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Syrbu, Sergei

https://orcid.org/0000-0003-4620-7923

Mayo Clinic

University of Iowa

Citations 60

Abstract A049: Spatially resolved microenvironment profiling reveals distinct follicular lymphoma archetypes
Thakkar, Bijal, Wilson, Ashley , Henderson, Jared, Ayers, Amy, Borgschatz, Sara, Harkins, R. Andrew, Lakra, Priya , Cohen, Jonathon B., Russler-Germain, David, Vega, Francisco, Chapman, J., Inghirami, Giorgio, Lossos, Izidore S. , Koff, Jean L., Nze, Chijioke, Martin, Peter, Syrbu, Sergei, Vij, Kiran, Flowers, Christopher R. , Novak, Anne J., Chihara, Dai, Sakata-Yanagimoto, Mamiko, Tobin, Joshua, Green, M, Abe, Yoshiaki , Kizhakeyil, Atish , Feldman, Andrew L. , Henderson, Jared M. , Ayers, Amy , Harkins, R. Andrew , Kaji, Daisuke , Cohen, Jonathon B. , Mou, Eric , Inghirami, Giorgio , Casulo, Carla , Koff, Jean L. , Nze, Chijioke , Syrbu, Sergei , Jaye, David L. , Cerhan, James R. , Novak, Anne J. , Burack, Richard , Sakata‐Yanagimoto, Mamiko , Tobin, Joshua W.D. , Li, Xubin

Blood Cancer Discovery | June 24, 2026 | Volume: 7 | Issue: 3_Supplement | Pages: A049-A049

10.1158/2643-3249.lymphoma26-a049 Get It

Abstract Recent single-cell transcriptomic studies of follicular lymphoma (FL) have revealed heterogeneity among malignant B (MB) cells and selected components of the tumor microenvironment (TME), but have been constrained by relatively small sample sizes and a lack of spatial context. We performed comprehensive cellular profiling and spatial dissection of over five million cells by integrating single-nucleus RNA sequencing (snRNA-seq) from 182 samples (FL, n = 167; control, n = 15) with single-cell spatial transcriptomics (ST) from 386 samples (FL, n = 365; control, n = 21). After stringent quality control, 1,289,073 and 3,968,427 cells from snRNA-seq and ST data, respectively, were analyzed. Unsupervised clustering of snRNA-seq data identified 58 TME cell subtypes. To extend this classification to the ST dataset, we integrated snRNA-seq and ST data by co-embedding them into a shared principal component space, enabling robust batch correction and cell-type label transfer across modalities. Using this supervised annotation framework, ST data recapitulated 54 TME cell subtypes. MB, proliferating MB (MBprolif), and healthy B (HB) cells were classified using sample-level unsupervised clustering in ST. Macrophages exhibited previously uncharacterized heterogeneity in transcriptomic profiles and spatial distribution. We identified CXCL13-expressing macrophage subtypes with high intra- and peri-follicular abundance, termed follicular macrophages (FMs). Non-negative matrix factorization of intrafollicular cell fractions identified five TME archetypes: FM, follicular stroma, two follicular T, and HB archetypes. The FM archetype was enriched for intrafollicular macrophages, including FMs, and showed a significantly higher proportion of grade 3A/3B cases (53.4%) compared to other archetypes (≤16.5%). It was also associated with a higher frequency of high tumor burden requiring treatment initiation rather than a watch-and-wait (WW) approach. Among patients managed by WW, those with the FM archetype showed significantly shorter event-free survival (EFS) compared to those with non-FM archetypes, whereas this association was not observed among treated patients. The percentage of intrafollicular macrophages (IFMP) showed excellent predictive performance for the FM archetype (area under the curve: 0.90). IFMP calculated in a published multiplex spatial protein imaging dataset from an independent cohort of 242 FL patients validated the associations between high IFMP and both pathology grade 3A/3B and shorter EFS in WW patients. Consistently, spatial neighborhood and cell–cell communication analyses revealed co-localization of FMs and MBprolif cells, forming a distinct niche with activated signaling mediated by FM-derived CXCL13, APRIL, and BAFF. Our integrative multi-modal analysis defines previously unrecognized cellular heterogeneity and spatial architecture in FL and highlights macrophage-enriched follicular ecosystems associated with aggressive clinicopathological features, providing a framework for improved biological understanding and patient management. Citation Format: Yoshiaki Abe, Bijal Thakkar, Atish Kizhakeyil, Ashley Wilson, Andrew L. Feldman, Jared Henderson, Amy Ayers, Sara Borgschatz, R. Andrew Harkins, Priya Lakra, Daisuke Kaji, Jonathon B. Cohen, David Russler-Germain, Eric Mou, Francisco Vega, Jennifer Chapman, Giorgio Inghirami, Carla Casulo, Izidore S. Lossos, Jean L. Koff, Chijioke Nze, Peter Martin, Sergei Syrbu, Kiran Vij, David L. Jaye, James R. Cerhan, Christopher R. Flowers, Anne J. Novak, Richard Burack, Dai Chihara, Mamiko Sakata-Yanagimoto, Joshua Tobin, Xubin Li, Michael R. Green. Spatially resolved microenvironment profiling reveals distinct follicular lymphoma archetypes [abstract]. In: Proceedings of the Fifth AACR International Meeting on Advances in Malignant Lymphoma: From Discovery to Clinical Impact; 2026 Jun 24-27; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2026;7(3_Suppl):Abstract nr A049.
Optimizing risk stratification in patients aged 80+ years with large B-cell lymphoma: Comparison of prognostic indices in three pooled international cohorts
Vodička, Prokop , Benešová, Kateřina , Šálek, David, Lossos, Izidore S. , Prochazka, Vit, Šýkorová, Alice , Móciková, Heidi , Prouzová, Zuzana , Ďuraš, Juraj , Steinerová, Kateřina, Mwangi, Raphael , Khurana, Arushi , Galko, Jan , Polgárová, Kamila , Kořen, Jan , Obr, Aleš , Friedberg, Jonathan W. , Kaščák, Michal , Cohen, Jonathon B. , Masar, Michal, Suri, Alexandra, Nowakowski, Grzegorz S. , Hricko, Samuel, Hrušková, Andrea, Flowers, Christopher R. , Bergerova, Veronika, Blahovcová, Petra, Michalka, Jozef , Campr, Vít , Wang, Yucai , Reagan, Patrick Michael , Koff, Jean L. , Mou, Eric , Feldman, Andrew L. , Kahl, Brad S. , Tsang, Mazie , Nze, Chijioke , Maláriková, Diana , Janikova, Andrea , Martin, Peter, Syrbu, Sergei , Belada, David , Suri, Alexandra, Maurer, Matthew J. , Habermann, Thomas M. , Klener, Pavel , Cerhan, James R. , Trněný, Marek

Blood | December 5, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 786-786

10.1182/blood-2025-786 Get It

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.
Performance of molecular classifiers relative to the international prognostic index (IPI) for overall and event-free survival in diffuse large B-cell lymphoma (DLBCL)
Cholack, George , King, Rebecca L. , Mwangi, Raphael , Nowakowski, Grzegorz S. , Ansell, Stephen M. , Novak, Anne J. , Cholack, George A , Edelmann, Dominic , Walker, Janek S. , Novak, Joseph P. , Wang, Yucai , Mou, Eric , Syrbu, Sergei , Seheult, Jansen N. , Vodička, Prokop , Paludo, Jonas , Witzig, Thomas E. , Hsi, Eric D. , Link, Brian K. , Habermann, Thomas M. , Maurer, Matthew J. , Cerhan, James R.

Blood | December 5, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 5301-5301

10.1182/blood-2025-5301 Get It

Abstract Over the past decade, classification systems using high-throughput genetic data have been developed to identify molecular subtypes of DLBCL. Although not a primary goal, these classifiers were also proposed as prognostic factors in their respective publications. To date, however, no study has directly compared these classifiers' ability to predict overall (OS) and event-free survival (EFS) in the same cohort. Herein, we sought to systematically compare predictive performance, benchmarked against the IPI, of several current established molecular classifiers and evaluate if any add significant independent prognostic information beyond the IPI. WES (including paired germline filter) and RNAseq data from newly diagnosed DLBCL patients (N=432; 2018 WHO criteria) in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource (MER) were available for analysis (WES n=112, RNAseq n=40, or both n=280). The number of cases able to be classified (including as unclassified) for each classifier was as follows: IPI (432, 100%), cell-of-origin (COO, by Hans algorithm; 346, 80.1%), refined COO (by gene expression with Dark Zone Signature; 320, 100%), Haematological Malignancy Research Network (HMRN; 349, 89.0%), B-cell state (320, 100%), Lymphoma Ecotype (320, 100%), Lymphoma Microenvironment (LME; 320, 100%), Tumor microenvironment (TME26; 320, 100%), SubLymE (312, 97.5%), LymphGen (358, 91.3%), and DLBclass (223, 58.2%). OS was defined as time from diagnosis to all-cause death while EFS was defined as time from diagnosis to disease progression, initiation of second-line treatment, or all-cause death. We calculated Harrell's c-statistics for each Cox proportional hazards model evaluating the discriminative performance of each classifier in predicting OS/EFS. Using bootstrap validation, we obtained optimism-corrected c-statistics, which we report in the results. We performed likelihood ratio tests (LRT) comparing a univariable Cox model with IPI alone and models including both IPI and a given classifier to assess if a classifier provided independent prognostic information beyond the IPI. All patients were treated with immunochemotherapy (IC) with curative intent, 247 (57%) were male, median age at diagnosis was 65 years (IQR 55-72 years), 390 (96%) were White, 209 (60%) had GCB subtype by Hans, 22 (5.1%) had MYC double-hit by FISH (MYC and BCL2 or BCL6), and 162 (37.9%) had an IPI ≥ 3. The median follow-up was 7.0 years, 167 (39%) experienced an event, and 137 (32%) died. In a univariable Cox model, the c-statistic for IPI predicting OS was 0.66 (95% confidence interval [CI] 0.61-0.70). All other classifiers had c-statistics of ≤0.56. The c-statistic for IPI predicting EFS was 0.64 (95% CI 0.60-0.69), and all other classifiers had c-statistics of ≤0.58. The univariate DLBclass results for OS and EFS were not significantly impacted when restricted to cases with confidence >0.7 (n=136). In Cox models of IPI alone versus IPI plus an individual classifier, the only classifier that provided statistically significant, independent information for OS was TME26 (LRT p=0.02). Adjusting for IPI, patients who were TME26-negative had significantly inferior OS compared to TME26-positive cases (HR 1.63, 95% CI 1.07-2.47; p=0.02). For EFS, DLBclass (restricted to confidence >0.7) added significant prognostic information beyond IPI (LRT p=0.02). This finding was largely driven by C5 subtype; relative to C1 subtype and adjusting for IPI, C5 subtype had significantly inferior EFS (HR 5.53, 95% CI 1.81-17.0; p=0.003). In summary, we compared prognostic performance of multiple DLBCL molecular classifiers with respect to OS and EFS in a single real-world, prospective cohort of newly diagnosed, IC-treated DLBCL. Our data supports two key findings: all classifiers had modest performance for prognosis, and none individually outperformed the IPI in predicting OS nor EFS. Second, only TME26 and DLBclass (confidence >0.7) provided additional prognostic information beyond that captured by the IPI for OS and EFS, respectively. This finding suggests that the tumor immune microenvironment and characteristics of C5 DLBCLs (ABC-subtype, CD79B mutations) can potentially offer significant independent information for predicting survival and response to front-line immunochemotherapy. If replicated, these findings could inform risk-adapted treatment approaches and aid in identifying high-risk patients for enrollment in genomically-informed clinical trials.
Shorter diagnosis to treatment interval is associated with poor prognosis in patients with peripheral T-cell lymphoma: Analysis from the LEO and MER cohorts
Mehta-Shah, Neha, Allen, Pamela, Cohen, Jonathon B. , Lossos, Izidore S. , Pongas, Georgios , Flowers, Christopher R. , Ruan, Jia , Mehta–Shah, Neha , Larson, Melissa C. , Mou, Eric , Bennani, N. Nora , Wallace, Danielle, Malpica, Luis , Martin, Peter, Habermann, Thomas M. , Wang, Yucai , Nze, Chijioke , Witzig, Thomas E. , Syrbu, Sergei , Jaye, David L. , Nastoupil, Loretta J. , Cerhan, James R. , Feldman, Andrew L. , Maurer, Matthew J.

Blood | December 5, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 5439-5439

10.1182/blood-2025-5439 Get It

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.
Outcomes in the 2nd decade following follicular lymphoma (FL) diagnosis: Long-term follow-up from the university of Iowa/Mayo Clinic SPORE molecular epidemiology resource (MER)
Thompson, Carrie A. , Flowers, Christopher R. , Ansell, Stephen M. , Day, Jonathan, Larson, Melissa C. , Mou, Eric , Durani, Urshila , Casulo, Carla , Tsang, Mazie , Farooq, Umar , Mondello, Patrizia , Villasboas, José C. , Syrbu, Sergei , Feldman, Andrew L. , Witzig, Thomas E. , Habermann, Thomas M. , Cerhan, James R. , Link, Brian K. , Wang, Yucai , Maurer, Matthew J.

Blood | December 5, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 1007-1007

10.1182/blood-2025-1007 Get It

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.
FLP-R: A clinical prediction model for follicular lymphoma Prognosis in the Relapsed/refractory setting
Cohen, Jonathon B. , Jørgensen, Jennifer Bøgh , Strouse, Christopher , Cahn, Elliot, Ansell, Stephen M. , Martin, Peter , Lossos, Izidore S. , Flowers, Christopher R. , Strouse, Christopher S , Maurer, Matthew J. , Larson, Melissa C. , Durani, Urshila , Tsang, Mazie , Mou, Eric , Day, Jonathan, Villasboas, José C. , Feldman, Andrew L. , Syrbu, Sergei , Burack, Richard , Chihara, Dai , Russler‐Germain, David A. , Wang, Yucai , Nastoupil, Loretta J. , Koff, Jean L. , Habermann, Thomas M. , El‐Galaly, Tarec Christoffer , Cerhan, James R. , Link, Brian K. , Casulo, Carla

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 5354-5354

10.1182/blood-2025-5354 Get It

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.
FLIPI24 as a prognostic model in marginal zone lymphoma: Results from an international multi-cohort analysis
Vodička, Prokop , Masar, Michal, Lossos, Izidore S. , Cohen, Jonathon B. , Obr, Aleš , Móciková, Heidi , Ďuraš, Juraj , Steinerová, Kateřina, Patel, Dilan A. , Martin, Peter , Šálek, David, Šýkorová, Alice , Cahn, Elliot, Campr, Vít , Michalka, Jozef , Štěpánková, Pavla , Hricko, Samuel, Suri, Alexandra, Jakša, Radek , Dlouhá, Jitka, Habermann, Thomas, Blahovcová, Petra, Flowers, Christopher R. , Maurer, Matthew J. , Wang, Yucai , Janikova, Andrea , Belada, David , Mou, Eric , Casulo, Carla , Nze, Chijioke , Karban, Josef , Martin, Peter, Feldman, Andrew L. , Klánová, Magdalena , Jaye, David L. , Syrbu, Sergei , Suri, Alexandra, Larson, Melissa C. , Klener, Pavel , Procházka, Vít , Cerhan, James R. , Trněný, Marek

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 1826-1826

10.1182/blood-2025-1826 Get It

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.
Characterizing primary mediastinal large B-cell lymphoma based on molecular classification: a multi-center retrospective pilot study
Superdock, Michael , Rimsza, Lisa M. , Strawderman, Myla , Ramsower, Colleen , Steiner, Raphaël , Faugh, Tina, Maurer, Matthew J. , Feldman, Andrew L., Rock, Philip , Robetorye, Ryan S. , Flowers, Christopher R. , Friedberg, Jonathan W. , Maurer, Matthew , Rosenthal, Allison C, Wallace, Danielle , Link, Brian K. , Rosenthal, Allison , Burack, Richard , Syrbu, Sergei , Feldman, Andrew L. , Cerhan, James R. , Casulo, Carla

Leukemia & Lymphoma | August 6, 2025 | Volume: 66 | Issue: 12 | Pages: 2324-2327

10.1080/10428194.2025.2539231 Get It

Real-world impact of differences in the WHO and ICC classifications of non-Hodgkin lymphoma: a LEO cohort study analysis
Abro, Brooj , Maurer, Matthew J. , Burack, Richard , Chapman, Jennifer R. , Cohen, Jonathon B. , Friedberg, Jonathan W. , Inghirami, Giorgio , Lossos, Izidore S. , Martin, Peter W., McDonnell, Timothy J. , Riska, Shaun M., Flowers, Christopher R. , Burack, W Richard , Cohen, Jonathon B , Inghirami, Giorgio , Link, Brian K , Lossos, Izidore S , Nastoupil, Loretta J , Vega, Francisco , Cerhan, James R , Feldman, Andrew L , Maurer, Matthew , Habermann, Thomas M. , Kahl, Brad S. , Larson, Melissa C. , Link, Brian K. , Martin, Peter, Nastoupil, Loretta J. , Syrbu, Sergei , Vega, Francisco , Vij, Kiran R , Cerhan, James R. , Jaye, David L. , Feldman, Andrew L.

Blood | September 10, 2024 | Volume: 144 | Issue: 19 | Pages: 2063-2066

10.1182/blood.2024025681 Get It

Abstract Recent introduction of 2 different lymphoma classifications has raised concerns about consistency in diagnosis, management, and clinical trial enrollment. Data from a large cohort reflecting real-world clinical practice suggest that differences between the classifications will affect <1% of non-Hodgkin lymphomas.
Romiplostim for Treatment of Children and Young Adults With Severe Aplastic Anemia and Myelodysplastic Syndrome
Carr, J. Walter, Claassen, David , Al‐Huniti, Ahmad , Mott, Sarah L. , Sharathkumar, Anjali , Carr, Jamie, Syrbu, Sergei , Bhagavathi, Sharathkumar , Modi, Arunkumar J. , Bates, Melissa Lowe

Journal of Pediatric Hematology/Oncology | May 24, 2024 | Volume: 46 | Issue: 5 | Pages: 252-261

10.1097/mph.0000000000002891 Get It

Thrombopoietin receptor agonists (TPO-RAs) induce trilineage hematopoiesis under conditions with acquired hematopoietic failure. We evaluated safety, tolerability, and preliminary efficacy of a TPO-RA, romiplostim (Nplate), with or without standard-of-care immunosuppressive therapy (±IST) for children (ages <21 y) with newly diagnosed and relapsed/refractory severe aplastic anemia (SAA) and myelodysplastic syndrome (MDS). Data were collected from an observational study and a single arm interventional pilot study. The safety outcome was treatment-related adverse events (AEs). Efficacy was evaluated by complete hematopoietic response (CHR) at week 24. Romiplostim was commenced at 5 µg/kg/week, with dose escalation of 2.5 µg/kg/week (maximum, 20 µg/kg/dose) based on platelet response. Romiplostim was continued until CHR was observed. Ten subjects (SAA, 9 [IST, 4; without IST, 5]; MDS, 1) completed the study (median age: 9.2 y). Median romiplostim dose was 10 µg/kg/week (range: 5 to 17.5 µg/kg/week). The cumulative incidence of CHR was 70.4% (95% CI, 20.2%-92.6%). Among 21 AEs (Grade 1 to 3), 3 were attributed to romiplostim. At a median posttherapy follow-up of 10.9 months (range: 0.7 to 77.5), no clonal evolution, bone marrow fibrosis or mortality was reported. This proof-of-concept study provides data about short-term safety, tolerability, and preliminary efficacy of romiplostim (±IST) for treatment of pediatric SAA/MDS.