Hwang, Steven R.

518 Background: Oncology has entered the digital era, accompanied by changes in patient interactions and expectations involving telemedicine. While much emphasis is appropriately placed on digital interactions with patients, little is known about modern non-digital interactions with patients in oncology practices. Methods: We analyzed Medical Oncology Pager (MOP) data from 7/1/18 – 4/14/23, during which patients had access to the electronic health record and messaging capabilities. The MOP for Mayo Clinic (Rochester) is covered by the medical oncology fellows, including after hours (6PM – 7AM). It covers consults and direct patient calls after hours and during weekends, in addition to critical results back up and inpatient oncology matters at all times. We also analyzed Medical Oncology Call Center (MOCC) data since 6/1/22, which takes inbound patient calls during working hours (7AM – 6PM) and is staffed by appointment office employees. Results: The MOP received a total of 17,679 pages during the analyzed period for a mean of 10.1 pages per day. Of these, 6,319 pages occurred after hours. The most after-hours pages were received on Fridays (n=1,091) and the least on Sundays (n=701); of those years with fully available data, 2022 had the highest volume (n=1,405) (Table 1). When comparing the MOP activity pre-pandemic (7/1/18 – 3/10/20) and intra-pandemic (3/11/20 – 4/14/23), the mean number of after-hours pages per day was relatively stable with 3.47 pre-pandemic and 3.69 intra-pandemic. Since 6/1/22, the MOCC has averaged 6,464 inbound calls per month during working hours, each of which had an average talk time of approximately five minutes. The majority of inbound calls occur on Monday mornings between 9 – 11AM, with over 6,500 recorded throughout the previous year. Conclusions: Telemedicine is multi-faceted, comprised of both digital and non-digital patient interactions. We show that many oncology patients utilize telephone communication with the healthcare system despite increased availability of digital capabilities. These data have implications for addressing the digital divide for those with limited digital access, serving older patient populations unfamiliar with digital technologies, healthcare navigation, trainee responsibilities, and resource allocation. Further work and standardization in non-digital telemedicine is necessary as it remains a pillar of modern healthcare delivery and oncology practices.[Table: see text]

Abstract In the pivotal study ECHELON-1, brentuximab vedotin (BV), doxorubicin, vinblastine, and dacarbazine (A + AVD) demonstrated superior efficacy compared with bleomycin + AVD for the treatment of advanced-stage classic Hodgkin lymphoma (cHL). However, there are minimal available data regarding the frequency of dose reductions or omission of BV during curative therapy and the potential impact on patient outcomes. In a real-world analysis, we retrospectively reviewed the characteristics and outcomes of 179 patients with stage III or IV cHL treated with frontline A + AVD from January 2010 to April 2022. Treatment consisted of up to 1.2 mg/kg of BV and standard dose AVD IV on days 1 and 15 of each 28-day cycle for up to 6 cycles. At the time of treatment, the median patient age was 37 years, and a high-risk International Prognostic Score was observed in 46% of patients. Overall, 91% of patients received 6 cycles of AVD; 55% of patients did not receive the intended cumulative dose of BV (CDB); 28% of patients received two-thirds or less than the planned CDB. At a median follow-up time of 27.4 months (95% confidence interval [CI], 24.8-29), the median progression-free survival (PFS) was not reached, and the 12-month PFS was 90.3% (95% CI, 85.9-95.0). The impact of CDB on PFS was not significant (P = .15), nor was high CDB significantly associated with increased adverse events. In real-world experience, A + AVD is a highly effective treatment for patients with advanced-stage cHL, including for patients with prominent dose reductions of BV.

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.