Larson, Melissa C.

Abstract Background: Despite advances in LBCL treatment, 35–45% of patients relapse or have refractory disease highlighting an unmet clinical need. Clinical trials are essential to advancing lymphoma treatment, yet participation remains low – especially among certain populations. We hypothesized that participation in clinical trials as part of first-line therapy is associated with improved survival outcomes and conducted this retrospective study in a multi-center cohort. Methods: The LEO cohort prospectively enrolled newly diagnosed patients with LBCL between 2015 and 2020 at 8 academic medical centers in the United States. LBCL histology's included T-cell/histiocyte rich LBCL, Primary mediastinal LBCL, high grade B-cell lymphoma and DLBCL NOS. Pathology was reviewed and classified by a LEO pathologist. Clinical and treatment data (including trial participation) were abstracted from medical records. The primary outcome endpoint is overall survival (OS) defines as the time from diagnosis to death from any cause or last follow up. Univariable and multivariable Cox proportional hazards models were used to evaluate the association between OS and therapeutic trial participation. Univariable models assessed each baseline covariate, with and without interaction with trial participation. The multivariable model adjusted for age, sex, race/ethnicity, diagnosis to treatment interval [DTI], and IPI, including an interaction between IPI and trial participation which was justified per minimal Akaike information criteria. All models clustered on institution. Results: Among the 2636 patients with LBCL, the median age was 63 (range 18 – 99), 57% were male, 75% non-Hispanic white (NHW), 12% Hispanic (H) and 7.3% African American (AA), 62% had Stage III/IV disease, and 214 (8.0%) participated in a clinical trial as part of first line therapy. Overall, between ages 18 – 80, clinical trial participation increased with age (55 % in ages 18-30 vs 11% in ages 71-80) but dropped significantly for patients > 80 (3.4%). There were no significant differences in the rate of trial participation by sex (male 8.6 % vs female 7.5%; p=0.35), race/ethnicity (NHW 8.9% vs H 5.5% vs AA 6.3%; p=0.061), body mass index (underweight [<18.5] 4.5% vs normal [18.5-24.9] 7.7% vs overweight [25-29] 8.3% vs obese (>30) 8.5; p = 0.75) or Rural-Urban Continuum Codes (Metro[1-3] 8.5% vs non-metro Urban [4-6] 7.6% vs non-metro Rural [7-9] 5.4 %; p=0.49). Patients with advanced disease more commonly participated in a trial. Most patients received systemic treatment (98%), with 94% of patients receiving an anti-CD20 antibody and 91% of patients receiving anthracycline-based therapy. Importantly, there was no difference in anthracycline use in trial participants vs nonparticipants (92 vs 91%; p=0.53). Patients with high IPI scores [3-5] were more likely to participate on trials compared to those with low scores [1-2] (8% vs 5.9% respectively, p= 0.012). Patients who participated in clinical trials had significantly longer median DTI (26 days vs 21 days; p <0.0001) and had a significantly lower number of comorbidities compared to non-participants (mean 0.55 vs. 0.69; p=0.032). Among patients with low IPI (0–2), 5-year OS was 89% trial participants (CTP) compared to 82% for non-participants (CTNP). Among patients with high IPI (3–5), 5-year OS was 78% for CTP vs 60%for CTNP. The multivariable Cox model demonstrated a significant interaction between trial participation and IPI, with trial participation with low IPI having a non-significant hazard ratio (HR) of 0.87 with 95% CI (0.57,1.32), while trial participation with high IPI had a significant HR of 0.57 (0.44, 0.74). Additionally, increased age, male sex, black race, and lower DTI were associated with increased hazard. Conclusion: Patients at high risk of poor outcomes such as those with advanced age (80+), higher comorbidities burden, and those needing more urgent therapy (shorter DTI) were less likely to participate in clinical trials. In this multi-institutional cohort of patients with LBCL treated at academic centers, frontline trial participants had outcomes that were equivalent or better than those receiving standard care. These finding underscore the value of clinical trial participation even in the frontline setting and support trial designs that expand inclusion- allowing participation of patients who are older, medically complex or in need urgent therapy.

Abstract Introduction: THRLBCL is a rare disease accounting for less than 10% of all diffuse large B-cell lymphoma (DLBCL) subtypes. THRLBCL was associated with poor outcomes in the pre-rituximab era, with limited contemporaneous data. Optimal frontline treatment remains unclear with some studies advocating for intensive regimens. The goal of this international study is to analyze the survival and treatment-related outcomes in patients with newly diagnosed THRLBCL treated with rituximab-containing chemotherapy and to compare with a DLBCL, not otherwise specified (NOS) cohort. Methods: THRLBCL and DLBCL patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) (NCT02736357) (7/2015 to 5/2020), Molecular Epidemiology Resource (1/2010 to 6/2015), and Czech Lymphoma Study Group project (NiHiL) (NCT03199066) (2/2010 to 11/2023) were analyzed. Diagnosis was made in dedicated hematopathology centers in both registries. We excluded patients with prior nodular lymphocyte-predominant Hodgkin lymphoma, central nervous system involvement, and not treated with rituximab-containing therapy. Event-free survival (EFS) and overall survival (OS) were estimated by Kaplan-Meier.Univariate associations were derived via Cox model and multivariate models were constructed by forward selection of significant variables with P≤0.05. Propensity score matching (1:5, caliper 0.2) between THRLBCL and DLBCL NOS patients was performed using IPI score components and treatment as covariates. Results: We identified 158 patients (LEO: 67 and NiHiL: 91) with THRLBCL. Among them, 140 patients received rituximab-containing regimens and were included in this analysis. Median age was 58 years (range, 19-89) with 57% aged ≤60 years. Most patients were male (n= 88; 63%) and had ECOG performance status (PS) of 0-1 (n= 111; 79%), stage III-IV (n= 111; 79%), elevated LDH (n= 92; 66%), and B symptoms (n= 84; 60%). Fifty (36%) patients had ≥2 extranodal (EN) sites, mostly liver (n= 39; 28%) and lung (n= 16; 11%), bone marrow (BM) involvement was observed in 26% (n= 37). Bulky disease (≥7.5cm) was present in 50 (36%) and IPI score ≥3 in 68 (48%) patients. The median diagnosis-to-treatment interval was 23 days (IQ range, 13-38.5). Frequent regimens were R-CHOP (n= 106; 75.7%), followed by intensive regimens such as R-MegaCHOP/ESHAP, R-HyperCVAD/MA, and R-CODOX-M/IVAC (n= 15; 10.7%), and R-CHOEP/EPOCH-R (n= 10; 7.14%). With a median follow-up of 3.92 years, the 4-year EFS & OS were 71% and 80%, respectively. Lymphoma was the main cause of death (n= 15; 11%) among 30 events. No difference in 4-year EFS (70% vs. 76%; P= 0.55) & OS (80% vs 82%; P= 0.96) were observed between R-CHOP and intensive regimens. Factors associated with shorter EFS and OS in univariate analysis for THRLBCL were ECOG PS 2-4: (HR= 3.3; P<.001 & HR= 5.97, P<.001, respectively); ≥2 EN sites (HR= 1.85, P= 0.043 & HR= 2.54, P= 0.014, respectively); B symptoms (HR= 2.35, P= 0.014 & HR= 2.84, P= 0.023) and IPI score (HR= 1.5, P= 0.002 & HR= 2.16, P<.001). Stage III-IV and BM involvement were associated with shorter OS only (HR= 7.36, P= 0.05 & HR= 2.18, P= 0.036, respectively). Among them, only ECOG PS 2-4 (OS: HR= 3.6, P= 0.003) and B symptoms (EFS: HR= 2.3, P= 0.046) were independent predictors of survival in multivariate analysis. Finally, we compared baseline characteristics and survival between THRLBCL (n= 140) and DLBCL NOS (n= 6099; LEO/MER: 2069 & NiHiL: 4030) treated with rituximab-containing regimens. Patients with THRLBCL were younger (≤60 years: 57% vs. 38%; P<.001), more frequently had ECOG PS 0-1 (79% vs 76%; P= 0.012), stage III-IV (79% vs 63%; P<.001), B symptoms (60% vs 38%; P<.001), and liver involvement (28% vs 7%; P<.001), compared to DLBCL NOS. Subtype was not associated with survival (OS HR= 0.79, P= 0.262 & EFS HR= 0.93, P= 0.662) when adjusted for IPI score. With a median follow-up of 4.89 years in the DLBCL NOS cohort, we observed similar 4-year EFS (71% vs 67%; P= 0.197) & OS between histologies (80% vs 77%; P= 0.125). These results were confirmed in propensity matching for EFS (HR= 0.98, P= 0.897) and OS (HR= 1.07, P= 0.732). Conclusions: In this large international analysis of patients with newly diagnosed THRLBCL contemporaneously treated, we observed similar survival rates compared to DLBCL NOS treated with R-CHOP and intensive regimens. ECOG PS and the presence of B symptoms were independent factors associated with survival.

Abstract Background Previous studies in aggressive B-cell lymphoma demonstrate that patients with shorter diagnosis-to-treatment intervals (DTI) represent those with higher risk disease. This suggests that patients enrolled in clinical trials may carry a selection bias as they often have longer DTI than patients in the general population. This has important implications for clinical research design and the generalizability of clinical trials in aggressive lymphomas. However, the prognostic implications of DTI have not been evaluated in peripheral T-cell lymphomas (PTCL). Therefore, we examined DTI and its association with clinical factors and outcomes in a prospective observational cohort of patients with PTCL from the United States within the LEO (Lymphoma Epidemiology and Outcomes) and MER (University of Iowa and Mayo Clinic Specialized Programs of Research Excellence Molecular Epidemiology Resource). Patients and Methods We evaluated patients enrolled to the MER (2002-2015) and LEO (2015-2020) cohorts with the following forms of PTCL: PTCL-not otherwise specified (PTCL-NOS, n=217), nodal T-follicular helper (TFH) cell lymphoma (nTFHL, n=153), anaplastic large cell lymphoma (ALCL), ALK positive (ALCL, ALK+, n=74), ALCL, ALK negative (ALCL, ALK-, n=95), enteropathy associated T-cell lymphoma (n=18), and monomorphic epitheliotropic intestinal T-cell lymphoma (n=2). Associations of DTI with clinical factors and outcomes were examined using Kaplan Meier and Cox models. Event free survival (EFS) was defined as the time from start of treatment to relapse/progression, start of 2nd line therapy, or death from any cause. Overall survival (OS) was defined as the time from start of treatment until death from any cause. DTI was defined as the number of days between the first diagnostic biopsy and the start of therapy. Patients who were initially observed or had DTI > 100 days were excluded. Results In 559 patients (229 MER and 330 LEO), median age was 60, 34% had IPI>2 and 71% were stage III/IV. 472 (84%) patients initially received anthracycline-based chemotherapy. Median DTI was 23 days (interquartile range (IQR): 12-39) and was similar in MER (21 days, IQR: 11-33) and LEO (25 days, IQR: 14-42). 168 (30%) patients had DTI 0-14 days, 178 (32%) 15-28 days, and 213 (38%) 29-100 days. Overall in the cohort, shorter DTI was associated with a worse 5-year OS (DTI 0-14 days: 43%; DTI 15-28 days: 53%; DTI 29-100 days: 58%, p<0.001) and 5-year EFS (DTI 0-14 days: 31%; DTI 15-28 days: 39%; DTI 29-100 days: 45%, p<0.001). In multivariable analyses, the association of DTI with outcomes remained consistent after adjusting for age and International Prognostic Index (IPI). Shorter DTI was strongly associated with adverse clinical factors, including elevated lactate dehydrogenase levels, poor performance status, B-symptoms, and higher IPI in both cohorts (all P < .003). DTI was not associated with age, sex, or distance from the LEO/MER center (all p>0.3). 6% patients with DTI of 0-14 days received 1L treatment on a clinical trial, compared to 11% with DTI 15-28 days and 13% with DTI 29-100 days, underscoring that patients with lower DTI may be underrepresented in clinical trials. When examining within PTCL subtypes, the association between short DTI (0-14 days) and inferior outcomes was most prominent in PTCL, NOS (OS HR=2.13, 95% CI: 1.52-2.94; EFS HR =1.49, 95% CI: 1.19-1.85). Associations between short DTI and outcomes were weaker in other subtypes: nTFHL (OS HR=1.28, 95% CI: 0.83-2.00; EFS HR =1.22, 95% CI: 0.82-1.81), ALCL, ALK-, (OS HR=1.30, 95% CI: 0.59-2.86; EFS HR =1.32, 95% CI: 0.68-2.56), ALCL, ALK+, (OS HR=1.05, 95% CI: 0.26-4.17; EFS HR =2.12, 95% CI: 0.84-5.26). Conclusion Shorter DTI is associated adverse prognostic clinical factors (LDH, stage, high IPI) and inferior EFS and OS in newly diagnosed PTCL. Patients with DTI ≤ 14 days, which represents approximately 1/3 patients with PTCL, may be underrepresented in clinical trials. Understanding of this selection bias should inform clinical trial design and interpretation. Future studies should consider strategies to minimize barriers to enrollment for patients with low DTI.

Abstract Introduction: Outcomes for FL have markedly improved, and the 10-year (yr) overall survival (OS) for patients (pts) diagnosed in the rituximab era is about 80%. Historically, FL is the leading cause of death in the first decade after diagnosis (dx); however, modern outcomes beyond 10 yrs after dx remain unknown. Here we report long-term outcomes of FL from a large prospective cohort of pts with FL from the rituximab era. Methods: Pts with biopsy-proven FL 1-3A at dx were prospectively enrolled within 9 months of dx from 2002-2015 in the MER. Outcomes of interest were OS, event-free survival (EFS), histologic transformation (HT), and cause of death. HT was defined as subsequent biopsy-proven FL 3B, diffuse large B cell lymphoma, or high-grade B cell lymphoma. Analyses were performed using Cox models and KM curves; cause of death was evaluated using a competing risk approach. A subset analysis was performed in younger (18-59 yrs) vs older (60+ yrs) pts. A landmark analysis was conducted in pts alive at 10 yrs. Results: 1,155 pts with FL 1-3A were enrolled in the MER from 2002-2015. Median age at dx was 60 yrs (IQR 51-69). Clinical characteristics were: 67% stage III/IV, 12% grade 3A, 4% ECOG PS 2-4, and 19% elevated LDH. Initial management was 35% observation (obs), 12% R-monotherapy (R-mono), 39% immunochemotherapy (IC; 43% R-CHOP, 28% R-CVP, 27% BR), and 14% other. FLIPI scores were 40% low, 33% intermediate (int), and 27% high; FLIPI24 risk categories were 49% low, 25% int, and 26% high. At a median follow-up of 14 yrs (IQR 11-18 yrs), 751 events, 148 HTs, and 402 deaths were observed. EFS estimates (95% CI) were: 10-yr: 40% (37-43), 15-yr: 31% (28-35), and 18-yr: 27% (24-31). 15 yr & 18 yr EFS by initial txs were 22% (18-27) & 18% (14-25) for obs, 30% (23-40) & 18% (11-30) for R-mono, and 40% (35-46) & 38% (33-45) for IC. The incidence (95% CI) of HT was 12% (10-14) at 10 yrs, 13% (11-16) at 15 yrs, and 14% (12-17) at 18 yrs. OS (95% CI) for the entire cohort was 77% (75-80%) at 10 yrs, 63% (60-66) at 15 yrs, and 55% (51-59) at 18 yrs. The incidence of non-lymphoma-related death (non-LRD) surpassed lymphoma-related death (LRD) after 12 yrs in pts with known cause of death. Estimates (95% CI) for LRD were 11% (10-13) at 10 yrs, 14% (12-17) at 15 yrs, and 16% (14-19) at 18 yrs, while estimates for non-LRD were at 8% (7-10) at 10 yrs, 17% (15-20) at 15 yrs, and 22% (19-26) at 18 yrs. Among pts diagnosed before age 60, LRD remained the predominant cause of mortality into the second decade following dx, with incidences (95% CI) of LRD vs. non-LRD of 7% (5-9) vs 3% (2-4) at 10 yrs, 10% (8-13) vs 5% (3-8) at 15 yrs, and 13% (9-17) vs 6% (4-10) at 18 yrs, respectively. In patients age >60 non-LRD was the predominant cause of mortality in the second decade. Incidence of LRD vs. non-LRD in those aged ≥60 at dx were 15% (13-19) vs 13% (10-16) at 10 yrs, 18% (15-22) vs 28% (24-32) at 15 yrs, and 20% (16-24) vs 35% (31-41) at 18 yrs, respectively. In the landmark analysis of pts alive at 10 yrs from dx (n=720), median age was 69 yrs (IQR 60-77). 63 pts (9%) had HT prior to landmark. The median number of prior treatments was 1 (IQR 1-2, range 1-8). Risk of death (95% CI) was 19% (15-22) in the next 5 yrs (i.e. 15 yrs from dx) and 29% (24-33) in the next 8 yrs (18 yrs from dx). The risk of LRD vs non-LRD was 4% (3-6) vs 12% (9-15) at 5 yrs and 7% (3-9) vs 18% (10-23) at 8 yrs.Conclusions: Long-term outcomes for pts with FL remain excellent into the second decade from dx. HT risk decreases significantly after 10 yrs, though late HTs still occur. At 15 yrs from dx, 40% of pts remained alive and event-free after 1L IC. Nearly a quarter of pts observed at dx remained treatment-free. The most common cause of death after 10 yrs from dx was from non-lymphoma causes, notably in older pts aging into their 70s and 80s. While younger pts have a lower overall risk of LRD compared to older pts, FL represents the leading cause of death in this population during the second decade following dx. These results provide critical insights into the natural history of FL diagnosed in the modern era.

Abstract Despite a characteristic indolent course, a substantial subset of follicular lymphoma (FL) patients has an early relapse with a poor outcome. Thus far, efforts to identify factors that predict survival have been unsuccessful. However, we and others have demonstrated the prognostic relevance of CD4+ T cells in the tumor microenvironment (TME) of FL and developed a bio-clinical risk model (called BioFLIPI) that offers improved risk stratification (Mondello et al, BCJ 2021). However, the mechanisms defining different BioFLIPI scores remain to be fully understood. To identify the programs associated with the BioFLIPI scores, we first interrogated the RNA-seq of purified B cells from 67 newly diagnosed FL1-3A (BioFLIPI 1 n=21; BioFLIPI 2-3 n=36; BioFLIPI 4 n=10). We found 1,156 upregulated genes and downregulation of 930 genes in BioFLIPI 4 vs 1, including well-known immune molecules such as CD70, IL10RA, CD69, and CCR6 (FDR<0.05). Gene set enrichment analysis (GSEA) using the MSigDB confirmed a negative enrichment in multiple immune response and interferon gamma signatures and revealed striking positive enrichment for cell proliferation and antigen presentation pathways in BioFLIPI 4 compared to BioFLIPI 1 tumors. The same pathways were dysregulated in BioFLIPI 2-3 but a lower magnitude. To investigate the somatic mutations associated with different BioFLIPI scores, we performed WES of the same 67 FLs and further expanded this cohort for a total of 90 patients (BioFLIPI 1 n=26; BioFLIPI 2-3 n=51; BioFLIPI 4 n=13). We found enrichment for mutations in several regulators of the germinal center in BioFLIPI 4 and 2-3, such as MEF2B (p=0.029), FOXO1 (p=0.038) and IRF8 (p=0.035), suggesting the cooperation of multiple oncogenic events promoting lymphomagenesis. In contrast, BioFLIPI 1 tumors harbored a higher rate of mutations in TNFRSF14 gene, known to enhance anti-lymphoma immune response. To investigate whether BioFLIPI modulates immune signatures of the microenvironment, we performed TME deconvolution by applying CIBERSORTx to bulk RNA-seq of these 67 FLs. We found that FLs with BioFLIPI 4 and 2-3 were enriched for CD4+ Tcm exh (p=0.02), Tem exh (p=0.04), Tfhexh (p=0.07) and NK cells (p=0.01) compared to BioFLIPI 1. In line with this data, CyTOF performed on a subset of these patients (BioFLIPI 1 n=12; BioFLIPI 2-3 n=25; BioFLIPI 4 n=6) confirmed progressive increase of CD4+ Tcm exh (p=0.006), Tem exh (p=0.009) and Tfh exh (p=0.025) cells from BioFLIPI 1 to BioFLIPI 4. Single cell RNA/BCR-seq of 21 FLs (BioFLIPI 1 n=6; BioFLIPI 2-3 n=12; BioFLIPI 4 n=3) corroborated a higher abundance of Tem exh, cytotoxic (CTL) Tem exh, Tfhexh and NK cells in BioFLIPI 4 and 2-3. Conversely, CD8+ naïve T cells were prevalent in BioFLIPI 1 tumors. Differential gene expression in T cell clusters from BioFLIPI 4 vs BioFLIPI 1 FL revealed a marked upregulation of multiple immune genes involved in antigen presentation (e.g., HLA-DRB, HLA-DQA, HLA-DPA/B) and immune response (e.g., ETS1, TNFSF8, IL7R). GSEA showed a positive enrichment for antigen presentation signatures and negative enrichment for TNFα signaling and Oxphos metabolism. Similar findings were observed in BioFLIPI 2-3 FLs. Using CellChat analysis, we found a stronger interaction between malignant B cells and Tem exh and CTL Tem exh cells in BioFLIPI 4 and 2-3 vs BioFLIPI 1 tumors. This was linked to an increased strenght of MHCI-CD8 interaction and concordant decrease of MHCII-CD4. Notably, the suppressive BTLA-TNFRSF14 signaling axis was present in BioFLIPI 4 and 2-3 but not in BioFLIPI 1 FLs. This was accompanied by a decreased signaling through TNF/LTA-TNFRSF1B, CD80/CD86-CD28/CTLA4. Linking the BioFLIPI-specific immunogenicity to lymphomagenesis, we found that FL patients with BioFLIPI 4 had two-three folds higher risk of transformation to an aggressive lymphoma (12% vs 7%) or death (21% vs 3%) than those with BioFLIPI 1, suggesting that this immune dysfunction favors the expansion of a dominant tumor clone and promotes a more aggressive form of FL. Collectively, our findings demonstrate that BioFLIPI scores in FL reflect distinct patterns of tumor immunogenicity that shape the TME. Notably, high BioFLIPI scores are paradoxically associated with enhanced antigen presentation alongside a suppressed immune response. This suggests a sustained antigen-specific T cell response that may drive immune exhaustion, promote tumor progression, and ultimately lead to histologic transformation

Abstract Background: Prognostication for patients with non-transformed relapsed/refractory (R/R) follicular lymphoma (FL) is not well defined. Progression of disease within 24 months (POD24) and number of lines of prior therapy are commonly used to benchmark outcomes and for trial eligibility in this space. However, a comprehensive model for risk prediction in R/R FL is lacking. Here we utilize patients from the LEO Consortium for Real World Evidence (CReWE) and Iowa/Mayo Clinic Lymphoma SPORE MER to develop a clinical prediction model for R/R FL. Methods: Patients with grade 1-3A FL were prospectively enrolled at diagnosis in the MER and/or initiated second line or later therapy (2L+) for non-transformed FL at one of the 8 LEO Centers from a previous LEO CReWE study (Casulo et al, Lancet Haem 2022). All available lines of therapy were abstracted; lines of therapy after histologic transformation were not used in the analyses. A management plan of observation was considered as a type of therapy in the 1L setting but not in the 2L+ setting. Clinical variables and outcomes were abstracted at each line of therapy. Variables considered for modeling included demographics, clinical labs, treatment history, and pertinent clinical variables (including FLIPI and FLIPI24 components). Multiple imputation was used to address missing data in modeling; beta-2 microglobulin (B2M) was unable to be imputed due to the amount of missing data. Index therapy was defined as the date of initiation of a line of therapy (2L, 3L or 4L) for non-transformed FL. The primary endpoint for model development was the time from index therapy until the histologic transformation or lymphoma-related death (HT/LD). Cox proportional hazards models were used for model development. Modeling was first performed separately for each line of therapy and then evaluated across lines. Bootstrapping on imputed datasets was used to assess optimism in model performance. Results: N=1001 patients initiated 2L+ therapy and were utilized for modeling. Of these patients, N=654 initiated 3L and N=344 initiated 4L therapy. Median age at index therapy was (60, 61, and 62) for lines 2-4, respectively. Median follow-up by line of therapy was 8.2, 6.1, and 6,1 years and number of HT/LD events for modeling was 272, 154, and 88, respectively. Observed outcomes decreased modestly as the line therapy increased: median event-free (1.6, 1.5, and 1.2 years) and overall survival (17.6 years, 14.5 years, and 12.3 years), for lines 2-4, respectively. 5-year estimates of HT/LD by line of therapy were 21.6% (95% CI: 18.9-24.3), 23.7% (95% CI: 19.9-27.4) and 29.3% (95% CI: 23.3-34.7), respectively. A clinical prediction model was independently developed for each line of therapy; the final model for each line consisted of the same variables: increasing age, male sex, higher LDH, lower hemoglobin, higher white blood cell count, prior immunochemotherapy exposure, and shorter time since initial diagnosis. The parameter estimates for these variables were broadly similar across the different lines of therapy. The model output is an individual patient's risk of HT/LD. Patients with high-risk FLP-R, as defined using the upper quartile of FLP-R risk scores for each line, had observed 5 year HT/LD rates of 43%, 44% and 51% in lines 2-4, respectively. In contrast, patients with the lower quartile of FLP-R risk scores had observed 5 year HT/LD rates of 10%, 6% and 8% in lines 2-4, respectively. The optimism-corrected c-statistic for the FLP-R model across all lines of therapy was 0.685. This added significant information beyond FLIPI diagnosis (c=0.533) FLIPI at index line (c=0.563), the line of therapy (c=0.525), POD24 status (c=0.578), or all 4 variables combined (c=0.614). Conclusions: The FLP-R model identifies a group of patients with non-transformed FL in the R/R setting who are at very high risk of transformation and/or lymphoma-related death across lines of therapy. FLP-R features 4 of the 5 components of the 1L FLIPI24 prediction model (B2M was unavailable for modeling) with the addition of sex, treatment history and time since initial diagnosis. The number of prior therapies is not sufficient to identify high-risk populations for clinical trial enrichment in the R/R FL setting and model discrimination for FLP-R was greatly improved over FLIPI and/or POD24 across lines of therapy. A Shiny app will be provided for model implementation; external validation is planned.

Abstract Introduction Short diagnosis-to-treatment interval (DTI) is associated with aggressive disease biology and inferior outcomes in diffuse large B-cell lymphoma (DLBCL), and is recognized as a potential source of selection bias in clinical trials if not properly addressed. However, its prognostic significance in follicular lymphoma (FL) remains poorly characterized. We aimed to evaluate the prognostic significance of DTI in newly diagnosed FL patients who received frontline (1L) immunochemotherapy (IC), using a large international dataset and an independent external validation cohort. Methods For the discovery dataset, we evaluated patients diagnosed between 2002 and 2018 from ten observational cohorts as part of the FLIPI24 Consortium. External validation was conducted using data from patients enrolled in the Lymphoma Epidemiology of Outcomes (LEO) Cohort between 2010 and 2015. All patients had FL grade 1–3A and received 1L IC within 100 days of diagnosis. Patients with a concurrent DLBCL were excluded. Missing baseline laboratory values were addressed via multiple imputation. The primary endpoint was event-free survival at 24 months (EFS24); secondary endpoint was 5-year overall survival (OS), both calculated from treatment initiation. DTI was analyzed as continuous (via splines) and dichotomized variable (≤14 vs >14 days; as defined in DLBCL). Results In the discovery cohort (n=3,907), median age was 61 years (IQR 53–69), and 50% were male; 49% of patients were high-risk according to FLIPI, 26% according to PRIMA-PI, and 38% according to FLIPI24. Included patients received R-CHOP (54%), R-CVP (26%), or B-R (20%) as 1L treatment, followed by anti-CD20 maintenance in 60%. The median DTI was 30 days (IQR 17–48). Using the 14-day cut-off, 851 patients (22%) had short DTI. These patients had more adverse baseline characteristics, including B symptoms (42% vs 32%, P<0.01), ECOG performance status ≥2 (15% vs 8%, P<0.01), elevated LDH (51% vs 40%, P<0.01), hemoglobin <12 g/dL (30% vs 17%, P<0.01), and elevated β2-microglobulin (56% vs 44%, P<0.01). Prognostic indices (PIs) were also more frequently high-risk in the short-DTI group: FLIPI (56% vs 47%), PRIMA-PI (36% vs 24%), and FLIPI24 (51% vs 34%, all P<0.01). Spline modeling showed a decreasing EFS24 rate with increasing DTI, reaching a plateau at 30–40 days. In logistic regression model, each additional week of DTI improved EFS24 (OR 0.92, P<0.01). DTI attenuated but remained prognostic after adjusting for PIs (OR 0.93 for FLIPI, 0.95 for PRIMA-PI, 0.96 for FLIPI24, all P<0.01). When analyzed as a dichotomized variable, short DTI was associated with inferior EFS24: OR 1.74 adjusted for FLIPI, 1.63 for PRIMA-PI, and 1.53 for FLIPI24 (all P<0.01). The 2-year EFS of short vs long DTI groups was 71% vs 82% (HR 1.50, 95% CI 1.34–1.67, P<0.01), 5-year OS was 80% vs 86% (HR 1.38, 95% CI 1.21–1.56, P<0.01), and the 5-year cumulative risk of histologic transformation was 7.7% vs. 5.4% (P<0.01). In the validation cohort (n=516), median age was 61 years (IQR 52–69 years), 55% were male; 36% of patients were high-risk according to FLIPI; 29% according to PRIMA-PI, and 33% according to FLIPI24. Patients received B-R (59%) or R-CHOP (41%) as 1L treatment. The median DTI was 31 days (IQR 19–48), 84 patients (16%) had DTI ≤14 days. Similar patterns were observed; patients with short DTI had adverse baseline characteristics, PIs, and shorter 2-year EFS (72% vs 84%, HR 1.69, 95% CI 1.13–2.55, P=0.01). DTI remained associated with EFS24 when analyzed as a continuous variable (per week: OR 0.88 unadjusted, 0.90 with FLIPI, 0.89 with PRIMA-PI, and 0.89 with FLIPI24), and dichotomized (≤14 vs >14 days: OR 1.83 adjusted for FLIPI, 1.88 for PRIMA-PI, and 1.73 for FLIPI24). Conclusion Short DTI, defined as ≤14 days (observed in 22% of FL patients vs 46% in DLBCL), is a strong and independent predictor of inferior outcomes in newly diagnosed FL patients treated with IC. While DTI correlates with adverse baseline features and established PIs, it retains independent prognostic value. Although a 14-day threshold is reasonable for risk modeling, DTI contains greater informational value when modeled as a continuous variable. Among PIs, FLIPI24 most strongly attenuated the DTI effect, underscoring its superior discriminative power over FLIPI and PRIMA-PI. Clinical trials designs should mitigate any potential barriers to enrollment of FL patients requiring urgent therapy.

Abstract Background: Rural/nonmetropolitan (nonmetro) counties face known barriers to comprehensive cancer care compared with metropolitan (metro) counties, which may impact the outcomes for lymphoma patients. We evaluated the impact metro vs nonmetro status on outcomes after a diagnosis of non-Hodgkin lymphoma (NHL) in the context of clinical, demographic, and lifestyle factors. Methods: Of 7724 participants enrolled in the prospective LEO cohort study from 2015-2020, 7610 (98.5%) had their county of residence at diagnosis assigned a RUCC (2013) code. We compared outcomes of participants from metro (defined as RUCC 1-3, which are central counties with ≥1 urban areas of ≥50,000) vs nonmetro counties (RUCC 4-9, which are counties with smaller urban areas as well as completely rural). We estimated hazard ratios (HRs) and 95% confidence intervals (CI) from univariable and multivariable Cox models for associations of metro status with overall survival (OS). Cause of death (lymphoma [including treatment related], non-lymphoma, unknown) was assessed using a competing risk approach. Results: Compared with metro counties (N=6096), LEO participants from nonmetro counties (N=1514) were older (median age 64 vs 62 years; p<0.001), more likely to be non-Hispanic white (94% vs 75%; p<0.001) and married (84% vs 75%; p<0.001), and less likely to have completed graduate or professional school education (16% vs 27%; p<0.001). There were no notable differences (>5%) by metro status for sex, employment status, NHL subtype, stage, performance status, abnormal lactate dehydrogenase (LDH), international prognostic index (IPI), number of comorbidities, time from diagnosis to treatment interval (DTI) or participation in a clinical trial. Compared with LEO participants from metro counties, those from nonmetro counties had inferior OS at 5 years (74.5% vs 78.4%; HR=1.23, CI 1.10-1.37; p<0.001). The OS association only slightly attenuated after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.20, CI 1.07-1.34; p=0.002), and held in models that adjusted for clinical prognostic factors (stage, NHL subtype, IPI, DTI), socioeconomic status (SES; education, marital status), health status (comorbidity, frailty), or lifestyle factors (smoking, body mass index). Using a competing risk model, the cumulative incidence of death at 5 years due to lymphoma (16.9% vs 14.1%; p=0.002) and non-lymphoma (5.9% vs 3.9%; p=0.002) was higher for participants from nonmetro vs metro counties, respectively. For participants <65 years, nonmetro vs metro status had inferior OS (HR=1.40, CI 1.17-1.67; p<0.001). This association remained after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.36, CI 1.14-1.63; p<0.001), as well as after adjustment for clinical prognostic, SES, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was higher in participants from nonmetro vs metro counties (15.1% vs 11.5%; p=0.002), while there was no difference by metro status for non-lymphoma related deaths (2.1% vs 1.7%; p=0.47). In contrast, for participants age 65+ years, there was no differences by metro status for OS (HR=1.04, CI 0.91-1.20; p=0.56). After adjustment for age, sex, race/ethnicity and NHL subtype, participants from nonmetro areas had inferior OS (HR=1.12, 0.97-1.29) although this was not statistically significant (p=0.13), and was attenuated in models adjusting for clinical, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was no different in participants from nonmetro vs metro counties (18.9% vs 18.0%; p=0.37), while non-lymphoma related deaths were higher in nonmetro counties (9.9% vs 6.8%; p=0.017). Conclusion: LEO participants from nonmetro vs metro counties had inferior OS overall, although this was predominately observed for younger (<65 years) participants. These associations did not appear to be explained by demographic, NHL subtype, clinical, SES, health status, or lifestyle factors. Of particular note, the risk of death due to lymphoma was higher in nonmetro areas for participants <65 years but not those 65+ years, while the risk of death due to other causes was higher in nonmetro areas for participants 65+ years but not those <65 years. These findings require further study, particularly related to barriers to care, and suggest the potential need for age-specific strategies to optimize outcomes for NHL patients from nonmetro/rural areas.

Abstract Introduction Marginal zone lymphoma (MZL) is an indolent and heterogenous disease. Several prognostic models have been proposed to assess outcomes in MZL, including FLIPI, IPI (primarily designed for overall survival [OS]), and MZL-specific scores such as MALT-IPI (event-free survival [EFS]) and MZL-IPI (progression-free survival). FLIPI24 is a recently developed prognostic index for patients with follicular lymphoma (FL) treated with first-line (1L) immunochemotherapy (IC), identifying a high-risk population with inferior survival and increased risk of lymphoma-related death. FLIPI24 has also demonstrated robust performance in the entire FL population, including patients under observation. This study aimed to evaluate the prognostic utility of FLIPI24 in patients with MZL and to compare its performance with other established indices (FLIPI, MZL-IPI, IPI, MALT-IPI). Methods We pooled harmonized data from newly diagnosed MZL patients with complete available FLIPI24 variables (age, white blood cell count [WBC], hemoglobin [HGB], serum lactate dehydrogenase [LDH], and beta-2-microglobulin [B2M] levels) treated with 1L IC. Data were collected from three prospective international cohorts: NiHiL (Czech Republic; n=897; enrolled 2005–2023), LEO (USA; n=62; 2015–2020), and MER (USA; n=32; 2010–2015), forming a pooled cohort of 991 1L IC-treated patients. The analysis was then extended to include all newly diagnosed MZL patients (n=2,116), regardless of treatment. The primary endpoint in the 1L IC-treated cohort was EFS at 24 months (EFS24), and for all MZL patients, it was OS. Secondary endpoints included OS24 for 1L IC treated cohort, lymphoma-related mortality by FLIPI24 risk groups, and comparative prognostic performance of FLIPI, IPI, and MALT-IPI, by C-statistics; performance of MZL-IPI was assessed on a subgroup of NiHiL patients with available data (n=877 all MZL, n=485 1L IC-treated). Results Among the 991 1L IC-treated patients, the median age at diagnosis was 66 years (range 22–94); 47% were male; 11% had ECOG performance status ≥2, 68% clinical stage III–IV, 42% elevated LDH, 40% IPI 3–5, 42% FLIPI 3–5, and 62% MALT-IPI 2–3. The median B2M level was 2.8 mg/L, WBC 7.0 × 10⁹/L, and HGB 13.1 g/dL. MZL subtypes were: 64% extranodal (EMZL), 22% nodal (NMZL), and 14% splenic (SMZL). Most common 1L IC regimens were R-CVP (46%), R-CHOP-like (32%), R-chlorambucil (9%), and B-R (9%). FLIPI24 stratified patients into low- (18%), intermediate- (37%), and high-risk (45%) groups. High-risk patients were older (median 54 vs 65 vs 71 years for low-, intermediate-, and high-risk groups, respectively; P<0.01), had more frequent adverse baseline features, and were more likely to have the SMZL subtype (2% vs 7% vs 25% for low-, intermediate-, and high-risk groups, respectively; P<0.01). After a median follow-up of 7.2 years, EFS24 was 89%, 85%, and 65% (P<0.01) across low-, intermediate-, and high-risk groups; OS at 2 years was 98%, 97%, and 79%; and OS at 5 years was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 13% in high-risk vs 6% in low-/intermediate-risk groups. FLIPI24 showed better prognostic accuracy for EFS compared with FLIPI, MZL-IPI, IPI and MALT-IPI (C-index: 0.640 vs 0.630, 0.622, 0.620 and 0.603, resp.), as well as for OS (C-index: 0.710 vs 0.672, 0.641, 0.663, 0.652, resp.). Prognostic performance was consistent across MZL subtypes. In the extended cohort of 2,116 newly diagnosed MZL patients (47% receiving IC, 17% rituximab monotherapy, 11% radiotherapy, 8% surgery, 2% antibiotics; 15% observed), FLIPI24 stratified patients into low- (24%), intermediate- (39%), and high-risk (37%) groups. OS at 2 year was 99%, 97%, and 83%, at 5 years it was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 12% in high-risk vs 4% in low-/intermediate-risk patients. FLIPI24 outperformed other indices (OS C-index: 0.754 vs MZL-IPI 0.654, FLIPI 0.700, MALT-IPI 0.694, IPI 0.699). Conclusion FLIPI24 demonstrates strong and consistent prognostic performance across all MZL subtypes, identifying ~40% of patients as high-risk with significantly worse survival and increased lymphoma-related mortality. The FLIPI24 outperforms FLIPI, MZL-IPI, IPI, and MALT-IPI in predicting outcomes and may serve as a practical tool to guide risk-adapted management and selection of patients for novel therapies in MZL. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

PURPOSE Although most patients with follicular lymphoma (FL) can expect an indolent course, progressive lymphoma remains the primary cause of death during the first decade after diagnosis. Progression of disease within 24 months (POD24) of starting first-line (1L) immunochemotherapy defines a high-risk population with poor survival, but better risk stratification at diagnosis is needed. METHODS The FLIPI24 model was developed and internally validated to predict 24-month event rates using individual data from 4,485 patients treated with 1L immunochemotherapy from 10 observational cohorts of FL. Overall and cause-specific survival was further evaluated in FLIPI24 risk groups. External validation in the 1L immunochemotherapy setting was performed using the prospective observational Lymphoma Epidemiology of Outcomes (LEO) cohort (N = 565) and three randomized phase III trials (N = 3,192); extension to all patients with FL (any 1L therapy) was performed in the LEO cohort (N = 1,445) and its Molecular Epidemiology Resource subcohort (N = 1,074). RESULTS The FLIPI24 model uses age and four blood-based variables (hemoglobin, lactate dehydrogenase, beta-2 microglobulin, and WBC count). FLIPI24 showed consistent performance across validation and extension data sets, which was superior to existing prognostic tools. Across the four external immunochemotherapy validation data sets, patients with high-risk FLIPI24 (23%-32% of patients) had significantly higher 24-month event rates (22%-35%) and inferior 5-year overall survival (77%-83%) compared with patients with low-risk FLIPI24 (29%-31% of patients, 24-month event rates: 10%-12%; 5-year OS: 96%-97%). Results were consistent when evaluating lymphoma-related death and when extended to all patients with FL. CONCLUSION The FLIPI24 model robustly stratifies, at diagnosis, patients with FL at increased risk of lymphoma-related death versus patients with very low lymphoma-related mortality during the first decade after diagnosis. FLIPI24 can be used to enrich future clinical trial designs in newly diagnosed FL.