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Cellular senescence is defined as a state of permanent cell cycle arrest, providing a natural barrier against cancer. However, senescent cells are very metabolically active and secrete a complex mixture of bioactive molecules collectively known as the senescence-associated secretory phenotype (SASP), which play a dual role in cancer biology. While the SASP can suppress tumors by facilitating immunosurveillance, it can also promote tumor progression by fostering a pro-inflammatory milieu, stimulating angiogenesis, enhancing invasiveness, and enabling immune evasion. In Head and Neck Cancers (HNCs), a highly heterogeneous group of malignancies, SASP has emerged as a critical player in disease progression and treatment resistance. Persistent DNA damage response (DDR) signaling drives SASP and thereby contributes to the progression of head and neck cancer by modulating the tumour microenvironment. It influences the tumor microenvironment (TME) by facilitating epithelial-to-mesenchymal transition (EMT), promoting cancer stem cell-like properties, and impairing the efficacy of radiotherapy, chemotherapy, and immune checkpoint inhibitors. These effects underscore the need for targeted interventions to regulate SASP activity. This review presents a comprehensive overview of the molecular mechanisms underlying SASP generation and its effects on HNCs. We discuss the dual roles of SASP in tumor suppression and progression, its contribution to therapy resistance, and emerging therapeutic strategies, including novel senolytic and senomorphic drugs. Finally, we highlight key challenges and future directions for translating SASP-targeted therapies into clinical practice, emphasizing the need for biomarker discovery, and a deeper understanding of SASP heterogeneity. By targeting the SASP, there is potential to enhance therapeutic outcomes and improve the management of HNCs.

Abstract Introduction The International Prognostic Index (IPI) is widely used to stratify risk in large B-cell lymphoma (LBCL) across all ages, with age-adjusted (aa)IPI applied to younger patients. While there have been efforts to develop prognostic indices (PIs) tailored to older patients, few are adopted in clinical practice due to their complexity and reliance on functional assessments, which are not routinely collected in real-world registry datasets. Recently proposed SENIOR-IPI (Dubois, ASH 2024) was developed for older patients with LBCL receiving anthracycline (A)-based therapy. We assessed the performance of standard and novel PIs in patients aged 80+ years and externally validated the SENIOR-IPI. Methods We harmonized and pooled data of patients aged 80+ years with newly diagnosed LBCL from a national registry and two prospective cohorts: NiHiL (Czech Republic, enrolled 2010–2023), LEO (USA; n=222, 2015–2020), and MER (USA; n=77, 2010–2015), forming a cohort of 819 individuals. We included 536 individuals with complete data on IPI components and albumin, including 485 treated with chemotherapy and 397 with A-based regimens (primary cohort). Following PIs were evaluated: IPI, NCCN-IPI, (aa)IPI, and SENIOR-IPI (age per year, aaIPI components, LDH >3x ULN as extra point, and albumin, all weighted six-fold; extranodal involvement excluded due to lack of prognostic significance). Multivariable hazard ratios (HR) were estimated using Cox proportional hazards models; discriminative ability was assessed using C-index and calibration plots. The primary endpoint was overall survival (OS); event-free survival results were consistent (230/357 events were deaths) and are not reported here. Results Among the 397 A-treated patients (median age 82 years, range 80–99), ECOG performance status (PS) 2–4 was observed in 35% of patients, clinical stage III–IV in 67%, elevated LDH in 65% (8% with >3x ULN), >1 extranodal (EN) site in 32%, and albumin levels < 3.5 g/dL in 27%. In multivariable modeling, only age per year (HR=1.07, P<0.01), and clinical stage (HR=1.36, P=0.048) were independent predictors of OS, whereas ECOG PS (HR=1.27, P=0.12), trichotomized LDH by ULN (HR=1.23, P=0.08) and albumin (HR=1.17, P=0.35) were not significant. SENIOR-IPI had the highest discrimination (C-index 0.631) in A-treated patients, outperforming IPI (0.617), NCCN-IPI (0.591), and aaIPI (0.620), with consistent results across cohorts: NiHiL (0.633), LEO (0.619), and MER (0.621). SENIOR-IPI stratified patients into low- (L-Risk, 0–9 points, 28%), low-intermediate (L-Int, 10–19 points, 42%), high-intermediate (H-Int, 20–29 points, 23%), and high-risk (H-Risk, 30–40 points, 7%) categories, with OS medians of 6.3, 3.8, 2.4, and 1.4 years, respectively (P<0.01), and significant separation between L-Int and H-Int (HR=1.47, P=0.02). By comparison, IPI categorized patients as L-Risk (12%), L-Int (24%), H-Int (27%), and H-Risk (37%), with median OS of 8.7, 4.6, 4.8, and 1.9 years, resp. (P<0.01). aaIPI yielded following distributions: 13%, 29%, 37%, and 21%; and median OS: 8.7, 5.3, 3.4, and 1.5 years; P<0.01. NCCN-IPI stratified patients into three groups: L-Int (13%), H-Int (49%), and H-Risk (39%), with respective OS medians of 8.7, 4.1, and 2.5 years (P<0.01). All PIs showed modest overestimation of mortality (calibration slopes: SENIOR-IPI 1.36; IPI 1.24; aaIPI 1.30; NCCN-IPI 1.26; intercept: -0.97, -0.87, -0.92, -0.87, resp.). In the entire cohort (n=536), SENIOR-IPI showed highest C-index (0.651 vs IPI 0.622, aaIPI 0.631, NCCN-IPI 0.606), and stratified patients into L-Risk (26%, 2-year OS: 6.4 years), L-Int (40%, 3.2 years), H-Int (24%, 1.5 years), and H-Risk (10%, 0.6 years). Calibration slope was 1.18 (intercept -0.33). Among patients not receiving chemotherapy, SENIOR-IPI also performed best (C-index 0.759 vs IPI 0.738, aaIPI 0.757, NCCN-IPI 0.728). Conclusion SENIOR-IPI enables effective risk stratification of patients aged 80+ years with LBCL into four prognostically distinct groups, outperforming traditional indices (IPI, NCCN-IPI, aaIPI) in patients receiving A-based therapy, as well as in the entire cohort and in patients not receiving chemotherapy. While its discrimination is superior, modest miscalibration suggests that future recalibration may improve precision. These findings support SENIOR-IPI as a clinically relevant prognostic tool for the elderly LBCL patient population. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

Abstract Background and Significance Diffuse large B-cell lymphoma (DLBCL) and other LBCLs account for 35–40% of non-Hodgkin lymphoma cases in North America, Europe, and East Asia. Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) is the standard first-line treatment for DLBCL, achieving cure rates in approximately 60–70% of patients. However, 30–40% of patients will relapse or become refractory (R/R) to treatment, facing poor prognosis. Patients with high International Prognostic Index (IPI) scores (3–5) and those with IPI 1–2 who have bulky disease and/or very high lactate dehydrogenase (LDH) are recognized as high-risk (HR) subsets with suboptimal outcomes (Maurer et al, ASH 2023, #4512). Novel combination strategies are an area of focus for improving efficacy in this population. GOLCA is a potential, first-in-class, oral CELMoD agent designed for the treatment of lymphoma, with preferential distribution to lymphoid organs and enhanced activity in lymphoma cell lines. GOLCA drives the closed, active conformation of cereblon to induce rapid and deep degradation of Ikaros and Aiolos, leading to direct cell killing (agnostic of cell of origin [COO]) and immunomodulatory activity. In the Phase 1b study CC-220-DLBCL-001, GOLCA in combination with R-CHOP demonstrated a predictable and manageable safety profile with high rates of durable responses, irrespective of COO, in previously untreated aggressive B-cell lymphomas (BCL), including promising activity in HR patients (Amzallag et al, ASH 2024, #579). The median relative dose intensity for GOLCA and CHO components was high (97–99%), indicating uncompromised delivery of curative standard-of-care treatment and combinability. GOLCA ± rituximab has also shown encouraging efficacy and safety in patients with R/R DLBCL (Bachy et al, ICML, #148). These findings support the further study of GOLCA + R-CHOP combination in the Phase 3 setting. Study Design and Methods GOLSEEK-1 (NCT06356129) is a randomized, double-blind, placebo-controlled, Phase 3 study evaluating GOLCA + R-CHOP versus placebo + R-CHOP in patients with previously untreated HR LBCL. Approximately 850 patients with previously untreated LBCL will be randomized 1:1 to either GOLCA + R-CHOP or placebo + R-CHOP. Eligible patients include those with histologically confirmed LBCL per WHO 2022 criteria—including DLBCL (not otherwise specified [NOS], ABC/GCB), high-grade BCL with MYC and BCL2 rearrangements or NOS, T-cell/histiocyte–rich LBCL, or Epstein Barr Virus-positive DLBCL. HR status is defined by IPI ≥3, or IPI 1–2 with HR features: LDH >1.3× upper limit of normal and/or bulky disease (≥7 cm lesion). All patients must have measurable disease as defined by Lugano criteria. Key exclusion criteria are other lymphoma subtypes such as primary mediastinal LBCL; primary cutaneous DLBCL-leg type, grade 3b follicular lymphoma (FL); transformed indolent lymphoma; anaplastic lymphoma kinase (ALK) positive LBCL; primary effusion lymphoma; and Burkitt lymphoma and known or suspected central nervous system involvement. Randomization will be stratified by IPI score (HR 1–2 and 3 vs 4–5) and bulky disease status (≥7 cm vs <7 cm). After a screening period of ≤4 weeks, patients will receive either GOLCA (0.4 mg) or placebo orally once daily for 7 consecutive days in each of 6 cycles, combined with R-CHOP every 21 days. The primary endpoint is progression-free survival (PFS) by investigator assessment per Lugano Response Criteria. Key secondary endpoints include PFS in non–high-grade BCL, event-free survival, independently assessed complete metabolic response, undetectable minimal residual disease by PhasED-Seq (defined as undetectable circulating tumor DNA levels at end of treatment), and overall survival. Patients will be followed up for up to approximately 67 months after beginning treatment. This study is currently recruiting at 309 sites in 36 countries , across the United States, Europe, Latin America, and East Asia. Acknowledgement BMS Artificial Intelligence was used to revise existing text with human author oversight.

Abstract Aggressive B-cell non-Hodgkin lymphomas represent a clinically heterogeneous group of malignancies characterized by rapid progression and varied molecular features. Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive B-cell non-Hodgkin lymphoma and encompasses a biologically diverse group of diseases, now classified into 18 molecular subtypes (Alaggio et al. Leukemia, 2022). While first-line R-CHOP therapy cures approximately 60% of patients (Coiffier et al. N Engl J Med. 2002), those with relapsed or refractory (R/R) disease face poor outcomes. Although CAR T-cell therapies (e.g. axicabtagene ciloleucel, tisagenlecleucel, lisocabtagene maraleucel) have improved outcomes, access remains limited due to logistical and disease-related constraints (Locke et al. N Engl J Med. 2022). More recently, bispecific CD20xCD3 antibodies such as epcoritamab and glofitamab have shown clinical activity in the R/R setting after ≥2 prior lines, with complete response (CR) rates of ~40% (Dickinson et al. N Engl J Med. 2022; Thieblemont et al. J Clin Oncol. 2023). However, treatment sequencing and mechanisms of resistance to CD20-targeted therapies remain areas of active investigation. One emerging resistance mechanism to CD20 bispecific antibodies is the downregulation or loss of CD20 expression, which has been associated with treatment failure and disease progression (Bannard et al. Clin. Cancer Research, 2022). This highlights the need for novel strategies to overcome CD20 resistance. Dapolsertib (MEN1703) is a first-in-class dual PIM/FLT3 kinase inhibitor that targets key oncogenic and survival pathways in hematologic malignancies. PIM kinases (PIM1, PIM2, PIM3) regulate translation, metabolism, apoptosis, and immune modulation. Overexpression and mutations in PIM genes are associated with poor prognosis in DLBCL, particularly in the ABC subtype, and are known to cooperate with MYC and BCL6 (Szydłowski et al. Cancer Res. 2021). Simultaneous inhibition of all three PIMs downregulates MYC and induces marked cytotoxicity in preclinical models. In AML, dapolsertib has demonstrated preliminary clinical single-agent activity, with ~10% CR/CRi reported in the DIAMOND study (NCT03008187; Martinelli et al. Blood Neoplasia, in press). Dapolsertib has also shown strong antitumor activity in lymphoma models, both in vitro and in vivo (Bellon et al. Mol Cancer. 2023). Notably, dapolsertib demonstrated synergy with anti-CD20 antibody, rituximab, providing a rationale for combination strategies (Szydłowski et al. Cancer Res. 2021). The rationale for combining dapolsertib with a CD20 bispecific antibody lies in its potential to modulate survival pathways, sensitize malignant B-cells to immunotherapy, and circumvent resistance mechanisms such as CD20 loss by inducing CD20 expression. JASPIS-01 (NCT06534437) is an ongoing, international multicenter, Phase 2 study evaluating dapolsertib as monotherapy or in combination with glofitamab in patients with R/R aggressive B-cell lymphoma after ≥2 prior lines of therapy. The trial consists of three parts: a safety run-in (Part 1), optional enrichment (Part 2), and a potential randomized comparison vs. glofitamab (Part 3). Part 1 will include 2 groups of patients. Group 1 comprises bispecific-naïve patients randomized to a prospective dose-optimization evaluation of the combination with dapolsertib. Patients receive either 125 mg on a 2 weeks on / 1 week off schedule or 150 mg on a 1 week on / 2 weeks off schedule for up to 12 cycles to investigate optimal therapeutic window. Group 2 comprises patients who exhausted therapeutic standard options and who will receive dapolsertib monotherapy at 125 mg on a 2 weeks on / 1 week off schedule until intolerable toxicity or disease progression. The initial safety run-in (Parts 1 of both groups) informs dose selection for Part 2. Dose continuation in Part 2 will be guided by Data and Safety Monitoring Board safety assessments after ≥2 completed treatment cycles. The primary objectives are to assess safety, tolerability, and preliminary anti-lymphoma activity. Key endpoints include incidence of adverse events, overall/complete response rates, and duration of response. As of July 11, 2025, Part 1 is enrolling in France, Poland, Spain and the UK with additional sites activation ongoing.

Abstract Introduction Although chemo-free regimens are increasingly used in elderly patients with large B-cell lymphoma (LBCL), most still receive conventional chemoimmunotherapy. Patients up to 75–80 years old are usually treated with full-dose R-CHOP, while 80+ patients receive the attenuated R-miniCHOP regimen as standard of care. Prior studies have shown that in patients aged 65+ years, R-CHOP was associated with improved survival based on propensity score matching (PSM) analysis (Al-Sarayfi, Am J Hematol, 2023), though this did not include comorbidity data. Furthermore, no formal studies have focused specifically on 80+ patients. We aimed to perform a PSM comparison of R-CHOP versus R-miniCHOP to better inform treatment decisions in this population. Methods We harmonized and pooled data from 237 LBCL patients receiving chemotherapy with rituximab (out of all 263 80+ patients) from the prospective LEO cohort (USA, n=147; 2015–2020) and NiHiL registry (Czech Republic, single center, n=116; 2010–2023). Of them, 205 (86%) receiving anthracycline(A)-based regimens were included. Baseline characteristics, comorbidities, treatments, and outcomes were collected. PSM (1:1, caliper 0.2) was performed to compare R-CHOP and R-miniCHOP using age, ECOG performance status (PS), clinical stage, lactate dehydrogenase (LDH), and major comorbidities (heart disease, history of stroke, and other recent cancer) as matching variables. The endpoints were overall survival (OS), event-free survival (EFS), and lymphoma-specific survival (LSS, defined as death attributed to lymphoma progression). Results Among 205 A-treated patients, median age was 83 years (range 80–99); 30% had ECOG PS 2–4, 67% clinical stage III–IV, 34% ≥2 involved extranodal sites, 59% elevated LDH, and 58% had International Prognostic Index (IPI) scores 3–5. Median follow-up was 5.5 years; median OS and EFS were 4.1 and 3.4 years, resp. A-based regimens comprised full-dose R-CHOP-like (n=79; 39%; R-CHOP n=74, DA-EPOCH-R n=5) and R-miniCHOP (n=126; 61%). Patients receiving R-CHOP-like regimens had more favorable baseline characteristics (median age 82 vs 83 years, P=0.04; ECOG PS 2–4: 16% vs 39%, P<0.01; IPI 3–5: 46% vs 66%, P=0.03) and a lower, though not statistically significant, comorbidity burden (mean 1.14 vs 1.39; heart disease 35% vs 45%, P=0.22; history of stroke 4% vs 6%, P=0.64; other cancer 6% vs 5%, P=0.87). R-CHOP-like regimens vs R-miniCHOP had superior OS (median 6.3 vs 3.4 years; HR=0.61, 95% CI 0.42–0.90; P=0.01) and EFS (median 5.3 vs 2.1 years; HR=0.58, 95% CI 0.40–0.83; P<0.01), with no significant difference in LSS (2-year 89% vs 82%, HR=0.77, 95% CI 0.39–1.54, P=0.46). To mitigate selection bias, we performed PSM on patients with available baseline characteristics treated with R-CHOP (n=69) and R-miniCHOP (n=121), resulting in 63 matched pairs. Matched cohorts were well-balanced on age (median 82 years in both cohorts; P=0.68), ECOG PS 2–4 (17% vs 19%; P=0.82), IPI 3–5 (52% vs. 59%; P=0.41), and comorbidity burden (mean 1.10 vs. 1.29; P=0.30). The presence of heart disease (40% in both cohorts), history of stroke (5% vs 6%), and cancer (5% vs 6%) were similar. Survival modestly favored R-CHOP, but differences were not significant: median OS 5.3 vs 3.5 years (HR=0.73; 95% CI 0.46–1.15; P=0.17), median EFS 3.8 vs 2.8 years (HR=0.76; 95% CI 0.49–1.18; P=0.23), and 2-year LSS 88% vs 84% (HR=1.09; 95% CI 0.45–2.63; P=0.85). Treatment-related mortality was similar in both cohorts (16%). Among R-miniCHOP patients, survival outcomes did not differ between matched (n=63) and unmatched (n=63) groups (OS P=0.72; EFS P=0.23; LSS P=0.27). Unmatched (n=16) R-CHOP patients had a trend toward improved survival compared to matched (n=63) individuals (OS P=0.10; EFS P=0.049; LSS P=0.24). Conclusion This is the first PSM-based analysis comparing R-CHOP and R-miniCHOP in LBCL patients 80+ years old. Despite inherent limitations of a non-randomized design and limited number of matched patients, our findings – derived from two prospective cohorts – suggest that R-miniCHOP may offer outcomes comparable to R-CHOP, particularly with respect to LSS. While these results support R-miniCHOP as an appropriate frontline option, treatment decisions remain highly individualized. These data may help inform clinical decision-making and provide a basis for designing future trials targeting this population, where R-miniCHOP could serve as a comparator arm. Funding: NU21-03-00411, U01 CA195568.

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.

Abstract Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors. Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS). Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%). In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era). Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598). We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568). Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients. Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.

Abstract Introduction The LEO Comorbidity Index (LCI), comprising ten equally weighted comorbidity categories (respiratory, cardiovascular, digestive, hepatic, renal, autoimmune, diabetes, cancer history, HIV, and stroke), has demonstrated prognostic utility in patients with non-Hodgkin lymphomas. However, its predictive accuracy may vary with increasing age, due to age-related rises in comorbidity burden and physiological vulnerability. To investigate these dynamics, we evaluated the age-stratified predictive performance of LCI in patients with large B-cell lymphoma (LBCL), with a focused analysis on individuals aged 80+ years. We also examined which specific comorbidities most strongly influenced overall survival (OS) and developed a simplified, clinically applicable index tailored to this population. Methods We first included adults ≥40 years with newly diagnosed LBCL and recorded comorbidities from the LEO registry (USA, 2015–2020; n=1,652) to assess age-stratified predictive performance of LCI using the C-index. Next, we focused on patients 80+ years (n=263), pooled from the LEO cohort (n=147) and NiHiL registry (restricted to General Hospital, Prague, Czech Republic, 2010–2023; n=116). Comorbidities were collected from patient self-reports (LEO) and/or medical records (LEO/NiHiL). Univariate and multivariate Cox models were used. The primary endpoint was OS. Results Among the total LBCL population (n=1,652), LCI predictive performance improved by age category with C-index for patients <65 of 0.584, 65–79 years 0.579, and ≥80 years 0.647, indicating stronger discrimination in the 80+ group. Subsequent analysis focused on patients aged 80+ years (n=263; median age 83). Within this cohort, 34% had ECOG performance status (PS) 2–4, 66% stage III–IV disease, 59% elevated lactate dehydrogenase, 35% >1 extranodal site involved, and 58% International Prognostic Index (IPI) score of 3–5. A total of 377 comorbidities were reported, averaging 1.43 per patient (1.22 in LEO; 1.61 in NiHiL). LCI distribution was: 0 points in 24% (n=62), 1 point in 33% (n=88), and 2–5 points in 43% (n=113). Higher LCI scores had worse ECOG PS 2–4: 19% (LCI=0), 33% (LCI=1), and 43% (LCI ≥2; P=0.01), and inferior OS (median 6.9 years LCI=0, 3.0 years LCI=1, and 2.8 years LCI≥2, resp.; P=0.02). Presence of ≥1 comorbidity was associated with shorter OS compared to no comorbidities (HR=1.67, P=0.01). The LCI was an independent predictor of OS after adjusting for age (HR=1.18, P=0.01, C-index 0.623), IPI (HR=1.16, P=0.03, C-index 0.628) as well as for recently proposed SENIOR-IPI (HR=1.14, P=0.049, C-index 0.665). When evaluating individual comorbidities, heart disease (HR=1.54, P=0.01), stroke (HR=1.89, P=0.03), and recent malignancy (HR=1.99, P=0.02) were independent predictors of OS. Based on these findings, we developed a simplified LCI (sLCI) for use in 80+ patients incorporating only the three comorbidities (1 point each). Patients were categorized as sLCI: 0 (49%, n=129), 1 (44%, n=115), and 2–3 points (7%, n=19). sLCI scores 0, 1, 2–3 were associated with ECOG PS 2–4 27%, 37%, and 63%, respectively (P=0.01) and inferior OS: median 5.3 years (0), 2.5 years (1), and 1.4 years (2–3; P<0.01). sLCI remained an independent and strong predictor of OS after adjusting for age (HR=1.71, P<0.01, C-index 0.636), IPI (HR=1.66, P<0.01, C-index 0.635), and SENIOR-IPI (HR=1.60, P<0.04, C-index 0.659). The results were consistent in both NiHiL and LEO cohorts and remained significant among patients treated with anthracyclines (sLCI adjusted for age: HR=1.58, P<0.01, C-index 0.607; for IPI: HR=1.53, P=0.01, C-index 0.623; for SENIOR-IPI: HR=1.51, P=0.01, C-index 0.633). Conclusion Comorbidity burden becomes increasingly prognostic with higher age in LBCL patients. In the 80+ individuals, comorbidities – particularly heart disease, recent cancer, and stroke – have an independent impact on OS. While the original LCI captures the impact of broadly defined comorbidities, its prognostic utility attenuates in the 80+ patients, likely reflecting limited relevance of indolent chronic conditions in this population's constrained survival horizon. The sLCI, focused on the most prognostically relevant comorbidities, offers practical risk stratification. Incorporation of sLCI into clinical decision-making – alongside other prognostic indices – could better identify high-risk individuals and guide treatment strategies. Funding: NU21-03-00411, U01 CA195568.

Abstract Background Secondary central nervous system lymphoma (SCNSL) is a rare but significant complication, affecting approximately 2–10% of patients with diffuse large B-cell lymphoma (DLBCL), often leading to poor outcomes. The CNS-International Prognostic Index (CNS-IPI) remains a widely adopted tool for estimating CNS relapse risk; however, recent advances in molecular profiling and evolving treatment paradigms have challenged the adequacy of CNS-IPI alone in guiding risk assessment. This study evaluates the prognostic relevance of CNS-IPI in conjunction with molecular and clinical factors, specifically cell-of-origin (COO), gene expression, and frontline treatment regimens. The aim is to refine risk stratification and identify patients at highest risk for SCNSL. Method Building on our previous study, we analyzed data from patients with newly diagnosed DLBCL between 2002 and 2023, enrolled in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource. Patients with primary CNS lymphoma, CNS involvement at diagnosis, or who received CNS-directed therapy were excluded. COO was determined using the Hans algorithm and/or Nanostring profiling. Multivariate cause-specific Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for predictors of CNS relapse that were measured at the time of initial DLBCL diagnosis. Cumulative incidence with competing risks and cause-specific Cox models were used to analyze relapse risk. Result We included 2137 patients in our analysis, median age at diagnosis was 63 (IQR 53-72), with 41.6% (n=890) females. The albumin level was below normal in 32.5% (n=350), 64.0% (n=1367) had CNS-IPI of intermediate/high, 37.5% (n=586) had non-germinal center B-cell (GCB) COO, and 14.5% (n=309) were double expressor positive. At a median follow-up of 83 months (IQR 42 -143), 82 (3.8%) SCNSL relapses were observed; the 3 and 5 yrs cumulative incidence for SCNSL from time of DLBCL diagnosis were 3.7% (95% CI 3.0-4.7) and 3.8% (95% CI 3.1-4.8) respectively. In models accounting for death as a competing risk, the 5-year cumulative SCNSL incidence estimate for patients with a CNS-IPI low was 1.5% (95% CI 0.8-2.7), Intermediate was 4.9% (95% CI 3.7-6.4), and high was 6.1% (95% CI 3.8-9.6). The 5-year cumulative SCNSL incidence estimate for patients with non-GCB COO was 5.2% (95% CI 3.6-7.4) compared to 2.4% (95% CI 1.6-3.6; p=0.001) for GCB patients, and the 5-year cumulative SCNSL incidence for double expressor positive patients was 8.6% (95% 5.8-12.6) compared to 1.5% (95% CI 0.8-2.7; p<0.001) for double expressor negative patients. In a multivariable model (including CNS-IPI, COO, double expressor, treatment group, extranodal involvement, and albumin group), CNS-IPI intermediate (HR 2.85 [1.58-5.14]; p<0.001) and high (HR 4.31 [2.15-8.65]; p<0.001), non-GCB COO (HR 2.36 [1.37-4.06]; p=0.002], double expressor (HR 5.56 [2.88-10.73]; p<0.001), and below normal albumin (HR 1.89 [1.02-3.50]; p=0.042) were independently associated with increased risk of SCNSL. The majority of the SCNSL relapse occurred within the first 2 years after DLBCL diagnosis; 81.7% (n=67), with only 6.1% (n=5) occurring after 5 years. For patients who developed SCNSL, the median OS from the time of SCNSL diagnosis was 24 months (95% CI 17-34), with 5 years OS of 31% (95% CI 22-43). These findings are being validated using an external, international cohort, and final analysis will be presented at the time of presentation at ASH. Conclusion In this large, prospectively followed cohort with long-term follow-up data, SCNSL remains a rare but devastating complication of DLBCL, with a 5-year cumulative incidence of 3.8% and it is associated with very poor long-term survival. While CNS-IPI remains a strong predictor of SCNSL risk, our study identifies non-GCB COO and double expressor phenotype as independent, additive molecular risk factors. These findings suggest that current risk stratification tools may underestimate the risk of CNS relapse in molecularly defined high-risk subgroups. Considering the poor outcomes linked to SCNSL and the absence of a connection with frontline treatment types, future research should aim to enhance risk prediction models through molecular profiling and explore prophylactic strategies to reduce the likelihood of SCNSL.