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Background: Prior “best practice guidelines” (BPG) have identified strategies to reduce the risk of acute deep surgical site infection (SSI), but there still exists large variability in practice. Further, there is still no consensus on which patients are “high risk” for SSI and how SSI should be diagnosed or treated in pediatric spine surgery. We sought to develop an updated, consensus-based BPG informed by available literature and expert opinion on defining high-SSI risk in pediatric spine surgery and on prevention, diagnosis, and treatment of SSI in this high-risk population. Materials and Methods: After a systematic review of the literature, an expert panel of 21 pediatric spine surgeons was selected from the Harms Study Group based on extensive experience in the field of pediatric spine surgery. Using the Delphi process and iterative survey rounds, the expert panel was surveyed for current practices, presented with the systematic review, given the opportunity to voice opinions through a live discussion session and asked to vote regarding preferences privately. Two survey rounds were conducted electronically, after which a live conference was held to present and discuss results. A final electronic survey was then conducted for final voting. Agreement ≥70% was considered consensus. Items near consensus were revised if feasible to achieve consensus in subsequent surveys. Results: Consensus was reached for 17 items for defining high-SSI risk, 17 items for preventing, 6 for diagnosing, and 9 for treating SSI in this high-risk population. After final voting, all 21 experts agreed to the publication and implementation of these items in their practice. Conclusions: We present a set of updated consensus-based BPGs for defining high-risk and preventing, diagnosing, and treating SSI in high-risk pediatric spine surgery. We believe that this BPG can limit variability in practice and decrease the incidence of SSI in pediatric spine surgery. Level of Evidence: Not applicable.

e19533 Background: Pneumocystis pneumonia (PJP) is a catastrophic infection seen in the context of low CD4 counts. Brentuximab vedotin (BV) is a drug antibody conjugate targeting CD30 and is used to treat patients with Hodgkin’s lymphoma (HL) and T-cell lymphoma (TCL). PJP prophylaxis is not currently recommended for patients receiving BV-based treatment despite co-expression of CD30 on CD4 cells. The frequency of PJP following BV remains poorly defined. Methods: We evaluated patients who received BV between January 1, 2011 and October 31, 2021 at Mayo Clinic for the development of PJP. Patient demographics and clinical characteristics including underlying disease, chemotherapy regimen, absolute lymphocyte count (ALC), and steroid exposure were collected. Patients who developed PJP more than 3 months after their last BV exposure were excluded. Results: Of 402 BV recipients identified, 63 received PJP prophylaxis and were omitted. Fourteen of the 339 (4.1%) not on prophylaxis developed PJP following BV. Those infected had a median age of 61 (22-87), 71% were male. The most common diagnoses were HL, TCL, and primary mediastinal B-cell lymphoma at rates of 57%, 21%, and 14% respectively. Therapy regimens included BV monotherapy, BV-CHP, and BV-AVD at rates of 43%, 21%, and 14% respectively. BV represented median 2nd line of therapy (1-10) and patients received median of 3 doses (1-10) prior to PJP diagnosis. Patients with PJP had median ALC of 620 (370-3500). 71.4% (10/14) had an ALC less than 750 and among those with ALC greater than 1000, 75% (3/4) had underlying diagnosis of HL. Three patients had CD4 count measured at time of PJP diagnosis with median value of 157 (5-175). 57.1% (8/14) had no steroid exposure beyond the treatment regimen. 14.3% (2/14) were on chronic doses of 5mg prednisone for autoimmune conditions. Short bursts of steroids (prednisone 40 mg) prior to PJP were seen in 21.4% (3/14) with median exposure of 8 days (7-10). One patient had prolonged steroid exposure but was weaned off 17 days prior to PJP diagnosis. 71.4% were older than 50 years at time of PJP. Conclusions: We observed rates of PJP above the commonly accepted threshold of 3.5% for recommending prophylaxis. Among patients with an ALC greater than 1000, 75% had HL raising the question of a qualitative defect in immunity. Close ALC monitoring is recommended for patients receiving BV with a low threshold to institute PJP prophylaxis, especially amongst those older than 50 or with a diagnosis of HL.[Table: see text]

Abstract Introduction Central nervous system (CNS) relapse (CNSr) in patients with aggressive non-Hodgkin lymphoma (NHL) occurs uncommonly (estimated incidence 5%) but carries a high morbidity and mortality. Studies have identified risk factors for CNSr such as high tumor burden and extranodal (EN) disease. However, most focus on B-cell NHL with minimal data in T-cell lymphomas (TCL), which are significantly less common and more heterogenous. The few small series of CNSr in TCL report a median overall survival (OS) less than 3 months (mo) with incidence ranging from 2.6-9%. To better define CNSr in TCL, we performed a multi-institutional retrospective analysis of TCL patients with CNSr and herein describe clinicopathologic characteristics and treatment of CNSr. Methods We performed a retrospective observational study using data from 9 US academic centers with IRB approval at individual sites. We included adult patients diagnosed with a mature T-cell neoplasm as per the 2016 WHO classification between 1/1/2009-1/1/2019, who were found to have CNSr at any time after initial diagnosis, and collected patient, disease, and treatment characteristics at time of initial diagnosis as well as at CNSr. Patients with a diagnosis of a precursor T-cell malignancy or with CNS disease identified at initial TCL diagnosis (TCLd) and/or prior to first-line systemic treatment were excluded. Results In this analysis, we report the outcomes of 75 patients (male n=45, female n=30). At TCLd, the median age was 59 years (range 20-81), and 61% of patients (n=46) had an IPI score of at least 3, 92% (n=69) had EN involvement with 37% (n=28) involving at least 2 EN sites, and 59% (n=44) had BM involvement. The most common pathologic diagnoses were peripheral T-cell lymphoma, not otherwise specified (PTCL, NOS; 24%, n=18), angioimmunoblastic T-cell lymphoma (AITL; 17%, n=13), adult T-cell leukemia/lymphoma (ATLL; 17%, n=13), and mycosis fungoides (MF; 12%, n=9) (Figure 1A). First-line systemic therapy for TCL included anthracyclines for 72% (n=54). Autologous and allogenic transplants were performed prior to CNSr in 12% (n=9) and 8% (n=6) of patients, respectively. Prior to CNSr, 48% (n=36) had non-CNS relapse. Some form of CNS prophylaxis was used during initial systemic lymphoma therapy in 24% of patients (n=18), predominantly intrathecal methotrexate (IT MTX; n=16). Median time from TCLd to CNSr was 8.5mo, though this was significantly longer in MF (46.8mo [range 17.5-187.7]) versus PTCL, NOS (7.6mo [range 1.1-58.4], P=0.0002), AITL (21.2mo [range 2.0-61.6, P=0.008), and ATLL (7.3mo [range 0.7-46.4], P=0.0005) (Figure 1B). CNSr developed within 6mo of TCLd in 31% of patients (n=23) and within 12mo in 57% (n=43). Symptoms related to CNSr occurred in 71% of patients (n=53). CNSr patterns were 61% leptomeningeal (n=46), 21% parenchymal (n=16), and 17% both (n=13) with no significant survival difference between leptomeningeal or parenchymal disease alone (HR 1.45, 95% CI 0.78-2.70, P=0.28). Concomitant systemic relapse was observed in 59% of patients (n=44). The most common CNS-directed therapy for CNSr was IT MTX (56%; n=42), though multiple different IT and/or systemic regimens were used. Patients received a median of 1 line of CNS-directed treatment (range 0-5). The overall response rate to initial CNS directed treatment was 32% (16% CR, 16% PR). Median follow up after CNSr was 40.7mo. At last follow up, 83% had died (n=62). Median OS after CNSr was 4.6mo (range 0.1-68.7) (Figure 1C). Those with ATLL had the shortest median OS after CNSr (2.7mo) versus 6.3mo in MF (HR 3.69, 95% CI 1.44-9.42, P=0.005), 6.5mo in AITL (HR 2.16, 95% CI 0.92-5.06, P=0.054), and 4.8mo in PTCL, NOS (HR 1.49, 95% CI 0.70-3.19, P=0.27) (Figure 1D). The most common cause of death was progressive lymphoma (77%; n=48). Conclusions This is to our knowledge the largest series of CNSr in TCL to date. Most CNSr occurred within 12mo, though CNSr occurred later in patients with MF. Although the prognosis after CNSr was generally poor, we found that median OS in CNSr was longer than previously reported, perhaps reflecting more effective treatments for CNS and systemic relapse, inclusion of MF, or lead time bias. Further analysis of the impact of different treatment strategies and outcomes in CNSr was limited by the small sample size and heterogeneity within our cohort, and future analyses in a larger cohort should focus on factors associated with outcomes. Figure 1 Figure 1. Disclosures Horwitz: ADC Therapeutics, Affimed, Aileron, Celgene, Daiichi Sankyo, Forty Seven, Inc., Kyowa Hakko Kirin, Millennium /Takeda, Seattle Genetics, Trillium Therapeutics, and Verastem/SecuraBio.: Consultancy, Research Funding; Affimed: Research Funding; Aileron: Research Funding; Acrotech Biopharma, Affimed, ADC Therapeutics, Astex, Merck, Portola Pharma, C4 Therapeutics, Celgene, Janssen, Kura Oncology, Kyowa Hakko Kirin, Myeloid Therapeutics, ONO Pharmaceuticals, Seattle Genetics, Shoreline Biosciences, Inc, Takeda, Trillium Th: Consultancy; Celgene: Research Funding; C4 Therapeutics: Consultancy; Crispr Therapeutics: Research Funding; Daiichi Sankyo: Research Funding; Forty Seven, Inc.: Research Funding; Kura Oncology: Consultancy; Kyowa Hakko Kirin: Consultancy, Research Funding; Millennium/Takeda: Research Funding; Myeloid Therapeutics: Consultancy; ONO Pharmaceuticals: Consultancy; Seattle Genetics: Consultancy, Research Funding; Secura Bio: Consultancy; Shoreline Biosciences, Inc.: Consultancy; Takeda: Consultancy; Trillium Therapeutics: Consultancy, Research Funding; Tubulis: Consultancy; Verastem/Securabio: Research Funding. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Chavez: AstraZeneca: Research Funding; ADC Therapeutics: Consultancy, Research Funding; Merk: Research Funding; MorphoSys, AstraZeneca, BeiGene, Genentech, Kite, a Gilead Company, and Epizyme: Speakers Bureau; MorphoSys, Bayer, Karyopharm, Kite, a Gilead Company, Novartis, Janssen, AbbVie, TeneoBio, and Pfizer: Consultancy; BMS: Speakers Bureau. Sokol: Dren Bio: Membership on an entity's Board of Directors or advisory committees; Kyowa-Kirin: Membership on an entity's Board of Directors or advisory committees. Saeed: Nektar Therapeutics: Consultancy, Other: research investigator; MEI Pharma Inc: Consultancy, Other: investigator; Celgene Corporation: Consultancy, Other: investigator; MorphoSys AG: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb Company: Consultancy; sano-aventis U.S.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceutica Products, LP: Consultancy, Other: investigator; Kite Pharma: Consultancy, Other: investigator; Other-TG therapeutics: Consultancy, Other: investigator; Other-Epizyme, Inc.: Consultancy; Other-Secura Bio, Inc.: Consultancy; Seattle Genetics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Mehta-Shah: Kiowa Hakko Kirin: Consultancy; C4 Therapeutics: Consultancy; Verastem: Research Funding; Karyopharm: Consultancy; Ono Pharmaceuticals: Consultancy; Secura Bio: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; AstraZeneca: Research Funding; Bristol Myers Squibb: Research Funding; Celgene: Research Funding; Innate Pharmaceuticals: Research Funding; Roche/Genentech: Research Funding; Corvus Pharmaceuticals: Research Funding. Olszewski: TG Therapeutics: Research Funding; PrecisionBio: Research Funding; Celldex Therapeutics: Research Funding; Acrotech Pharma: Research Funding; Genentech, Inc.: Research Funding; Genmab: Research Funding. Allen: Epizyme: Consultancy; MorphoSys: Consultancy; ADC Therapeutics: Consultancy; Secure Bio: Consultancy; Kyowa Kirin: Consultancy. Gerson: Abbvie: Consultancy; Kite: Consultancy; TG Therapeutics: Consultancy; Pharmacyclics: Consultancy. Landsburg: Triphase: Research Funding; Takeda: Research Funding; Curis: Research Funding; ADCT: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Other: DSMB member; Incyte: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees. Schuster: Adaptive Biotechnologies: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Genentech/Roche: Consultancy, Research Funding; Tessa Theraputics: Consultancy; Juno Theraputics: Consultancy, Research Funding; Loxo Oncology: Consultancy; BeiGene: Consultancy; Alimera Sciences: Consultancy; Acerta Pharma/AstraZeneca: Consultancy; Abbvie: Consultancy, Research Funding; Nordic Nanovector: Consultancy; Novartis: Consultancy, Honoraria, Patents & Royalties, Research Funding; Incyte: Research Funding; TG Theraputics: Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Svoboda: Atara: Consultancy; Adaptive: Consultancy, Research Funding; Astra Zeneca: Consultancy, Research Funding; Imbrium: Consultancy; Pharmacyclics: Consultancy, Research Funding; Genmab: Consultancy; Merck: Research Funding; Incyte: Research Funding; BMS: Consultancy, Research Funding; TG: Research Funding; Seattle Genetics: Consultancy, Research Funding. Barta: Kyowa Kirin: Honoraria; Acrotech: Honoraria; Daiichi Sankyo: Honoraria; Seagen: Honoraria.

Abstract We performed a multicenter retrospective analysis across 10 US academic medical centers to evaluate treatment patterns and outcomes in patients age ≥60 years with classic Hodgkin lymphoma (cHL) from 2010-2018. Among 244 eligible patients, median age was 68, 63% had advanced stage (III/IV), 96% had Eastern Cooperative Oncology Group performance status (PS) 0-2, and 12% had documented loss of ≥1 activity of daily living (ADL). Medical comorbidities were assessed by the Cumulative Illness Rating Scale–Geriatric (CIRS-G), where n = 44 (18%) had total scores ≥10. Using multivariable Cox models, only ADL loss predicted shorter progression-free (PFS; hazard ratio [HR] 2.13, P = .007) and overall survival (OS; HR 2.52, P = .02). Most patients (n = 203, 83%) received conventional chemotherapy regimens, including doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD; 56%), AVD (14%), and AVD with brentuximab vedotin (BV; 9%). Compared to alternative therapies, conventional regimens significantly improved PFS (HR 0.46, P = .0007) and OS (HR 0.31, P = .0003). Survival was similar following conventional chemotherapy in those ages 60-69 vs ≥70: PFS HR 0.88, P = .63; OS HR 0.73, P = .55. Early treatment discontinuation due to toxicity was more common with CIRS-G ≥10 (28% vs 12%, P = .016) or documented geriatric syndrome (28% vs 13%, P = .02). A competing risk analysis demonstrated improved disease-related survival with conventional therapy (HR 0.29, P = .02) and higher mortality from causes other than disease or treatment with high CIRS-G or geriatric syndromes. This study suggests conventional chemotherapy regimens remain a standard of care in fit older patients with cHL, and highlights the importance of geriatric assessments in defining fitness for cHL therapy going forward.

e20057 Background: T-cell lymphomas (TCL) are a heterogeneous group of rare, but aggressive non-Hodgkin lymphomas. CD4+ and CD8+ T-cell function plays a vital role in the immunologic response to P.jirovecii infection. Our study aims to define the prevalence of Pneumocystis jirovecii pneumonia (PJP) in HIV-uninfected TCL patients. Methods: All patients at Mayo Clinic, Rochester MN diagnosed with TCL and a positive Pneumocystis PCR assay from either bronchoalveolar lavage (BAL) fluid or other respiratory specimens were identified from March 2005 until November 2019. Patients with TCL and a diagnosis of PJP made outside of our medical center were identified through Advanced Cohort Explorer, a query building tool. Results: A total of 922 patients with TCL were identified, and only 14 cases (1.5%) had confirmed PJP. In confirmed PJP cases, the median age of TCL diagnosis was 62 years (IQR 51-70 years), 79% were male, and the median number of chemotherapy lines was 1.5 (IQR of 1-3). Half of the cases (6/12) received CHOP as first-line of therapy, followed by CHOEP (25%, 3/12). The median time to PJP diagnosis relative to chemotherapy was 18 days (IQR 14-27 days). Peripheral TCL, not otherwise specified was the most common TCL, followed by angioimmunoblastic TCL, and CD30+ T-cell lymphoproliferative disorders (64%, 29% and 7%, respectively). The primary specimen type sampled for PJP diagnosis was BAL fluid (n = 9, 64%), followed by sputum (n = 3, 22%), induced sputum (n = 1, 7%), and transbronchial lung biopsy (n = 1, 7%). Three patients had a prior autologous stem cell transplant (ASCT), and all three cases had relapsed TCL one year after ASCT. 77% of cases received oral prednisone equivalents (median dose of 25 mg, IQR 20-40 mg) 30 days prior to PJP diagnosis. Two patients developed PJP despite anti- Pneumocystis prophylaxis with aerosolized pentamidine. At the time of PJP diagnosis, most patients had lymphopenia (88%, 8/9), and CD4+ T-cells measurement was obtained only in one patient (CD4+ of 100 cells/mL). 71% of the cases were treated with trimethoprim/sulfamethoxazole (TMP/SMX). After the initial PJP episode, 36% of the cases were transitioned to TMP/SMX for secondary prophylaxis. All cause 30-day and 90-day mortality was 7% and 29%, respectively. Mortality attributed to PJP was 7% (n = 1). Conclusions: In our TCL cohort, the occurrence of PJP was low. Primary prophylaxis should be individualized in this population.

8030 Background: There is growing interest in the identification of modifiable patient-specific factors that may predict response to immune checkpoint inhibitors (ICIs) in classical Hodgkin lymphoma (cHL). Recently, it has been proposed that antibiotic use could decrease the efficacy of ICIs in the treatment of advanced solid malignancies. The objective of our study is to assess whether antibiotic use prior to or concurrent with ICIs is associated with changes in outcomes in patients with cHL. Methods: Patients who received a PD-1 or CTLA-4 blocker for the treatment of cHL at Mayo Clinic Rochester between January 1, 2011 and October 20, 2018 were identified. We conducted a longitudinal retrospective chart review to identify those who received antibiotics within 30 or 90 days prior to initiation or concurrent with ICI therapy. Univariate cox regression analysis was used to assess for an association between antibiotic use and overall survival (OS) and progression-free survival (PFS) within these groups; a time-dependent variable was used for concurrent antibiotic use. Results: A total of sixty-two patients were identified (61% male, median age at ICI initiation 35 years [range: 19-87]). Median duration of follow up from ICI start was 38 months (range: 4-78). Twenty-one patients (34%) received antibiotics within 90 days of initiation of ICI, of which thirteen (21%) received antibiotics within 30 days. Thirty-five patients (57%) received antibiotics concurrently with ICI. Concurrent and prior antibiotic use within 90 days of ICI were both associated with inferior PFS (concurrent HR = 6.38 [95% CI 3.02-13.47]; 90-day HR = 2.21 [95% CI 1.10-4.47]) and OS (concurrent HR = 8.77 [95% CI 1.91-40.36]; 90-day HR = 2.96 [95% CI 1.09-8.04]). Conclusions: Antibiotic use is associated with inferior outcomes in patients with cHL treated with ICIs in this single institution cohort. This may reflect potential antibiotic effects on the gut microbiome (GMB) and immune system as has been suggested in prior studies. Further confirmatory studies and examination of potential confounding covariates are needed.

e17539 Background: Chemotherapy with Docetaxel (D) or androgen pathway inhibition (API) with Abiraterone Acetate plus prednisone (AAP), Aplautamide(APA) and Enzalutamide(E) are acceptable, FDA approved treatment options for mCSPC. It is not clear whether the magnitude of benefit varies by the choice of initial agent [chemotherapy vs API] or by volume of disease [High vs Low]. Data is now available from all registration trials by volume status and motivated this analysis to inform initial treatment choice in mCSPC. Methods: We systematically searched MEDLINE(Ovid), Embase, and Scopus for randomized controlled trials of chemotherapy(D) or APIs (AAP, APA, ENZ) that had available hazard ratios (HRs) for overall survival (OS) and Progression Free Survival (PFS) according to patient’s volume of disease. We also reviewed abstracts and presentations from all major conference proceedings. We calculated the pooled overall survival HR and 95% CI by chemotherapy and APIs and by high volume(HVD) and low volume(LVD) using a random effect model, and tested for heterogeneity to assess the null hypothesis that no difference in the survival advantage exists by choice of initial agent and volume of disease. Results: Of 4456 studies identified in our search, there were 8 eligible randomized controlled trials that were included in the analysis. Both D and APIs significantly improved PFS [HR 0.48; 0.45-0.51] and OS [0.72; 0.64-0.81] when added to ADT, however the latter was associated with significantly higher improvement in PFS( P < 0.01) and OS (P = 0.03). In patients treated with D, patients with HVD derive significantly more benefit as compared to LVD( P = 0.046) and patients treated with APIs both HVD and LVD patients derive similar benefit( P = 0.80) (Table). Conclusions: mCSPC patients derive higher magnitude of survival benefit when treated with APIs as compared to D; however, D may be preferred in HVD patients. [Table: see text]