Cerhan, James R.

Background: Understanding the symptoms and quality of life (QOL) over time of adults with follicular lymphoma (FL) is important for treatment decision-making and clinical management. However, there are limited population-level data on the long-term QOL of adults with FL. We aim to describe the real-world, long-term QOL of adults with newly diagnosed FL up to 5/6 years after diagnosis. Methods: We used the Mayo Clinic/Iowa Molecular Epidemiology Resource (MER) and the multi-institutional Lymphoma Epidemiology of Outcomes (LEO) to identify adults with grade 1-3A FL who completed QOL surveys at baseline and follow-up. Participants with lymphoma were prospectively enrolled within 9 months of diagnosis in the MER cohort from 2002-2015 and within 6 months of diagnosis in the multi-institutional LEO cohort study across 8 cancer centers from 2015-2020. The LEO/MER cohort studies systematically collected information on disease status, QOL, health behaviors, and functional assessment. Treatments, disease relapses, and deaths were verified by medical record review. Treating physicians determined clinical management. QOL was measured using the Functional Assessment of Cancer Therapy-General (FACT-G) at years 1, 2, 3, and 5/6 post-diagnosis. A higher FACT-G total score (range 0-108) indicated better QOL across 4 subscales (range): physical (0-28), social/family (0-28), emotional (0-24), and functional (0-28) well-being. We categorized participants based on their frontline management at time of diagnosis: “observation” (surveillance), “treatment” (systemic treatment with immunotherapy +/- chemotherapy), and “local” (radiation) groups. We employed a generalized linear mixed model to evaluate and compare the changes in QOL scores (as a continuous variable) from baseline for the observation, treatment, and local groups, adjusting for sex, race/ethnicity, age, FLIPI risk, and cohort (i.e., LEO or MER). We also evaluated QOL changes by FLIPI risk. Results: Our study included 1,544 participants with FL and QOL data. At the time of enrollment, median age was 61 years (range 19-91), 88% were non-Hispanic White, and 49% were female. Based on initial management, 529 (34%) were in the observation group, 880 (57%) were in the treatment group, and 135 (9%) were in the local group. FLIPI risk was high for 17% in the observation group, 29.3% in the treatment group, and 3% in the local group. The mean (standard deviation) baseline FACT-G total score was lowest in the treatment group with the following baseline scores: 86 (13) for the observation group, 83 (14) for the treatment group, and 88 (12) for the local group (Table 1). The observation and local groups reported a greater worsening of their baseline FACT-G total score vs the treatment group at both the 2-year (-1.2, -0.8 vs +1.8, respectively) and 5/6 year (-5.4, -6 vs. -1.6, respectively) timepoints (Figure 1). This appeared to be driven by worsened physical and functional well-being in the observation (-1.3, -2.2, respectively) and local (-0.9, -2.4, respectively) groups vs the treatment group (0, -0.3, respectively). These differences were statistically significant between the observation vs treatment groups. There were no statistically significant differences in the other subscales, i.e., social/family and emotional well-being, by frontline management. Social/family well-being decreased across all groups by 5/6 years (-2.3 in observation, -2.2 in treatment, and -3 in local, p<0.05). Regardless of FLIPI risk, the total FACT-G scores decreased within each FLIPI risk group at 5/6 years (-4.4 for low, -3.8 for intermediate, and -4.9 for high, p<0.05). This was primarily due to worsened social/family well-being (-2.4 for low, -2.2 for intermediate, and -3 for high, p<0.05) at 5/6 years. There was no statistically significant difference in QOL between FLIPI risk groups. Conclusion: This is one of the first and largest studies with real-world longitudinal QOL data for FL. Our study suggests that frontline systemic treatment initially improved QOL and resulted in a lower degree of QOL decline over time. Social/family well-being decreased over time regardless of frontline management or FLIPI risk. Further research is warranted to explore the impact of timing and specific systemic treatments on QOL, incorporate the patient/caregiver experience to address social/family well-being, and identify the clinical significance of our findings.

Background: Relapsed DLBCL occurs in up to 40% of patients and has a poor prognosis. Current prognostic tools such as the international prognostic index (IPI) and newer forms (NCCN-IPI) only include baseline clinical features. PET/CT features have not yet been incorporated into prognostic risk models despite being essential for staging and response assessment. Deep learning computer algorithms have consistently demonstrated the ability to analyze imaging data and identify features that are not readily apparent to the human eye. Using a deep learning computer vision model that automatically extracted radiomic features from PET/CTs, we examined the association of changes between baseline PET and interim PET (PET2) radiomic features on survival outcomes and compared the prognostic performance with NCCN-IPI. Methods: Adult patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) between 2005 and 2015 and enrolled in the prospective MER cohort were included. Native DICOM images from FDG PET/CT scans at baseline and interim PET (PET2, after 2-3 cycles of chemotherapy) were preprocessed for regularity and then segmented using the nnU-Net architecture with an external lymphoma-specific model. Feature extraction and standard uptake value (SUV) characterization were accomplished with PyRadiomics and NiBabel. Our computational method included no manual segmentation correction. Individual radiomics features (n=115) and the % change above (Δ High) and below (Δ low) 50 th quartile from baseline to PET2 were evaluated for association with event free survival (EFS) and overall survival (OS) using a univariate Cox regression model and by Kaplan Meier analysis. EFS was defined as time from PET2 to first systemic relapse or death from any cause. OS was defined as time from PET2 to death from any cause. Additionally, Spearman and Pearson correlation matrices were used to guide feature selection while minimizing collinearity. We then assessed the association of the highest scoring radiomics features with EFS in a multivariate cox regression model. Results: A total of 506 patients had baseline and PET2 scans available for radiomic feature extraction. Median age at diagnosis was 61 years (range 18-90), 43% were females. NCCN-IPI composition and outcomes of our cohort was comparable to the previously published NCCN cohort, with patient distribution and 5-year OS as follows: Low (9%, 5-y OS 83%), Low-intermediate (38%, 5-y OS 49%), High-intermediate (41%, 5-y OS 31%), High (11%, 5-y OS 12%). At a median follow up of 81 months,there were 308 events, and272 patients had died.Several radiomics features were associated with EFS including change in tumor surface area (SA Δ) (HR: 1.75, 95% CI 1.36-2.24, p<0.005, median of 26,927 mm 2, Figure 1A) and change in total metabolic tumor volume (TMTV Δ) (HR: 1.64, 95% CI 1.27-2.10, p<0.005, median of 120,473 mm 3, Figure 1B). As a reference, NCCN-IPI univariate Cox regression analysis of EFS produced a Harrell's C-statistic (c) of 0.624. Single radiomics features of SA Δ and TMTV Δ individually produced unadjusted c-statistics of 0.616 and 0.614 respectively. Combinations of radiomics features (SA Δ, TMTV Δ and NCCN-IPI classification) demonstrated cumulative benefit (c=0.652). Conclusion: Automatic PET-CT radiomic feature extraction using deep learning models is feasible among patients with newly diagnosed DLBCL. The change in tumor SA and TMTV appear to be promising radiomic biomarkers. A low decline in either tumor SA or TMTV by PET2 is associated with higher risk of relapse and poor survival outcomes. As individual characteristics, these features are similar prognostic indicators of EFS as the NCCN-IPI. Further investigation into risk stratification when combining radiomics with clinical and genomic variables is warranted. Figure 1. Event free survival for DLBCL patients with A) a change in tumor surface area by PET2 less than 50% percentile (SA_Δ Low) and greater than 50 th percentile (SA_Δ High) and B) a change in TMTV by PET2 less than 50% percentile (TMTV_Δ Low) and greater than 50 th percentile (TMTV_Δ High).

Background: Event-free survival at 24 months (EFS24) after frontline immunochemotherapy (IC) is an important endpoint in diffuse large B-cell lymphoma and follicular lymphoma, and patients who achieve EFS24 have similar survival compared to age- and sex-matched general population. The role of EFS24 in predicting subsequent survival has not been established in mantle cell lymphoma (MCL), possibly due to perceived poor survival historically. In the last decade, the outcomes of MCL are improving in the evolving treatment landscape. In this international multicenter study, we investigated conditional survival and cause of death in patients with MCL who achieved EFS24 after frontline IC in the older and more recent eras. Methods: Outcomes after frontline IC were evaluated in 5 independent cohorts that included over 3000 patients in total: Mayo/Iowa MER prospective cohort, BC Cancer retrospective population-based cohort, US 12-center retrospective cohort, Swedish Lymphoma Registry, and Danish National Lymphoma Registry. For each cohort, 2 treatment eras were defined based on cohort-specific shifts in treatment patterns (Table 1). Overall survival (OS) after diagnosis and after achieving EFS24 were compared to the background age- and sex-matched general population using a standardized mortality ratio (SMR). Cumulative incidences of cause-specific deaths were analyzed using a competing risk model. Results: In the MER cohort, patients treated in Era M1 (2002-2009; n=147) and Era M2 (2010-2015; n=153) both had inferior OS compared to the general US population. A lower SMR in Era M2 vs M1 (2.25 vs 3.46) suggests a narrower gap in OS compared to the general US population. Lymphoma was the leading cause of death in both eras. In Era M1, patients who achieved EFS24 still had inferior OS compared to the general US population (SMR=2.40, 95% CI 1.76-3.19), and lymphoma remained the leading cause of death. For patients in Era M2 who achieved EFS24, the difference in OS compared to the general US population was not statistically significant with current follow-up (SMR=1.43, 95% CI 0.93-2.09), and lymphoma was no longer the leading cause of death (Table 2). In the BC cohort, patients treated in Era B2 (6/2013-2019; n=188) vs Era B1 (2003-5/2013; n=250) had a narrower gap in OS compared to the general British Columbia population (SMR 4.53 vs 6.69). Lymphoma was the leading cause of death in both eras. For patients achieving EFS24, the gap in OS was narrower in Era B2 vs B1 (SMR 3.56 vs 4.99). After achieving EFS24, lymphoma was the single leading cause of death for patients in Era B1 but not in Era B2 (Table 2). In the US 12-center cohort, patients treated in Era U1 (2002-2011; n=312) and Era U2 (2012-2016; n=417) both had inferior OS compared to the general US population (SMR 2.68 and 2.92, respectively). In patients who achieved EFS24, with current follow up, the difference in OS compared to the general US population was statistically significant in Era U1 (SMR=2.01, 95% CI 1.50-2.64) but not in Era U2 (SMR=1.44, 95% CI 0.82-2.34). Lymphoma was not the leading cause of death after achieving EFS24 (Table 2). In the Swedish cohort, the gap in OS compared to the general Swedish population was narrower in Era S2 (2013-2018; n=439) vs S1 (2006-2012; n=442), both after frontline IC (SMR 4.8 vs 5.4) and after achieving EFS24 (SMR 2.6 vs 3.4). After achieving EFS24, lymphoma was the leading cause of death for patients in Era S1 but not in Era S2 (Table 2). In the Danish cohort, patients treated in Era D2 (2014-2020; n=370) vs Era D1 (2004-2013; n=461) had a slightly narrower gap in OS compared to the general Danish population (SMR 1.90 vs 2.10). For patients who achieved EFS24, those in Era D1 still had inferior OS compared to the general Danish population (SMR=1.44, 95% CI 1.22-1.68), but the OS difference compared to the general Danish population in Era D2 was not statistically significant (SMR=1.27, 95% CI 0.92-1.72) with current follow-up (Table 2). Cause of death data were not available in this cohort. Conclusion: Survival in patients with MCL who achieved EFS24 after frontline IC improved in the more recent treatment era and moved closer to the background expected survival. After achieving EFS24, lymphoma-related mortality was no longer the leading cause of death in the more recent era. EFS24 following frontline treatment may become a critical endpoint for predicting subsequent outcomes in patients with MCL in the modern era.

Background: Shorter diagnosis to treatment interval (DTI) has been shown to be associated with more aggressive disease features and inferior outcomes in diffuse large B-cell lymphoma (DLBCL; Maurer et al, JCO 2018). Additional confirmatory studies have also shown that DTI is related to tumor volume (Alig et al, JCO 2021) and molecular phenotype (Aluaij et al, Blood 2023). Here we evaluate DTI in a large multicenter cohort of patients prospectively enrolled and followed as part of the Lymphoma Epidemiology of Outcome (LEO) cohort. Methods: Patients were enrolled within 6 months of diagnosis at one the 8 LEO cohort academic medical centers in the United States between 2015 and 2020. Patients in this analysis had aggressive B-cell lymphoma (BCL) treated with anthracycline-based chemotherapy. DTI was defined as the initial lymphoma biopsy date until the start of initial chemotherapy; patients with DTI between 0-100 days were evaluated. Short DTI was defined as DTI ≤ 14 days (DTI≤14) as previously described in prior publications (e.g. Maurer et al, JCO 2018) and confirmed via examination of functional forms via splines. Event-free survival (EFS) was defined as the time from start of treatment until progression/relapse, retreatment, or death due to any cause. Overall survival (OS) was defined as the time from start of treatment until death due to any cause. Results: 2565 patients with aggressive B-cell lymphoma were evaluated. Median age was 62 years (IQR 51-71) and 1469 (57%) were male. 297 patients (12%) were self-reported non-White race and 314 patients (12%) were self-reported Hispanic or Latino. The majority had DLBCL, NOS subtype (N=1927, 75%), while 227 (9%) had high-grade BCL with MYC and BCL2 and/or BCL6 rearrangements (HG, DH) and 90 (4%) had high-grade BCL NOS (HG, NOS). Clinical characteristics are summarized in the table. At median follow-up of 49 months (IQR 36-68), 800 patients (31%) had an event and 578 patients (23%) died. EFS at 24 months (EFS24) was 76% (95% CI: 74-77). Median DTI across all subtypes was 21 days (IQR 12-33) and 845 patients (33%) had DTI≤14. Patients with DTI≤14 were significantly younger (median age 59 years) but there was no association between DTI and gender, race, or ethnicity. Patients with DTI≤14 were more likely to have HG, DH or HG NOS subtypes, ECOG PS 2-4, advanced stage, elevated LDH, CNS involvement, B symptoms, and bulky disease ( see table). Patients with DTI≤14 were more likely to receive R-EPOCH-based or intensive therapies (41%) and less likely to receive 1L therapy on a clinical trial (3.8%) compared to DTI>14 (26% and 10.1%, respectively). Consistent with previously reported data, DTI≤14 was associated with inferior EFS (HR=1.62, 95% CI: 1.41-1.87, figure), OS (HR=1.73, 95% CI: 1.47-2.04), and EFS24 (OR=1.93, 95% CI: 1.60-2.38). The association between DTI and outcomes remained significant after stratifying for subtype (EFS HR=1.68, 95% CI: 1.46-1.94; OS HR=1.78, 95% CI: 1.50-2.10) and adjustment for IPI (EFS HR=1.43, 95% CI: 1.24-1.65; OS HR=1.47, 95% CI: 1.24-1.74). In subset analysis, DTI≤14 was significantly associated with inferior outcomes within the subtypes of HG, DH (EFS HR=2.70, 95% CI: 1.82-4.01; OS HR=2.97, 95% CI: 1.92-4.60); HG, NOS (EFS HR=2.07, 95% CI: 0.93-4.60; OS HR=2.36, 95% CI: 1.03-5.43); and DLBCL, NOS (EFS HR=1.51, 95% CI: 1.27-1.78; OS HR=1.52, 95% CI: 1.45-1.85). Analysis was limited in other subtypes due to number of events. Notably, within the subset of patients with DTI>14, there was no significant difference in EFS between subtypes for DLBCL, NOS (EFS24=80%, EFS HR=ref), HG, DH (EFS24=73%, EFS HR=1.26, 95% CI: 0.92-1.73) and HG, NOS (EFS24=83%, EFS HR =0.84, 95% CI: 0.40-1.78), logrank p=0.29; similar results were observed for OS (p=0.22). Conclusions: Patients requiring early initiation of therapy for aggressive B-cell lymphoma represent a distinct population of patients with more aggressive clinical features and inferior outcomes. In patients with longer DTI, high grade subtypes had similar outcomes to DLBCL, NOS. Efforts should be made to include patients with anticipated short DTI in clinical trials and translational studies to fully capture the spectrum of patients with aggressive B-cell lymphoma.

Introduction Lymphoid malignancy (LM) is a heterogenous neoplasm with respect to biology, aggressiveness, and treatment with over 100 subtypes, including Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM). Genome-wide association studies have identified common variants associated with risk of specific LM subtypes, but less is known about the contribution of rare inherited pathogenic variants (PV) in the genetic architecture of LM risk. Rare PV have been shown to contribute to the genetic architecture of solid tumor cancer risk, many of which have been found in genes that are important to the DNA-damage repair (DDR) pathway (e.g., BRCA1, BRCA1, ATM). Here, we investigated the prevalence of PV in cancer predisposition genes regularly included on multi-gene panel testing based on NCCN guidelines and correlated with risk of LM overall and by common subtypes. Methods In this association study, cases were newly diagnosed lymphomas (excluding chronic lymphocytic leukemia) from Mayo Clinic who were enrolled between 2002 and 2015 in the Lymphoma SPORE Molecular Epidemiology Resource (MER) and MM from Mayo Clinic enrolled primarily between 1998 and 2022 in a clinical registry. Controls were from the Mayo Clinic Biobank who were enrolled between 2009 and 2016, from which we excluded individuals with a history of hematologic malignancy. All participants provided a blood sample for whole exome sequencing, performed by Regeneron on an Illumina NovaSeq panel (mean coverage of 48X). Variants were called using GATK v4 and variant annotation was performed using BioR. All loss-of-function variants (i.e., nonsense, frameshift, and consensus splice sites) and pathogenic missense in 19 cancer predisposition genes with a minor allele frequency < 0.5% were included in the analyses. Logistic regression was used to estimate odds ratio (OR) and 95% confidence intervals (CI) for the association between mutation status by gene (burden test) and risk of LM overall, and by subtype that had more than 5 mutation carriers. All analyses were adjusted for age (at diagnosis for cases and at enrollment for controls) and sex. Results A total of 6990 cases and 42432 controls were included. Median age was 63 years for both cases and controls (case range 18-94 years, control range 18-99 years). Males accounted for 58.5% (n=4090) of the cases and 41.7% (n=17762) of the controls. MM accounted for 31% (n=2138) of the cases, followed by diffuse large B-cell lymphoma (DLBCL, n=1146) and follicular lymphoma (FL, n=1132) each accounting for 16% of cases. CHEK2 (1.0%), ATM (0.4%), BRCA2 (0.4%), and BRCA1 (0.3%) had the most PV carriers in controls; these frequencies are in the range of published control populations. A total of 1816 (3.7%) individuals had a PV across the 19 genes, with 4.7% of cases and 3.5% of controls carrying any PV (OR=1.34, 95% CI: 1.18-1.51). ATM (OR=1.86, 95% CI: 1.36-2.49), CHEK2 (OR=1.74, 95% CI: 1.42-2.13) and TP53 (OR=9.07, 95% CI: 4.51-18.87) were all significantly associated with increased risk of LM overall (Figure 1). When investigating subtypes (Table 1), CHEK2 (OR=1.93, 95% CI: 1.23-2.89) and TP53(OR=10.97, 95% CI: 3.06-31.43) were significantly associated with DLBCL. ATM (OR=2.22, 95% CI: 1.13-3.90) was significantly associated with FL. ATM (OR=1.97, 95% CI: 1.16-3.12), CHEK2 (OR=1.75, 95% CI: 1.24-2.41) and TP53 (OR=7.67, 95% CI: 2.43-20.72) were significantly associated with MM and ATM (OR=8.62, 95% CI: 4.47-15.12), NBN (OR=6.94, 95% CI: 2.41-15.76) and TP53 (OR=38.30, 95% CI: 10.27-116.69) were significantly associated with mantle cell lymphoma (MCL). When subset to LM cases overall, there was no evidence of enrichment for young onset (age <60 years), male sex, or family history of hematologic malignancy between PV carriers and non-PV carriers. However, FL cases with an ATM PV tended to be less than 60 years (OR=3.21, P=0.09) compared to non- ATM PV carriers. Similarly, MM cases with a TP53 PV tended to be less than 60 years of age (OR=7.39, P=0.07) compared non-carriers. Discussion In this large case-control study, PV in established cancer predisposition genes were associated with increased risk of LM overall, demonstrating that rare inherited variants may play an important etiologic role. This study also suggests that PV in cancer predisposition genes may be subtype specific. These results will help inform LM risk for individuals who undergo genetic testing of cancer predisposition genes.

Background: Tumor mutational burden (TMB), defined as the number of nonsynonymous mutations per megabase (Mb) in the coding regions of a tumor genome, has been associated with improved response to immune checkpoint blockade treatments and more broadly with overall survival (OS) in many cancers. Limited prior studies have found that TMB is higher in diffuse large B-cell lymphoma (DLBCL) compared to many other cancers. However, only two studies have evaluated TMB and prognosis in newly diagnosed DLBCL patients. The prognostic role of TMB in diffuse large B-cell lymphoma (DLBCL) remains unclear as prior studies have been limited to panel sequencing of cancer genes and/or lacked matched germline-tumor samples for filtering. Methods: We characterized TMB from whole exome sequencing (WES) in newly diagnosed DLBCL patients with matched diagnostic tumor-normal samples prior to treatment with standard immunochemotherapy (IC). Tumor DNA was extracted from formalin-fixed, paraffin embedded tissue sections and germline DNA from peripheral blood. We evaluated the association between TMB and event-free (EFS) and OS using Cox regression adjusted for the international prognostic index (IPI) and other factors including cell of origin (COO), MYC double hit (DH) with BLC2 or BCL6 by FISH, and TP53 mutation status. EFS and OS were defined as time from diagnosis to earliest of treatment failure (EFS only), death, or last follow-up; EFS at 24 months (EFS24) was also modeled as a marker of early aggressive DLBCL. An optimal high/low TMB cutpoint was determined based on EFS using maximally selected rank statistics; sensitivity analyses used an 20/80 percentile to define the threshold. We also evaluated the association of driver tumor mutational load (driverTML) with EFS and OS, defined as the total number of mutations in 292 DLBCL driver genes. Results: In the analysis cohort of 394 DLBCL patients, the median age at diagnosis was 65 years (interquartile range: 56-73), 43% were female, 62.2% had IPI 0-2, and 57.4% germinal center B-cell COO. MYC was DH in 7.5% and TP53 was mutated in 16.2% of patients. Through a median follow-up of 7.5 years, there were 141 events and 122 deaths. EFS24 was achieved in 75.1% of the cohort; 5-year EFS was 69% (95% CI 64-74%) and 5-year OS was 75% (95% CI 71-80%). Median TMB in our cohort of DLBCL patients was 3.6 mutations/Mb, which was the fifth highest compared with 32 cancers in The Cancer Genome Atlas. As a continuous variable, increasing TMB (mutation/Mb) was associated with superior EFS (HR=0.89, 95% CI 0.81-0.98) and OS (HR=0.89, 95% CI 0.81-0.99) after adjustment for IPI. Spline analyses confirmed linear associations of TMB with EFS and OS. The optimal modeled cutpoint based on EFS was 4.5 mutations/Mb, with 31% classified as high TMB (>4.5). No significant ( P >.05) differences were observed between high and low TMB patients with clinical (i.e., age, sex, IPI category) or molecular (cell of origin, MYC DH, TP53 mutated) factors. In Cox regression, high-TMB was significantly protective for EFS and for OS compared to low-TMB after adjustment for each clinical factor ( Figure 1), with simultaneous adjustment for all these factors associated with superior EFS (HR=0.52, 95% CI 0.33-0.84) and OS (HR=0.59, 95% CI 0.36-1.00). TMB (high/low) combined with IPI (0-2, 3-5) was significantly ( P =.001) associated with EFS in Kaplan-Meier analysis ( Figure 2). Among patients with IPI 3-5, high TMB was significantly associated with superior EFS (HR=0.47, 95% CI 0.27-0.81) and OS (HR=0.57, 95% CI 0.33-0.99). Among patients with IPI 0-2, we also observed longer EFS (HR=0.62, 95% CI 0.34-1.11) and OS (HR=0.62, 95% CI 0.32-1.20) in high TMB patients, although the associations were not statistically significant ( P >.05). In sensitivity analyses, a 20/80 percentile TMB threshold found similar results for EFS (HR=0.64, 95% CI 0.41-1.03) and OS (HR=0.69, 95% CI 0.42-1.12) as in our main analyses. TMB and driverTML were significantly correlated ( R=0.65, P <10 -16) and we found similar effect sizes for EFS (HR=0.45, 95% CI 0.22-0.91) and OS (HR=0.55, 95% 0.27-1.13) as in our main analyses. Conclusions: In a large and well-defined cohort of IC treated DLBCL patients, we found DLBCL patients with higher TMB had superior EFS and OS after adjustment for other clinical and molecular prognostic factors, and the prognostic association for TMB was robust to threshold and gene set.

Background: Bendamustine and rituximab (BR) is a standard-of-care first-line (1L) therapy for older or unfit patients with mantle cell lymphoma (MCL). The SHINE trial compared BR with rituximab maintenance plus ibrutinib vs placebo in patients ≥65 years old and showed that the ibrutinib arm had significantly improved progression-free survival (PFS; median 80.6 vs 52.9 months) but similar overall survival (OS; 57% vs 55% at 7 years) compared to the placebo arm. Whether sequential treatment with BR in 1L and a Bruton's tyrosine kinase inhibitor (BTKi) in second-line (2L) can result in a similar cumulative PFS compared to 1L BR plus BTKi combination therapy is unknown. To provide insight to this question, we modeled observational data to evaluate MCL outcomes after 1L BR and 2L BTKi therapy in the BTKi era. Methods: Patients with MCL who received 1L BR with or without rituximab maintenance in 2014-2020 at one of the 27 participating centers were included. Exclusion criteria included participation in the SHINE or ECHO trials, any additional 1L therapy other than BR (with or without rituximab maintenance), and stem cell transplant consolidation after 1L BR. Baseline characteristics, treatment, and follow-up data were abstracted by chart review. Event-free survival (EFS) was defined as time from index line treatment start to the first event (progression, relapse, retreatment, or death). OS was defined as time from index line treatment start to death. Using an intention-to-treat (ITT) framework, EFS2 was defined as time from 1L BR start to progression, relapse, or retreatment following 2L BTKi treatment or death. Patients who received a non-BTKi treatment at 2L were censored for EFS2 at 2L treatment start; living patients without an event following 1L BR or 2L BTKi were censored for EFS2 at last follow-up. Results: A total of 618 patients with MCL who received 1L BR in 2014-2020 were included. The median age was 71 (IQR 65-76) years, and 447 (72%) were male. 59 (11%) patients had an ECOG PS ≥2, 566 (93%) had stage III-IV disease, and simplified MIPI was low in 105 (21%), intermediate in 200 (39%), and high in 202 (40%) patients. The median follow-up following 1L BR start was 57.4 (95% CI 53.8-63.2) months. Response data were available in 580 patients, and the best ORR was 92% (79% complete response [CR] and 13% partial response [PR]). 258 (42%) patients received rituximab maintenance. As of last follow-up, 255 patients were alive and in remission after 1L BR, 92 patients died without 2L therapy, and 271 patients received a 2L therapy. The median EFS was 34.1 (95% CI 31.0-40.0) months. The median OS was 97.8 (95% CI 81.2-NA) months, the 5-year OS rate was 58.6% (95% CI 54.4-63.2), and the 7-year OS rate was 56.7% (95% CI 52.4-61.5) (Fig 1). Among the 271 patients who started a 2L treatment, 203 (75%) received a BTKi at 2L - 101 (50%) ibrutinib, 76 (37%) acalabrutinib, and 26 (13%) zanubrutinib. The median follow-up following 2L BTKi start was 38.5 (95% CI 31.3-45.1) months. Response data were available in 171 patients, and the best ORR was 64% (36% CR, 28% PR). The median EFS was 10.7 (95% CI 7.7-14.0) months, and the median OS was 24.8 (95% CI 17.3-33.1) months with 2L BTKi therapy (Fig 2). By ITT analysis, the median EFS2 following 1L BR and 2L BTKi was 72.1 (95% CI 56.7-97.8) months (Fig 1). A subset analysis of patients aged ≥65 years (n=471; 198 [42%] received rituximab maintenance) showed similar results. The median EFS with 1L BR was 32.7 (95% CI 29.1-36.3) months. The median OS was 81.5 (95% CI 65.0-NA) months, and the 7-year OS rate was 53.3% (95% CI 48.3-58.7). 208 patients received a 2L therapy, 163 (79%) with a BTKi. The median EFS was 11.5 (95% CI 7.6-15.8) months, and the median OS was 21.0 (95% CI 14.0-29.6) months with 2L BTKi therapy. By ITT analysis, the median EFS2 following 1L BR and 2L BTKi was 58.0 (95% CI 50.2-77.0) months. Conclusion: In this multicenter retrospective study, initiation of 1L BR (with or without rituximab maintenance) resulted in a 7-year OS of 57%. Median EFS2 for sequential 1L BR and 2L BTKi was 72.1 months. In context, the SHINE study reported a median PFS of 80.6 months in the BR (with rituximab maintenance) plus ibrutinib arm and a 7-year OS of 57% in the ibrutinib arm and 55% in the placebo arm, where 39% of patients received a BTKi in 2L. Within the constraints of observational data, our results provide support for sequential use of BR in 1L and BTKi in 2L for patients with MCL.

Background: High Grade B cell Lymphoma (HGBL) with MYC and BCL2 and/or BCL6 rearrangements(R) was introduced as an entity in 2016 by the WHO revised 4 th edition. In 2022, both the WHO 5 th edition (beta version) and the International Consensus Classification (ICC) separated DHL- BCL2 (+/- BCL6-R)from DHL- BCL6 given differences in biology . However, while the ICC has maintainedDHL- BCL6 as a provisional entity, the WHO has removed the category, thus removing the requirement to FISH for BCL6-R in this setting. Clinical data on DHL- BCL6 is much more limited, as these cases represent only 10-20% of DHL and have been combined with BCL2-R cases in prior studies. Outcomes are variable in retrospective studies with no consistent data on prognosis or optimal therapeutic strategies. By retaining the category of DHL-BCL6 as a provisional entity, the ICC emphasized the need for further, multicenter, prospective studies evaluating the clinical and biological features of this disease. We herein report a comprehensive comparison of clinical characteristics and outcomes in patients with DHL- BCL6 compared to diffuse large B-cell lymphoma (DLBCL), not otherwise specified (NOS); DLBCL with MYC rearrangement only; DHL- BCL2; and HGBL, NOS in a large, multicenter, prospective cohort of patients from Lymphoma Epidemiology of Outcomes (LEO). Methods: Adult patients with newly diagnosed large B-cell or HGBL were enrolled within 6 months of diagnosis at one the 8 LEO cohort academic medical centers in the US between 2015 and 2020. Baseline characteristics were abstracted at the time of diagnosis per protocol. Based on FISH data patients were further sub mgrouped into DLBCL, NOS (without MYC rearrangement); MYC-R DLBCL, NOS; HGBL, NOS; DHL- BCL2 and DHL- BCL6. Event-free survival (EFS) was defined as the time from diagnosis until progression/relapse, retreatment, or death. Overall survival (OS) was defined as the time from diagnosis until death due to any cause. Results: A total of 1526 eligible patients were identified during this time period. All FISH data was available at the time of diagnosis and the choice of treatment was based on physician discretion. Median age at diagnosis was 63 years (IQR 53-72), with 148 (10%) patients in the AYA category, and 128 (8%) patients > 80 years. 58% (891) were male, 11% self identified as Hispanic or Latino, and 7% as Black/African American. The median diagnosis to treatment interval (DTI) was 20 days (IQR 12-32), and 33% had DTI < 14 days. The FISH-based subgroups were MYC-negative DLBCL, NOS (N=1146, 75%), MYC-R DLBCL,NOS 227 (N = 96, 6%), DHL- BCL2 (N=154, 10%), DHL- BCL6 (N=38, 3%), and HGBL, NOS (N=92, 6%). When available, COO by Hans algorithm was 92% GCB in DHL- BCL2 and 50% GCB in DHL- BCL6. Clinical characteristics can be found in the table. At a median follow-up of 49 months (IQR 36-67), 490 patients (32%) had an event and 356 patients (23%) died. EFS at 24 months (EFS24) was 75% (95% CI: 73-77). Patients with DHL- BCL6 were younger at diagnosis (median 60 years), had more extranodal site involvement (40%), more often stage III/IV disease (70%), and more often treated with a higher intensity regimen than R-CHOP (69%) compared to DLBCL,NOS and MYC-R DLBCL. DHL- BCL6 also had fewer patients that were males (47%), with DTI <=14 days (33%), NCCN IPI ≥ 4 (45%), elevated LDH (53%) than HGBL, NOS and DHL- BCL2. The 2-year EFS and OS rates were noted to be significantly better in the DHL- BCL6 (EFS 79%, 95% CI: 67-93; OS 92%, 95% CI: 84-100) as compared to DHL- BCL2 (EFS 58%, 95% CI: 50-66; OS 70%, 95% CI 63 - 78) and HGBL, NOS (EFS 74%, 95% CI: 65-84; OS 74%, 95% CI: 65-84 ), (Figure 1) but were comparable to that of DLBCL, NOS (EFS 78%, 95% CI: 76-81; OS 87%, 95% CI: 86-89). Conclusions: Our data support separating DHL- BCL6 from DHL -BCL2 as these patients form a unique subgroup with some clinical characteristics comparable to both DLBCL, NOS as well as HGBL, NOS and DHL- BCL2 subtypes. In this cohort, clinical outcomes are more comparable to DLBCL, NOS than DHL- BCL2 or HGBCL, NOS. More frequent use of intensive chemotherapy in DHL- BCL6 compared with DLBCL may account for this finding, although larger multicenter studies are needed. Our results support continued identification of DHL- BCL6 in the clinical setting to better understand optimal therapy and biology of this cohort.

Introduction: Histologic transformation (HT) from follicular lymphoma (FL) to an aggressive lymphoma is infrequent but has unfavorable outcomes. Sarkozy et al. (J Clin Oncol, 2019) reported that approximately half of FL-related deaths within the first decade of diagnosis occurred following HT. Our recent analysis showed heterogeneous outcomes with median overall survival (OS) of 61 months (Day et al., ASH, 2022). Prognostic tools post HT would be clinically useful but development has been limited by small cohort sizes. Factors previously associated with outcomes following HT have included age, time to progression, prior therapy, anthracycline exposure, and early HT. Utilizing the Lymphoma Epidemiology of Outcomes (LEO) Consortium of Real World Evidence (CReWE), we describe patterns of care and evaluate other prognostic factors following HT. Methods: This multicenter observational cohort consists of prospectively enrolled patients in the LEO Cohort, and patients with HT retrospectively identified at LEO centers. Patients diagnosed with biopsy proven grade 1-3A FL at diagnosis, and a subsequent biopsy showing HT to an aggressive lymphoma (FL grade 3B, diffuse large B cell lymphoma [DLBCL], or high-grade B cell lymphoma [HGBCL]) between 2002-2022, were eligible for the study. Patients with a component of FL grade 3B, DLBCL, or HGBCL at diagnosis were excluded. HGBCL was defined as double or triple hit or another aggressive subtype. OS was defined as the time from HT until death from any cause and calculated via Kaplan-Meier. Associations between clinical factors at time of HT and/or diagnosis and OS were evaluated using Cox models. Cause of death was evaluated using a competing risk approach. Results: Overall, 328 patients were confirmed with HT during the study period, 41% were female, and the median age at HT was 63 years (interquartile range [IQR] 56-70). The median time from diagnosis to transformation (TDT) was 35 months (IQR 12-66). At HT, 88% had advanced stage disease (III-IV) and LDH was elevated in 49%, while few patients exhibited B symptoms (5%) and ECOG performance status was >2 in 9%. 23% did not receive systemic therapy prior to HT. For those with prior therapy, the median time from prior therapy to HT was 15 months (IQR 7-39). The most frequent treatment regimens following HT were CD20-CHOP (42%), followed by platinum-based salvage therapy (20%), R-EPOCH (10%), CD20-Benda (8%), R-Mono (4%), and R-Gem-Ox (3%). 50 (15%) patients underwent consolidation with autologous stem cell transplant, 3 underwent allogeneic transplant (30 platinum-based, 15 CD20-CHOP, 5 R-EPOCH, 3 Other), and 2 received CAR T-cell therapy (Figure 1). After median follow-up of 85 months from HT, 170 patients had died; 5-year OS was 52% and median OS was 65 months (95% CI: 55-107). Among 160 patient deaths, cause was most often lymphoma-related (progression, n=107 [63%]; therapy-related, n=14 [7%]) compared to non-lymphoma (n=20, 13%) or missing/unknown causes (n=29, 17%). Clinical factors at the time of HT that were associated with worse OS include: ECOG PS >2, age ≥70, IPI 3-5, and shorter TDT (<24 months), hemoglobin <10 g/dl and elevated LDH. A transformation to HGBCL was also associated with inferior OS (Table 1). OS did not significantly differ by gender, BMI, stage, presence of B-symptoms, absolute lymphocyte count, number of extranodal groups, presence of bulky disease at HT, or response to prior FL treatment. Factors at the time of FL diagnosis that were associated with decreased OS after HT included FLIPI score 3-5 (high risk), FLIPI 2 (moderate risk), and FL grade 3A at diagnosis. Exposure to any systemic therapy for FL prior to HT was associated with shorter OS, with the worst outcomes in patients receiving an anthracycline prior to HT. POD24 to frontline immunochemotherapy was associated with inferior OS after HT (Table 1). Conclusions: Patterns of care in Transformed FL are heterogeneous and vary greatly in intensity. These data confirm previous reports that age, early HT, and any systemic therapies prior to HT are negative prognostic indicators for OS. At HT elevated LDH, low hemoglobin, POD24 status, poor performance status, and HT to HGBCL were associated with poor outcomes following HT. These data provide a basis for future prognostic indices to identify patients with highest risk of lymphoma related mortality for whom study of novel treatments is greatly needed.

Aim: Patients with R/R LBCL after first-line treatment have poor prognosis. Multiple novel therapies have been approved for R/R LBCL in recent years, but CIT regimens are still commonly used. This study evaluated the effectiveness of CIT and novel therapies in 2L+ in patients with R/R LBCL and the association between patient clinical characteristics and real-world outcomes. Methods: This was a multi-site retrospective observational study of patients aged ≥18 years with R/R LBCL in the Lymphoma Epidemiology of Outcomes (LEO) Consortium of Real-World Evidence (CReWE) cohort (patients followed from 1/1/2015 to 2/15/2023) who were treated with CIT or novel therapy in 2L+. CIT regimens included salvage/palliative chemotherapy, lenalidomide, rituximab, or obinutuzumab, used alone or in combination. Novel therapies included polatuzumab vedotin plus bendamustine and rituximab or variations thereof (i.e., pola-based regimen), tafasitamab plus lenalidomide or variations thereof (tafa-based regimen), and loncastuximab tesirine (lonca). Patients' demographic and clinical characteristics were assessed from the first confirmed R/R disease diagnosis and initiation of 2L+ therapy. When multiple lines of therapy (LOTs) were eligible for inclusion in the analysis, one was randomly selected as the index LOT. Real-world outcomes, determined by investigators at each clinical site, including overall response rate (ORR), complete response (CR) rate, duration of response (DOR), duration of complete response (DOCR), progression-free survival (PFS), and overall survival (OS) were described for all patients in each treatment group and for the subgroup of patients with prior chimeric antigen receptor (CAR) T-cell therapy. Multivariable Cox Proportional Hazards models were used to assess associations between select patient clinical characteristics and real-world outcomes. Results: The study population included patients treated with CIT (N=653), pola-based regimen (N=116), tafa-based regimen (N=55), and lonca (N=42) ( Figure 1A). The median (m) age at date of index treatment initiation across groups ranged from 63 to 74 years. Across groups, most patients had primary refractory disease-i.e., were refractory to the first LOT (69.5% CIT vs. 73.3% pola vs. 58.2% tafa vs. 71.4% lonca), whereas variable proportions had one prior LOT (65.5% vs. 17.2% vs. 43.6% vs. 7.1%) and prior CAR T-cell therapy (5.1% vs. 43.1% vs. 32.7% vs. 47.6%). In the CIT group, ORR was 33.8%, 15.5% of patients achieved CR, mPFS (95% CI) was 1.9 (1.7, 2.1) months, and mOS was 9.1 (8.1, 10.5) months. In the pola group, ORR was 42.2%, 24.1% of patients achieved CR, mPFS was 2.5 (2, 3.2) months and mOS was 7.8 (6.4, 11.8) months. In the tafa group, ORR was 25.5%, 14.5% of patients achieved CR, mPFS was 2.7 (2.1, 4.2) months, and mOS was 8 (5.3, 12.7) months. In the lonca group, ORR was 40.5%, 21.4% of patients achieved CR, mPFS was 3 (2.1, 5.1) months, and mOS was 4.7 (3.7, 10.8) months. Demographics and outcomes for all patients and those who received prior CAR T-cell therapy are summarized in Figure 1A. In the multivariable Cox regression analysis, International Prognostic Index (IPI) risk score ≥3, CIT as the index treatment type, and primary refractory status were significantly associated with time from response to progression/death (P<0.05; Figure 1B). IPI risk score ≥3, CIT as the index treatment type, and primary refractory status were significantly associated with worse PFS. IPI risk ≥3, ≥3 prior LOTs, and primary refractory status were significantly associated with OS. Conclusion: In this large clinical cohort of patients with R/R LBCL with high proportions having primary refractory disease, all common treatments were associated with modest ORR/CR and poor OS. Receiving CIT treatments, higher IPI score, primary refractory status, and higher number of prior LOTs were significantly associated with poor clinical outcomes. A study with larger sample size and longer follow-up may be warranted to further understand the clinical effectiveness of novel treatments. Thus, despite the availability of novel treatments during the study period, these findings highlight the need for more effective treatment alternatives beyond currently available options to improve outcomes.