). Pts with CNSinv were less likely to achieve a complete response (62% vs 76%, P=.005), had worse 3 yr PFS (47% vs 69%; P3x upper limit of normal [LDH>3x]; see Evens AM et al, ASH 2019 for further details). With median follow up of 3.6 yrs, 33 pts (6%) experienced a CNS recurrence (82% within 1 yr from dx; 79% purely in CNS, and 21% with concurrent systemic BL). The cumulative risk of CNS recurrence was 6% [4-8%] at 3y (Fig. D). Univariate significant predictors of CNS recurrence included baseline CNSinv, HIV+ status, stage 3/4, poor PS, LDH>3x, involvement of ≥2 extranodal sites, marrow, or testis. However, in a multivariate model only baseline CNSinv (SHR, 3.35 [1.53-7.31]) and poor PS (SHR, 2.24 [1.03-4.90]) retained significance. The 3 yr risk of CNS recurrence varied from 3% for pts with no risk factor, to 10% with one, and 17% with both factors (Fig. E). In addition, the risk of CNS recurrence differed according to chemotherapy regimen, and was significantly higher for pts treated with DA-EPOCH (12% at 3y [8-18%]; Fig. F) compared with CODOX-M/IVAC (4% [2-8%]) or hyperCVAD/MA (3% [1-6%]; SHR for DA-EPOCH vs. others, 3.50 [1.69-7.22]). All pts recurring after DA-EPOCH had received IT chemotherapy. Higher risk of CNS recurrence persisted with DA-EPOCH regardless of baseline CNSinv (Pinteraction=.70), poor PS (Pint=.14), or HIV status (Pint=.89). Baseline CNSinv was the strongest factor associated with CNS recurrence after DA-EPOCH (3 yr risk, 30% vs 8%, P<.001). Of 7 pts who received HDMTX with DA-EPOCH (6 with leptomeningeal CNSinv at dx), 3 (43%) experienced CNS recurrence. Median OS among all BL pts with CNS recurrence was 2.8 months [1.9-3.9] (Fig. G). After recurrence, 67% of pts received salvage systemic and 9% IT chemotherapy, 3% radiation, and 21% hospice care. Conclusions: In adult BL, baseline CNSinv and poor PS predicted subsequent CNS recurrence, an outcome that is associated with a dismal prognosis. Furthermore, treatment with DA-EPOCH was associated with a significantly increased risk of CNS recurrence in this real-world analysis. For BL pts with baseline CNSinv treated in routine clinical practice, regimens with highly BBB-penetrant drugs (e.g. CODOX-M/IVAC, hyperCVAD/MA) may be preferred. Studies should delineate ways to mitigate the risk of CNS recurrence with lower-intensity programs. Disclosures Evens: Seattle Genetics: Consultancy, Honoraria; Research to Practice: Honoraria; Verastem: Consultancy, Honoraria; Affimed: Consultancy, Honoraria; Pharmacyclics: Honoraria, Other: DMC; Bayer: Consultancy, Honoraria; Takeda: Research Funding; Merck: Research Funding. Smith:Incyte Corporation: Research Funding; Seattle Genetics: Research Funding; Portola Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Acerta Pharma BV: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Ignyta (spouse): Research Funding; Merck Sharp & Dohme Corp: Consultancy, Research Funding; Denovo Biopharma: Research Funding; Bristol-Myers Squibb (spouse): Research Funding; Ayala (spouse): Research Funding. Naik:Celgene: Other: Advisory board. Reddy:KITE Pharma: Consultancy; Abbvie: Consultancy; Genentech: Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy. Farooq:Celgene: Honoraria; Kite Pharma: Research Funding. Epperla:Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Khan:Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Janssen: Other: Educational Content/Symposium; Abbvie: Membership on an entity's Board of Directors or advisory committees; Bristol Myers: Other: Research Funds. Alderuccio:Puma Biotechnology: Other: Immediate family member; Agios: Other: Immediate family member; Inovio Pharmaceuticals: Other: Immediate family member; Targeted Oncology: Honoraria; OncLive: Consultancy; Foundation Medicine: Other: Immediate family member. Yazdy:Bayer: Honoraria; Genentech: Research Funding; Octapharma: Consultancy; Abbvie: Consultancy. Diefenbach:Bristol-Myers Squibb: Consultancy, Research Funding; Denovo: Research Funding; Genentech: Consultancy, Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; MEI: Research Funding; Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Trillium: Research Funding. Karmali:Astrazeneca: Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Martin:Celgene: Consultancy; Teneobio: Consultancy; Karyopharm: Consultancy; Janssen: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy. Magarelli:Tevan Oncology: Speakers Bureau. Kamdar:Seattle Genetics: Speakers Bureau; Pharmacyclics: Consultancy; AstraZeneca: Consultancy; Celgene: Consultancy; University of Colorado: Employment. Portell:Xencor: Research Funding; Roche/Genentech: Research Funding; Infinity: Research Funding; TG Therapeutics: Research Funding; AbbVie: Research Funding; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy, Research Funding; Amgen: Consultancy; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding. Lossos:Janssen Scientific: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; NIH: Research Funding. Olszewski:Genentech: Research Funding; Adaptive Biotechnologies: Research Funding; TG Therapeutics: Research Funding; Spectrum Pharmaceuticals: Research Funding

Burkitt lymphoma in the modern era: real-world outcomes and prognostication across 30 US cancer centers

We examined adults with untreated Burkitt lymphoma (BL) from 2009 to 2018 across 30 US cancer centers. Factors associated with progression-free survival (PFS) and overall survival (OS) were evaluated in univariate and multivariate Cox models. Among 641 BL patients, baseline features included the following: median age, 47 years; HIV+, 22%; Eastern Cooperative Oncology Group (ECOG) performance status (PS) 2 to 4, 23%; >1 extranodal site, 43%; advanced stage, 78%; and central nervous system (CNS) involvement, 19%. Treatment-related mortality was 10%, with most common causes being sepsis, gastrointestinal bleed/perforation, and respiratory failure. With 45-month median follow-up, 3-year PFS and OS rates were 64% and 70%, respectively, without differences by HIV status. Survival was better for patients who received rituximab vs not (3-year PFS, 67% vs 38%; OS, 72% vs 44%; P 3× normal (PFS, HR = 1.83, P < .001; OS, HR = 1.63, P = .009), and CNS involvement (PFS, HR = 1.52, P = .017; OS, HR = 1.67, P = .014) predicted inferior survival. Furthermore, survival varied based on number of factors present (0, 1, 2 to 4 factors) yielding 3-year PFS rates of 91%, 73%, and 50%, respectively; and 3-year OS rates of 95%, 77%, and 56%, respectively. Collectively, outcomes for adult BL in this real-world analysis appeared more modest compared with results of clinical trials and smaller series. In addition, clinical prognostic factors at diagnosis identified patients with divergent survival rates