Martin, Peter

Background Mantle cell lymphoma (MCL) is more common in males, with a male to female ratio of approximately 3:1. However, it is unclear whether disease characteristics and survival outcomes differ by sex. Additionally, the impact of race and ethnicity in MCL is understudied due to underrepresentation of minorities in clinical studies and trials. In this study, we utilized the National Cancer Database (NCDB) to examine patient and disease characteristics and survival outcomes of MCL by sex, race and ethnicity. Methods Patients diagnosed with MCL in 2004-2020 were identified from NCDB. Patient and disease characteristics were compared between groups using Chi-squared tests. Overall survival (OS) analysis was performed using the Kaplan-Meier method and the Cox proportional hazards model. Results A total of 35,135 patients was included. The median follow-up was 83.0 months (95% CI 81.9-84.1). 24,980 (71.1%) patients were male and 10,155 (28.9%) were female. Females had more elderly (age ≥65: 65.9% vs 59.0%; p<0.001), lower Charlson-Deyo Score (CDS ≥2: 7.0% vs 8.6%; p<0.001) and fewer stage III-IV diagnoses (80.5% vs 82.6%; p<0.001). Females were less likely to receive upfront treatment (80.7% vs 85.3%; p<0.001), treatment at academic centers (36.8% vs 40.9%; p<0.001) or transplant (11.0% vs 13.7%; p<0.001). Compared to males, females were more likely to live in metropolitan areas (83.7% vs 81.6%; p<0.001), had similar incomes, had more Medicare (60.4% vs 53.1%) and fewer private insurance (33.2% vs 38.6%; p<0.001). Female patients had better OS, with a median OS of 76.0 (95% CI 72.4-79.6) vs 67.8 months (95% CI 65.9-69.6; p<0.001). In the multivariable Cox model adjusting for age, race, ethnicity, CDS, stage, upfront treatment (vs surveillance or no treatment), facility (academic vs nonacademic), transplant, residence (metropolitan vs urban or rural) and insurance, female sex remained associated with superior OS (HR 0.84, 95% CI 0.793-0.890; p<0.001). For race, 32,399 (92.2%) patients were White, 1,465 (4.2%) were Black, 942 (2.7%) were others and 329 (0.9%) were unknown. Compared to White patients, Black patients had fewer elderly (52.9% vs 61.7%; p<0.001), higher CDS (≥2: 11.4% vs 7.9%; p<0.001), similar stage III-IV (80.7% vs 82.1%; p=0.276) and upfront treatment (84.7% vs 84.0%; p=0.074), were more likely to be treated at academic centers (50.6% vs 38.9%; p<0.001), were less likely to receive transplant (11.1% vs 13.0%; p=0.042), were more likely to live in metropolitan areas (91.0% vs 81.5%; p<0.001), had lower income, had more uninsured (4.4% vs 2.0%) and Medicaid (9.8% vs 3.7%) and fewer Medicare (47.4% vs 56.0%; p<0.001). Black and White patients had similar OS, with a median of 67.9 (95% CI 57.5-78.2) vs 69.6 months (95% CI 67.8 vs 71.3; p=0.697). In the multivariable Cox model, Black vs White race was not associated with OS (HR 1.086, 95% CI 0.952-1.240; p=0.219). For ethnicity, 31,717 (90.3%) patients were non-Hispanic, 1,894 (5.4%) were Hispanic and 1,534 (4.3%) were unknown. Hispanics had fewer elderly (51.3% vs 61.5%; p<0.001), lower CDS (≥2: 6.4% vs 8.2%; p=0.018), similar stage III-IV (81.2% vs 82.1%; p=0.467), were more likely to receive upfront treatment (86.0% vs 83.9%; p<0.001), more likely to be treated at academic centers (49.9% vs 39.5%; p<0.001), equally likely to receive transplant (13.0% vs 13.1%; p=0.943), more likely to live in metropolitan areas (95.4% vs 81.6%; p<0.001), had lower income, had more uninsured (9.6% vs 1.8%) and Medicaid (15.2% vs 9.6%) and fewer Medicare (40.3% vs 55.9%; p<0.001). Hispanics had better OS, with a median OS of 84.4 (95% CI 71.7-97.1) vs 70.5 months (95% CI 68.7-72.2; p<0.001). However, in the multivariable Cox model, Hispanic ethnicity was not associated with OS (HR 0.952, 95% CI 0.839-1.080; p=0.448). Conclusion This study is the first of its scale to demonstrate that female MCL patients have superior survival outcomes compared to males. It also demonstrated that neither Black race nor Hispanic ethnicity appears to be associated with worse survival outcomes. Despite its size, the NCDB is limited in the treatment information and disease characteristics it provides, including MIPI score, Ki-67, blastoid/pleomorphic morphology, and TP53 status. Thus, additional real-world dataset studies are needed to gain a deeper understanding of potential differences in sex, race and ethnicity with regards to disease characteristics and survival outcomes.

Abstract Objective This study aimed to conduct a scoping review of machine learning (ML) techniques in outpatient parenteral antimicrobial therapy (OPAT) for predicting adverse outcomes and to evaluate their validation, implementation and potential barriers to adoption. Materials and methods This scoping review included studies applying ML algorithms to adult OPAT patients, covering techniques from logistic regression to neural networks. Outcomes considered were medication intolerance, toxicity, catheter complications, hospital readmission and patient deterioration. A comprehensive search was conducted across databases including Cochrane Central, Cochrane Reviews, Embase, Ovid MEDLINE and Scopus, from 1 January 2000 to 1 January 2024. Results Thirty-two studies met the inclusion criteria, with the majority being single-centre experiences primarily from North America. Most studies focused on developing new ML models to predict outcomes such as hospital readmissions and medication-related complications. However, there was very little reporting on the performance characteristics of these models, such as specificity, sensitivity and C-statistics. There was a lack of multi-centre or cross-centre validation, limiting generalizability. Few studies advanced beyond traditional logistic regression models, and integration into clinical practice remains limited. Discussion ML shows promise for enhancing OPAT outcomes by predicting adverse events and enabling pre-emptive interventions. Despite this potential, significant gaps exist in development, validation and practical implementation. Barriers include the need for representative data sets and broadly applicable, validated models. Conclusion Future research should address these barriers to fully leverage ML’s potential in optimizing OPAT care and patient safety. Models must deliver timely, accurate and actionable insights to improve adverse event prediction and prevention in OPAT settings.

7006 Background: Rituximab maintenance (RM) after first-line (1L) bendamustine and rituximab (BR) in MCL did not improve progression-free survival in the MAINTAIN trial (Rummel et al, ASCO 2016) but was associated with improved survival outcomes in a North American observational study (Martin et al, JCO 2023). We sought to examine the potential benefit of RM after BR using a large observational cohort from 26 US academic centers. Methods: Patients with MCL who received 1L BR (without stem cell transplant) outside of clinical trials were included. At the landmark of 3 months after the end of BR, patients who achieved a complete response (CR) or partial response (PR) to BR and had no evidence of progressive disease (PD) or second-line (2L) therapy were deemed eligible for RM. Event-free survival (EFS) was defined as time from landmark to progression, relapse, retreatment, or death. EFS2 was defined as time from landmark to progression, relapse, or retreatment following 2L therapy or death. RM was not considered a line of therapy for either endpoint. OS was defined as time from landmark to death. Survival analysis was done with Kaplan-Meier methods and Cox regression models adjusting for sex and simplified MIPI. Results: Among 796 patients who received 1L BR in 2007-2020, 693 achieved a CR or PR. At the 3-month post-BR landmark, 613 had no evidence of PD, among whom 318 (52%) received RM and 295 did not. The RM group was younger (median age 70 vs 72, p = 0.010) and more predominantly male (78% vs 69%, p = 0.047). There was no statistical difference in stage, simplified MIPI, histology (blastoid or pleomorphic vs classic), Ki-67, TP53 alteration, complex karyotype, year of BR start, or best response to BR between the two groups. The median follow-up after the 3-month post-BR landmark was 61.3 months (95% CI 62.6-70.4). The median number of doses of RM was 10 (IQR 5-12). RM was associated with improved EFS (median 47.1 vs 29.7 months, adjusted HR 0.59, 95% CI 0.48-0.73), EFS2 (median 89.1 vs 48.3 months, adjusted HR 0.63, 95% CI 0.50-0.81), and OS (median 136.1 vs 74.3 months, adjusted HR 0.57, 95% CI 0.44-0.75) (all p values < 0.001). In patients with CR to 1L BR (n=527), 271 (51%) received RM, for a median of 11 (IQR 6-12) doses. In this subgroup, RM was associated with improved EFS (median 60.6 vs 31.5 months, adjusted HR 0.56, 95% CI 0.44-0.71), EFS2 (median 89.1 vs 48.3 months, adjusted HR 0.62, 95% CI 0.48-0.81), and OS (median 136.1 vs 75.6 months, adjusted HR 0.59, 95% CI 0.44-0.79) (all p values < 0.001). Analysis in patients with PR to 1L BR was limited by the sample size (n=86, 47 received RM). The numeric differences in median EFS (20.8 vs 11.5, log-rank p = 0.370), EFS2 (48.9 vs 30.3, log-rank p = 0.210) and OS (87.3 vs 46.9, log-rank p = 0.067) were not statistically significant. Conclusions: In this large multicenter study, RM after 1L BR was associated with improved EFS and OS, supporting its use in routine practice for patients with newly diagnosed MCL.

Introduction: The use of standardized, evidence-based classification systems is crucial for the accurate diagnosis and treatment of diseases. Moreover, standardized classification facilitates research and epidemiologic studies and promotes consistency in communication among healthcare professionals. Since 2016, the revised 4 th edition of the World Health Organization classification (WHO-HAEM4R) has been the global standard for diagnosis of lymphoid malignancies. With the emergence of new data, 2 new classification systems were developed and published in 2022: the 5 th edition of the WHO Classification (WHO-HAEM5) and the International Consensus Classification (ICC). Both WHO-HAEM5 and ICC maintain a shared fundamental concept of disease classification that integrates clinical, pathologic, and molecular data. However, they differ on nomenclature, establishment of new entities, and/or diagnostic criteria for some disease categories. To evaluate the impact of these differences on real-world diagnosis of non-Hodgkin lymphoma (NHL), we examined the diagnostic classification of NHL in the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study (NCT02736357). Methods: Initiated in 2015, LEO is an ongoing prospective observational study of patients aged ≥18 years with newly diagnosed NHL. Patients are enrolled at 8 major U.S. medical centers. Clinical, epidemiologic, pathologic, and treatment data are abstracted at baseline and active follow-up is conducted for all patients. Lymphoma subtype is coded for each case based on expert hematopathology re-review of the diagnostic pathology slides, the pathology report, biomarker data, and clinical data. Of note, NHL subtype distribution is similar to SEER data. We studied all patients enrolled in LEO between 7/1/2016 (the date LEO pathology review started using WHO-HAEM4R diagnostic codes) and 5/31/2020. WHO-HAEM4R diagnoses and additional clinicopathologic data, when relevant, were used to map cases into the corresponding WHO-HAEM5 and ICC diagnoses. Differences between WHO-HAEM5 and ICC were annotated for each case as: None - same disease entity; Minor - difference in nomenclature with similar diagnostic criteria; Major - difference in disease category and/or diagnostic criteria; or Unevaluable - insufficient data to assign WHO-HAEM5 and/or ICC diagnosis. Results: LEO enrolled 6143 patients during the study period. Of these, comparison between WHO-HAEM5 and ICC was evaluable in 5730 (93.3%). Unevaluable cases included those without a specific WHO-HAEM4R diagnosis at enrollment (N=384; e.g., patients with a low-grade B-cell lymphoma that could not be definitively sub-classified) and those with a specific WHO-HAEM4R diagnosis, but with insufficient clinicopathologic data to assign a specific WHO-HAEM5 and/or ICC diagnosis (N=29). Of the 5730 evaluable cases, 5376 (93.8%) showed no difference between WHO-HAEM5 and/or ICC diagnosis, 311 (5.4%) showed minor differences (nomenclature only), and 43 (0.8%) showed major differences (Table 1). The 43 major differences all involved B-cell NHLs; 20 (46.5%) were attributable to different approaches to classifying double-hit lymphomas, 21 (48.9%) to classification of splenic/leukemic B-cell lymphomas, and 2 (4.6%) to classification of B-cell lymphomas occurring at specific anatomic sites (Table 2). Conclusion: In a large, prospective lymphoma cohort reflecting real-world clinical practice at 8 major U.S. medical centers, major diagnostic differences in the classification of NHL using WHO-HAEM5 or ICC classification criteria were seen in 0.8%, whereas the remaining 99.2% of diagnoses were either the same or showed differences in nomenclature only. The existence of 2 concurrent classification systems presents potential for discrepancies in pathologic diagnosis, clinical practice, clinical trials, and other lymphoma research. Furthermore, some of the differences between WHO-HAEM5 and ICC are clinically and potentially therapeutically significant, and their resolution requires further study. Nevertheless, our findings argue that the proportion of patients affected would be small in real-world practice settings. This appears largely related to incidence rates of specific lymphoma subtypes, with major differences between the 2 classifications predominantly affecting rare entities, while there is general concordance on the most common forms of NHL.

Introduction: PET/CT is the standard-of-care for staging and therapy response assessment in lymphoma. Fluorodeoxyglucose (FDG)-avidity in extranodal marginal zone lymphoma (EMZL) remains controversial with some variability by extranodal location. The current Lugano classification recommends the use of CT scans only in staging and follow-up for EMZL. However, emerging data from small studies have challenged this suggestion. In this study we aimed to determine the ability of PET/CT to detect FDG-avid EMZL during staging work-up. Methods: First, we retrospectively analyzed the University of Miami (UM) MZL database (period 2/2016-1/2023) searching for patients who underwent staging PET/CT. Images were reviewed by expert radiologists to ascertain avidity of tumor and not surrounding tissue, with specific attention to ocular and GI locations; if scans were not available (n=15), we retrieved data from reports (results presented in part at ICML2023). Next, we aimed to validate the initial UM results additionally analyzing data from imaging reports for patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) MZL cohort (period 7/2015-5/2020), excluding LEO patients from Miami to avoid overlap. Patients with high-grade transformation at diagnosis were excluded. For patients with &gt;1 extranodal site, each location was counted independently. We considered FDG-avid disease if SUVmax was ≥2 as this value is commonly observed between mediastinal blood pool (BP) and liver background. To normalize data, we calculated ratios of lymphoma SUVmax versus both BP and liver background, as available. Patients without measurable disease were excluded from analysis. Results: Among 210 patients with EMZL in the UM cohort, 152 had staging PET/CT and were analyzed. Twenty-two patients demonstrated &gt;1 extranodal site providing a total of 187 locations. The LEO cohort included 411 patients from 7 centers, with 235 having available imaging reports. Fifty-two patients in this cohort demonstrated &gt;1 extranodal site providing a total of 306 locations. Disease distribution is depicted in Table 1. Among 187 EMZL locations in the UM cohort, the most common were gastric (n=33, 17.6%), ocular (n=31, 16.6%), lung (n=30, 16%), skin and soft tissue (n=16, 8.6%, each). Similarly, lung (n=63; 20.6%), soft tissue (n=46; 15%), gastric and ocular (n=34 each; 11%) were common locations in the LEO cohort. EMZL demonstrated FDG-avidity (SUVmax ≥2) across all locations with identical values in both cohorts (UM= 78.1% & LEO= 76.5%). FDG-avidity by location is shown in Table 1A & B with salivary gland (100% & 100%), lung (93.3% & 95.2%), soft tissue (93.8% & 100%), and airways (90.9% & 100%) demonstrating high avidity in both cohorts. Contrarily, skin was commonly non-FDG avid (93.8% & 81%). The median size of FDG-avid lesions was 2.4cm (range, 0.7-17.4) in UM and 2.9cm (range, 0.1-12) in LEO cohorts. In patients with &gt;1 extranodal site FDG-avidity was nearly universal across sites (UM=93% & LEO=100%). We observed a significant correlation between lymphoma size and FDG-avidity for UM (r=0.33; P=0.001), and for LEO (r=0.55; P&lt;0.0001). In patients with background FDG-avidity data in the UM cohort (n=150), a BP index and liver index ≥1 detected lymphoma in 79.3% & 71.5% cases, respectively. We were unable to calculate indexes in LEO cohort since only limited data on BP (n=26) and liver (n=19) background was available in imaging reports. Conclusions: This study represents the largest analysis evaluating accuracy of PET/CT to determine initial tumor burden in 387 patients with EMZL. We demonstrate that EMZL is largely an FDG-avid disease across two cohorts, and PET/CT should be included in the staging of these patients while acknowledging possible limited sensitivity in GI locations due to physiologic uptake. Furthermore, we observed that patients with multiple extranodal locations demonstrate uniform FDG-avidity across all sites except for skin involvement. Based on our results we recommend the incorporation of PET/CT into standard staging of EMZL in planned revised Lugano classification guidelines. In those demonstrating initial FDG-avidity, a lower SUVmax threshold of SUVmax ≥2, comparison to mediastinal BP rather than to liver background activity and evaluating for resolution of focal FDG-avidity should be considered to assess treatment response in routine care and clinical trials.

Background: QOL can be affected by disease burden, side effects of treatment, and psychosocial effects of living with cancer. Although MZL is considered incurable, we previously found that patients diagnosed from 2002-2015 had a good QOL both at baseline (BL) and the first decade after diagnosis, regardless of treatment choice (Bommier et al., submitted). Here, we evaluate whether these findings can be extended to the 2015-2020 treatment era and a more diverse US cohort. Methods: Adults with newly diagnosed MZL from 8 academic centers were prospectively enrolled within 6 months of diagnosis from 2015-2020 in the LEO cohort (NCT02736357). Participants were actively followed for disease progression/relapse, retreatment and death. QOL was measured at BL, and at 1, 2, 3 and 5 years after diagnosis using the Functional Assessment of Cancer Therapy-Lymphoma (FACT-Lym) scale (range 0-164), which consists of the FACT-General (FACT-G, range 0-104) plus a lymphoma-specific scale (range 0-60). Total FACT-G measures 4 QOL domains (range): physical (0-28), social/family (0-28), emotional (0-24), and functional (0-28) well-being (WB). We also used the Trial Outcome Index (TOI; range 0-112), which consists of FACT-G physical and functional WB plus the lymphoma-specific scale and is commonly used as an endpoint in treatment trials. All MZL patients with both BL and at least one follow-up QOL questionnaire were eligible for analysis. Patients were grouped by initial management: active surveillance (observation), local/antibiotic therapy (radiation, surgery, or anti- H. pylori therapy), or systemic therapy (chemotherapy, targeted agents, or antibody therapy). Change in QOL scores over time was analyzed using mixed models for repeated measurements, and initial treatment groups were compared. Results: Of 384 patients, 60% were female, 91% were White, 6.6% were Black/African American, and 13% were Hispanic (all races). The median age was 64 years (range 19-94). For initial management, 28% (N=106) were observed, 31% (N=118) received local/antibiotic therapy, and 42% (N=160) received systemic therapy. Across treatment groups, there were no significant differences by age, gender, race, or performance status, while there were differences by Hispanic ethnicity (p=0.006), Ann Arbor stage (p&lt;0.001) and MALT-IPI score (p&lt;0.001) (Table). At BL, patients receiving systemic therapy had lower physical WB (p=0.008), emotional WB (p=0.04), functional WB (p=0.03), FACT-G total score (p=0.008), lymphoma subscale (p&lt;0.001), FACT-Lym (p=0.001) and TOI (p&lt;0.001) compared to observation and local/antibiotic therapy (Table). While FACT-G total scores were largely stable through 5 years after diagnosis, social/family WB declined from BL for patients initially receiving either local/antibiotic therapy (mean at 1-year -1.4, p&lt;0.05; 2-year -2.1, p&lt;0.05; 3-year -1.6, p&lt;0.05; 5-year-2.9, p&lt;0.05) or systemic therapy (mean at 2-year -1.2 , p&lt;0.05; 3-year -1.4, p&lt;0.05; and 5-year -1.2, p&lt;0.05), while this was stable for observed patients. In patients receiving initial systemic therapy, there was a transient improvement in the lymphoma-specific scale (mean +1.7, p&lt;0.05) and TOI (mean +3.7, p&lt;0.05). Otherwise, QOL remained stable over time and global QoL (FACT-G, FACT-Lym), TOI, Lymphoma-specific scale (Figure), and the other FACT-G subscales (physical, emotional, or functional WB) did not differ by initial treatment strategy. Conclusions: In the diverse LEO cohort from the recent treatment era, we confirm our prior findings for newly diagnosed MZL patients that QOL is globally stable over the first 5 years after diagnosis; emotional WB is not associated with initial treatment type, providing evidence that being initially observed does not negatively impact emotional health; and there is a decline in social/family WB (support from friends and family, family acceptance of illness, family communication, close to partner), which supports the need to consider interventions for patients to address these unmet needs. In addition, this study extends these findings to the lymphoma-specific scale, FACT-Lym, and TOI, which all showing largely stable trends in the 5 years after diagnosis and suggest that recent MZL treatment strategies, including systemic therapies, neither impair nor improve QOL.

Background The therapeutic landscape of mantle cell lymphoma (MCL) has evolved significantly since the early 2000s. We previously reported that a shift in frontline immunochemotherapy choices from 2002−2009 to 2010−2015 was associated with improved event-free survival and overall survival (OS) in both younger (age ≤65) and older (age &gt;65) patients in a prospective Mayo Clinic/University of Iowa cohort (Castellino, Blood Advances, 2022). In addition, we recently reported that changes in treatment for relapsed/refractory (R/R) disease over the last two decades were associated with steady improvements in OS for R/R MCL (Tawfiq, ASH, 2022). In this study, we utilized data from the National Cancer Database (NCDB) to investigate the impact of therapy in the modern era on survival outcomes of patients with MCL in the US since 2004. Methods The NCDB is an outcomes database of more than 1,500 hospital-based cancer registries covering approximately 70% of newly diagnosed cancers in the US. The latest version of NCDB was used to identify patients with newly diagnosed MCL from 2004 to 2020. Three treatment eras were defined as Era 1 (2004−2009), Era 2 (2010−2014), and Era 3 (2015−2020), based on immunochemotherapy changes (from Era 1 to Era 2) and increased access to novel agents such as Bruton's tyrosine kinase (BTK) inhibitors (from Era 2 to Era 3). Overall survival between different eras was stratified and analyzed based on 3 age groups: &lt;65, 65−79, and ≥80 years. Survival analysis was performed using the Kaplan-Meier method and all Cox proportional hazards models were adjusted for age and sex. Results A total of 32,746 patients with newly diagnosed MCL was identified, 12,847 (39.2%) patients were age &lt;65, 14,297 (43.7%) age 65−79, and 5,602 (17.1%) age ≥80. For every age group, the distributions in sex, stage, Charlson-Deyo score, and treatment facility type (academic vs non-academic) were largely similar between eras. As expected, the median OS was significantly worse for patients age ≥80 years (19.8 months) compared to patients age 65-79 years (60.9 months) and patients age &lt;65 years (143.9 months; p &lt;0.001). In patients age &lt;65 years, OS in Era 2 was improved when compared to Era 1, with a 5-year OS rate of 72.1% vs 67.6% (logrank p&lt;0.001) (Figure 1) and an age- and sex-adjusted hazard ratio (HR) of 0.83 (95% CI 0.78−0.89, p&lt;0.001). OS in Era 3 was similar to that in Era 2, with a 5-year OS rate of 72.2% vs 72.1% (logrank p=0.61) and an age- and sex-adjusted HR of 0.97 (95% CI 0.89−1.06, p=0.51). In patients age 65-79 years, similar trends in OS changes between eras were observed. The 5-year OS rate in Era 1, Era 2, and Era 3 was 43.3%, 52.8%, and 54.9%, respectively (p&lt;0.001 comparing Era 2 vs Era 1, and p=0.05 comparing Era 3 vs Era 2). Age- and sex-adjusted HR was 0.83 (95% CI 0.78−0.87, p&lt;0.001) comparing Era 2 vs Era 1 and 0.95 (95% CI 0.89−1.01, p=0.07) comparing Era 3 vs Era 2. In patients age ≥80 years, the improvement in OS from Era 1 to Era 2 was less prominent than other age groups. The 5-year OS rate was 22.9% vs 19.5% (p=0.03), and age- and sex-adjusted HR was 0.88 (95% CI 0.81−0.94, p&lt;0.001). OS in Era 3 vs Era 2 was similar, with a 5-year OS rate of 23.1% vs 22.9% (logrank p=0.79) and an age- and sex-adjusted HR of 0.98 (95% CI 0.91−1.06, p=0.67). Conclusions This large NCDB study demonstrated that survival of patients with newly diagnosed MCL has improved over the last two decades. The results are consistent with our Mayo Clinic/University of Iowa prospective cohort study and confirm an improved OS after 2010, which was most likely driven by both frontline immunochemotherapy changes and better access to novel agents for R/R disease. The 5-year OS in patients diagnosed in 2015−2020 did not appear to be superior to those in 2010−2014, despite presumably having better access to novel agents such as BTK inhibitors in the R/R setting. This lack of a difference in OS may be partially due to short follow-up, but may also suggest that further improvement in frontline therapies by incorporating novel agents may be required to improve OS. The OS of patients age ≥80 years is limited and has only minimally improved after 2010, highlighting a significant unmet need for therapies with improved tolerability and efficacy in this age group.

Background: Recently, large B-cell lymphomas (LBCLs) have undergone major shifts in classification and treatment paradigm, particularly with the advent of CD19-targeted chimeric antigen receptor T cell therapy (CAR-T). Initially approved as third-line treatment in LBCL in 2017, as of early 2022 CAR-T is indicated for second-line therapy (2L) in patients with relapsed or refractory (R/R) disease within 12 months of frontline treatment or who are not candidates for autologous stem cell transplant (ASCT). Given this quickly changing landscape, we aimed to describe disease characteristics, patterns of care, and survival outcomes in patients with R/R LBCL receiving two or more lines of systemic therapy across modern treatment eras. Methods: We developed a database of patients with R/R LBCL from 8 U.S. academic centers in the Lymphoma Epidemiology of Outcomes (LEO) Cohort study (NCT02736357) and Consortium for Real World Evidence (CReWE). Unlike the SCHOLAR-1 dataset (M Crump et al, Blood 2017), our cohort included any patient receiving 2L, regardless of timing of progression/relapse. For this analysis, eligible patients were aged ≥18 years and received 2L between 2002-2022. Patients with histologic transformation, post-transplant lymphoproliferative disorder, primary CNS lymphoma, primary mediastinal B-cell lymphoma, Burkitt lymphoma, or plasmablastic lymphoma were excluded. Prognostic factors, therapy details (including intent for ASCT and/or CAR-T), and outcomes, including treatment response, event-free survival (EFS), and overall survival (OS), were abstracted for all lines of therapy. Treatment eras were defined as pre-CAR-T (2002-2010), CAR-T available via clinical trial (2011-2017), and post-FDA approval of CAR-T (2018-2022). Results: Of 1760 patients initiating 2L for R/R disease, 1523 were eligible for analysis. Median age at start of 2L was 62 (interquartile range [IQR] 53-70), and 65% were male; 11% were non-White, and 8% were Hispanic. High-grade subtypes comprised 16% of all cases. IPI was available for 1013 patients at time of 2L therapy, with 54% having IPI 3-5. Median time from diagnosis to 2L was 8.7 months (IQR 5.6-18.5), with 834 patients not having achieved complete response (CR) to 1L, 285 patients relapsing &lt;12 months after 1L, and 404 patients relapsing ≥12 months after 1L. The median number of total lines of therapy received was 4 (range 2-18), with 586 and 347 receiving ASCT and CAR-T, respectively, at any line of treatment. At a median follow-up of 48 months from the start of 2L, 926 patients (61%) had died. Progressive lymphoma was the primary cause of death in 75% of deceased patients, with 8% of reported deaths due to therapy. 2L was received at an academic medical center in 83% cases, and 209 patients (14%) received 2L on a clinical trial. ASCT and/or CAR-T was planned at 2L for 989 patients (65%), of whom 463 ultimately received ASCT, 88 received CAR-T, and 21 received allogeneic transplant at 2L. 494 patients were not considered for ASCT or CAR-T at 2L, and 40 were unknown for ASCT/CAR-T intent. Breakdown by treatment era (n = 1518 with available treatment start date) is shown in the Table. Median EFS from start of 2L was 4.2 months (95% confidence interval [CI]: 3.8-4.8). Median OS from start of 2L was 18 months (95% CI: 17-22), and 2- and 5-year OS estimates were 46% (95% CI: 44-49%) and 35% (95% CI: 33-38%), respectively. EFS and OS improved significantly for patients initiating 2L between 2011-2017 compared to 2002-2010. However, EFS and OS in the 2018-2022 era remained similar to 2011-2017 (Figure). Conclusions: To our knowledge, this study is the first-ever large-scale attempt to describe patterns of care and outcomes in LBCL 2L in the modern era, inclusive of all treatment approaches. The rich and unique LEO CReWE dataset captures evolving practice approaches over time in terms of both intent for and receipt of cellular therapies. Likely reflecting the rapid development of many novel immune effector cell products and bispecific antibodies, we observed increased enrollment on 2L clinical trials in the 2018-2022 period, including a substantial proportion of patients receiving CAR-T in 2L. Importantly, survival increased in treatment eras during which CAR-T was available. Ongoing analyses of factors associated with improved survival will be presented at the meeting.

Background: We previously reported thatearly events in follicular lymphoma (FL), defined as progression of disease within 24 months (POD24) or early transformation to a more aggressive histology, are significantly associated with increased risk of lymphoma related death. To refine clinical management, the FLIPI24 prognostic model was developed to predict the risk of early events after starting immunochemotherapy (IC) (Maurer et al, 2022). The FLIPI24 model was found to be significantly superior to standard clinical models for prediction of both event-free survival at 24 months (EFS24) and overall survival (OS) in internal and external validation sets of patients receiving IC. We sought to evaluate the prognostic ability of the FLIPI24 model in patients with FL not receiving IC. Methods: The cohort consists of prospectively enrolled patients in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and the multicenter Lymphoma Epidemiology of Outcomes (LEO) Cohorts. Data were collected from medical records by standard protocol with all events verified by medical record review. Eligible patients were those diagnosed with grades 1-3A FL and initiated observation, rituximab monotherapy, radiation, or other non-IC therapy. The FLIPI24 model utilizes 5 continuous variables: age (linear 60-90 years with inflection at age 75), HGB (linear 8-17 g/dL), WBC (linear 4-11x10 9/L), LDH/ULN (linear 0.5-5), and B2M (linear 1-10 mg/L). FLIPI24 risk is grouped as follows: low risk (≤10%], low-average risk (10-15%], average risk (15-20%], high risk (20-40%], very high risk (&gt;40%) for an early event. EFS was defined as time from diagnosis to progression, relapse, (re)treatment, histologic transformation, or death due to any cause. OS was defined as the time from diagnosis until death from any cause. Cox models and Kaplan Meier curves were used to evaluate association between FLIPI24 and EFS or OS. Results: 1542 patients initiating non-IC management approaches at diagnosis from 2002-2020 were identified. 51% were &gt;60 years (IQR 52-70), and 49% were male. Most patients (86%) had FL grade 1-2. 61% of patients met any criteria for high tumor burden per GELF, BLNI, or GITMO based on available variables. Treatment approaches were 833 observation (54%), 315 rituximab monotherapy (20%), 186 radiation (12%), and 208 other non-IC approaches (14%). At median follow-up of 58 months, EFS24 was 73.8% (95% CI: 71.6%, 76.1%), 5-year OS was 90.9% (95% CI: 89.3%, 92.5%) and 253 (16%) patients died. The FLIPI24 score identified poor outcomes among patients with high/very high-risk score (FLIPI24 &gt;20%), with median EFS of 1.8 years (95% CI, 1.3, 3.28) and 5 year OS of 65.1% (95% CI: 55.9-75.8) (Figure 1). When evaluating patient subsets, for patients with high tumor burden (defined based on available variables) and high/very high-risk score, median EFS was 1.6 years and 5 year OS was 64.6% (95% CI: 54.9%-76.1%). Among patients with low tumor burden FL and high/very high-risk score, median EFS was 2.0 years (95% CI: 0.84-NA) and 5 year OS was 66.2% (95% CI: 42.4%-100%). Patients undergoing observation with high/very high-risk score similarly had shortened median EFS of 1.53 years (95% CI: 1.25-NA) and 5 year OS of 68.9% (95% CI: 56.4%-84.1%). The FLIPI24 had superior concordance for OS (c=0.726) compared to the FLIPI (c=0.646) when evaluated in patients not treated with IC. Results were comparable in the subsets of patients observed (c=0.706 vs 0.596) and receiving rituximab monotherapy (c=0.764 vs 0.721). Conclusion: The FLIPI24 model has been previously validated to provide an individual risk score at diagnosis for the likelihood of experiencing an event within 24 months from starting IC. Here we demonstrate that a high FLIPI24 score predicts for poorer outcomes following non-IC strategies including observation, treatment with radiation, and rituximab monotherapy. The FLIPI24 has better prognostic performance for OS than FLIPI in this non-IC population. High FLIPI24 in patients not treated with IC identifies a patient population who should be considered for IC and/or novel frontline therapies when feasible.