A recent survey conducted by Moore et al found 56% of pathologists read 5-20 smears daily which can represent significant workload. The survey also found well-accepted guidelines for initiating pathologist review lacking though desired by the hematopathologist community. Pathologist blood smear review can be clinician-initiated or lab-initiated. In our busy laboratory, clinician-initiated reviews bypass manual technologist review. For lab-initiated review, smears undergo rigorous analysis by technologists to identify cytomorphologic and/or numerical abnormalities if recognized based on lab-based criteria for CBC, automated differential and manual differential findings in the hematology laboratory. Once an abnormality is flagged, the lab sends the slide, noting the policy-based abnormality for which the smear was escalated for pathologist review. Our hematopathology practice has registered an increasing volume of clinician-initiated smear reviews including many for which clinical value was unclear. We hypothesize that our laboratory policies are adequate to identify blood smears meriting pathologist review. As a prelude to testing this hypothesis prospectively, we undertook a retrospective pilot study to better understand the blood smear review test lifecycle and to determine which clinician-initiated pathologist smear reviews would likely have been flagged by laboratory policy. We collected a random sample of 50 clinician-initiated pathologist smear reviews over several months, recording which pathologist reviews were accompanied by a CBC, automatic differential, and/or manual differential. Then, we inferred if there was a pathologic abnormality that would have mandated pathologist review according to laboratory policy, classified the ordering provider’s level of training, determined if the clinician provided a comment, classified the comment as medically relevant or irrelevant, and determined if the pathologic diagnosis was reported in the clinical note. We found that smears were ordered by physicians (86%) and advanced practice providers (14%). Of these, 78% were accompanied by CBCs, 46% were accompanied by automatic differentials, and 26% were accompanied by manual differentials. Interestingly, only 26% of clinicians provided comments with the pathologist review order. Furthermore, only 46% of these comments contained medically relevant information. Of note, 46% of physicians provided medically relevant information compared to 0% of advanced practice providers. On the other hand, 38% of physicians provided medically irrelevant information compared to 15% of advanced practice providers. Notably, only 38% of clinician-initiated pathologist reviews would be sent for pathologist review per our laboratory policy. And of those 38%, 74% would be flagged for cytomorphologic abnormalities, 11% for numerical abnormalities, and 16% for both numerical and cytomorphological abnormalities. Strikingly, 62% of clinician-initiated pathologist blood smear reviews would not be flagged by our lab for pathologist review. These findings provide context and rationale for a prospective study to improve test utilization, speculating that appropriate laboratory policy would capture all findings that warrant pathologist review.

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.

Introduction There is currently no standard-of-care for patients (pts) who cannot tolerate full dose anthracycline regimens in frontline large B-cell lymphoma (LBCL). R-miniCHOP is a commonly used regimen that provides curative intent treatment with manageable toxicity. Despite this, lymphoma and treatment-related mortality are the leading causes of death in these pts. Additionally, many pts may not be eligible to receive R-miniCHOP due to comorbidity or frailty. There are limited clinical trial and real-world data focused on this population. Methods Pts with LBCL age 18 years (yrs) and older were identified from the Lymphoma Epidemiology of Outcomes (LEO) cohort, a prospective study of newly diagnosed pts with non-Hodgkin lymphoma enrolled from 2015-2020 at 8 academic medical centers in the US. Pts with LBCL were included in this analysis if they had received R-miniCHOP or a regimen that did not include an anthracycline (nonAC). NonAC regimens included R-CVP, BR, rituximab, radiation and lenalidomide and rituximab. Pts completed the Vulnerable Elders Survey (VES-13) and were considered vulnerable if they had a score >3. Event-free survival (EFS) was defined as the time from start of treatment until progression/relapse, retreatment, or death due to any cause; EFS at 24 months (EFS24) was a secondary endpoint. Overall survival (OS) was defined as the time from start of treatment until death due to any cause. EFS and OS for R-miniCHOP and non-IC groups, as well as vulnerable and not vulnerable by VES-13 were estimated using Cox models. Results A total of 190 pts received R-miniCHOP (N=139) or nonAC (N=51). R-miniCHOP-treated pts were older (median 82 vs 72 yrs) and more commonly female (55% vs 35%). The majority in both groups (86% vs 78%) received their treatment at a LEO center and did not receive therapy on a clinical trial (89% vs 100%). Most pts receiving R-miniCHOP had high-intermediate (32%) or high (30%) international prognostic index (IPI) score, while both high-intermediate (22%) and high (20%) IPI were lower in the nonAC-treated pts. Cell of origin was determined by immunohistochemistry as available clinically, with GCB 42% vs 31%, non-GCB 32% vs 29%, and not done/unknown 26% vs 39% in R-miniCHOP vs nonAC pts. Double-hit status by FISH was known in 115 pts and was positive in 13% of R-miniCHOP pts and 10% of nonAC pts. The diagnosis-to-treatment interval (DTI) was ≤14 days in 30% of R-miniCHOP pts and 24% of nonAC pts. Of pts who had a VES-13 score (N=119), vulnerable status trended higher in the R-miniCHOP (66%) vs the non-IC group (50%; p=0.15). With a median follow-up of 50.5 months, the median EFS was 37.1 months and median OS was 50.0 months. R-miniCHOP, compared with non-IC, was associated with improved EFS (unadjusted HR=0.54, 95% CI 0.36-0.81; p=0.003) and OS (unadjusted HR=0.58, 95% CI 0.38-0.88; p=0.011). When adjusted for age, IPI, LBCL subtype (diffuse large B-cell lymphoma, not otherwise specified vs other), DTI and VES-13, R-miniCHOP was strongly associated with improved EFS (HR=0.26, 95% CI 0.14-0.50; p<0.001) and OS (adjusted HR=0.29, 95% CI 0.15-0.57; p<0.001). EFS24 rate was 56% in all pts and was superior in pts treated with R-miniCHOP vs non-IC (62.7% vs 34.1%; p=0.001). In the R-miniCHOP group, vulnerable status (adjusted for IPI) was associated with inferior OS (HR=2.22, 95% CI 1.09-4.50; p=0.028) and trended towards inferior EFS (HR=1.76, 95% CI 0.93-3.32; p=0.083). In a competing-risk cumulative-incidence analysis, lymphoma was the leading cause of death for pts receiving R-miniCHOP at 2 (0.16, 95% CI 0.11-0.24) and 5 (0.20, 95% CI 0.14-0.28) yrs, as well as for those receiving non-IC at 2 (0.35, 95% CI 0.24-0.53) and 5 (0.38, 95% CI 0.26-0.56) yrs. Treatment-related mortality was similar in both groups. In the R-miniCHOP group, the 2-yr (0.20 vs 0.03) and 5-yr (0.20 vs 0.11) lymphoma-related mortality was higher in pts who were vulnerable vs not by VES-13, while there were no differences for mortality due to therapy or other causes by vulnerable status. Conclusions These data support R-miniCHOP as a curative regimen in older and frail pts with the majority achieving EFS24. R-miniCHOP compared to non-IC use is strongly associated with improved EFS and OS when adjusted for disease and patient related variables. Within the R-miniCHOP group, vulnerable status is associated with inferior OS. Additional research efforts are needed to optimize outcomes for this group of pts.

Lenalidomide (LEN) containing regimens are common maintenance therapies for multiple myeloma (MM) patients post autologous stem-cell transplantation (ASCT). Previous studies correlated increased risk of secondary-primary malignancies, including therapy-related myeloid neoplasms (t-MN), with LEN maintenance. The rates and timelines specific acquired myeloid-associated cytogenetic lesions with LEN are poorly described. We reviewed all institutional bone marrow and/or blood pathology results of 387 MM patients who underwent ASCT between 12/2007 and 12/2016, with follow up data accessed up to 10/2022. Among these, 280 patients received LEN alone, while 107 controls were observed (OBS). Patients who acquired > = 1 cytogenetic abnormality from the Revised International Prognostic Scoring System (IPSS-R) post -ASCT and/or a secondary primary marrow-based hematolymphoid neoplasm were identified in LEN and OBS groups. Myeloid-associated and myeloma-associated abnormalities in single clones were excluded. The LEN group included older patients, with more marrow biopsies on average and longer follow-up durations [avg age LEN 61.06 yrs vs OBS 58.38 years (p = 0.01)]. Racial distribution between groups was similar, except slightly higher Hispanics in the OBS group. There was no significant difference in gender distributions. Myeloid-associated cytogenetic abnormalities occurred in 8.9% of LEN versus 2.8% of the OBS group (p = 0.046). Median time-to-acquisition was 1,557 days for LEN and 969 days the OBS group (p = 0.40). The most frequently observed abnormality was del(20q), 5.7% of LEN versus 0.9% of OBS group (p = 0.050). Other findings included: del(5q) 1.8% of LEN versus 0.9% OBS (p = 1.000); del(7q) 2.1% LEN versus 0% OBS (p = 0.193); and complex karyotype (>3) 1.8% LEN versus 0% OBS (p = 0.328). Twelve LEN and no OBS patients developed a t-MN post-ASCT (p = 0.193). Of these patients, nine developed myelodysplastic syndrome (MDS), three post-MDS acute myeloid leukemia (AML), and three de novo AML. Eight of nine MDS patients sorted into the five IPSS-R prognostic subgroups: 50% low-risk, 12.5% high-risk, 37.5% very high-risk, with none very low- or intermediate-risk. One MDS patient was excluded for lack of pretreatment karyotype. The distribution of MDS patients across R-IPSS risk groups was skewed toward high- and very high-risk categories versus published de novo MDS distributions. Three LEN and one OBS patient developed B-lymphoblastic leukemia (p = 1.0). One LEN patient developed mantle cell lymphoma, with no lymphomas from OBS (p = 1.0). The OBS group showed median overall survival 3,979 days, with median survival not reached for LEN. LEN group patients displayed a significantly better overall survival versus OBS (p = 0.03). Though there was no statistically significant difference in secondary primary marrow-based hematolymphoid neoplasms with LEN, myeloid-associated cytogenetic abnormalities developed more commonly vs control OBS. Despite the increased occurrence of secondary primary hematolymphoid marrow neoplasms with LEN, the overall survival of LEN group was significantly better vs OBS.

Background: The prognostic impact of specific genomic changes in mantle cell lymphoma (MCL) is not well characterized beyond altered TP53, which is recognized as a high-risk marker and commonly assessed at diagnosis, and the “proliferation signature” developed using gene expression in fresh frozen tissues (Rosenwald et al, Cancer Cell 2003). To bridge this knowledge gap, we applied comprehensive tumor sequencing to investigate how genomic abnormalities affect prognosis in patients (pts) with MCL with and without TP53 alterations. Methods: The Atlas of Blood Cancer Genomes project is an international collaborative effort including 25 sites for collecting and sequencing all blood cancers (Love et al, ASH 2021). We recruited MCL pts with detailed clinical data and subjected their tumors to whole exome, whole transcriptome, and targeted sequencing. TP53-aberrant cases (i.e., mutation or deletion) were identified from sequencing and clinical pathology reports. Progression-free survival (PFS) and overall survival (OS) were measured using the Kaplan-Meier method, with statistical comparisons by the log-rank test. Risk for a gene signature was defined as the coefficient from the respective Cox proportional hazard model. Results: RNA and DNA sequencing were performed successfully for 252 pts with MCL. Clinical features and treatment regimens were consistent with prior disease descriptions and have been reported previously (Koff et al, ASH 2022). In the entire cohort, median PFS was 38 months, and median OS was not reached. As expected, TP53 abnormalities were associated with inferior OS compared to TP53-wildtype (WT; 5-year OS 48% and 79%, respectively, p<0.001). A novel gene expression signature (“immune signature”) was determined by identifying genes that displayed prognostic ability independent of the previously described MCL proliferation signature (Rosenwald et al, Cancer Cell 2003; Scott et al, J Clinical Oncology 2017). This signature was distinct from the proliferation signature both in terms of included genes and ability to discriminate between risk groups; the correlation plot between the immune and proliferation signature scores showed a low R2 value of 0.01. The immune signature appears to derive from differences in tumor microenvironment (TME) CD8+ T and T follicular helper cells: pts designated as high-risk by the immune signature demonstrated lower proportions of these TME subsets as assessed by CIBERSORT (p=0.001). For the cohort with tumors sequenced prior to treatment (n=208), 5-year OS was 45% for pts with a high-risk immune score (bottom quartile), 80% for pts with intermediate-risk immune score (middle 2 quartiles), and 91% for low-risk immune score (top quartile, p <0.001), with improved discrimination compared to the proliferation signature (56%, 79%, and 80% for high-, intermediate-, and low-risk proliferation scores, respectively; p=0.03). The immune signature also risk-stratified outcomes in MCL subgroups with and without TP53 alteration. For pts with TP53-WT (n=74), low-risk immune score predicted 5-year OS of 86%, while high-risk immune score was associated with 5-year OS of 38% (p<0.001), compared to 72% vs 82% for low-risk and high-risk proliferation scores (p=0.16). For pts with aberrant TP53 (n=43), low-risk immune score had 5-year OS of 77%, and high-risk immune score had 5-year OS of 9% (p<0.001), compared to 35% vs 52% for low-risk and high-risk proliferation scores (p=0.28). Application of the immune signature also further stratified pts deemed high-risk by the proliferation score (n=52): within this group, low-risk immune score associated with 5-year OS of 76%, and high-risk immune score predicted 5-year OS of 29% (p<0.001). Similar stratification was also observed when the immune signature was applied to pts with low- and intermediate-risk proliferation scores (n=156; 5-year OS of 88% vs 57% for low-risk vs high-risk immune score respectively, p<0.001). Conclusions: In this largest-ever study of MCL's genomic landscape, we identify a novel gene expression signature that stratifies risk within and across existing prognostic groups, including TP53-altered cases. Our findings support development of the immune signature as a tool that can be used in routine clinical practice to improve risk stratification of all MCL patients at diagnosis. Additional study is warranted to define therapeutic implications of differential TME T cell subset composition in MCL.

Digital pathology (DP) with whole slide imaging (WSI) is a rapidly advancing field with great potential in applications such as telepathology and artificial intelligence (AI). Our laboratory uses a modern and popular high-throughput DP system that is approved for interpretation of formalin-fixed paraffin embedded (FFPE) sections cut on a microtome. Bone marrow (BM) biopsies represent off-label usage of our DP system because a BM case includes cytological (i.e. not cut) components; aspirate and blood smear. We performed an abbreviated mock validation of our DP system with BM biopsies from multiple myeloma (MM) patients using the latest DP validation guidelines from CAP, ASCP, and API to understand the analytical performance of our DP system with BM biopsies. Ten MM cases diagnosed within the past year at a single institution were selected and scanned. Each case included a peripheral blood smear, BM aspirate smear, clot, and core biopsy. Cases with secondary hematologic malignancies, additional testing, i.e., immunohistochemistry, or inadequate smears were excluded. De-identified glass and DP slides were assigned unique case numbers and evaluated by three pathologists, who signed them out within one week, with a two-week washout period between glass and digital reviews. Pathologists were provided with the patient’s age, flow cytometry results, two most recent complete blood counts, and prior history. A non-assigned reviewer compared diagnoses between glass and DP slides, categorizing discrepancies as “none,” “minor,” or “major.” Pathologists were given a qualitative evaluation form to rate their experience at the end of the study. All 10 cases demonstrated high (100%) diagnostic concordance between glass and digital slides. No major discrepancies impacting clinical management were observed (0/10). Of these, 6/10 cases showed no discrepancies, while 4/10 had minor discrepancies related to reported plasma cell percentages, with an average difference of 4.38% (range: 1–7.5%). The qualitative evaluation survey indicated that pathologists found the cases easy to diagnose using the DP platform (mean score: 1.3) on a 1–5 scale, (1 = strongly disagree that the diagnosis was challenging). Additionally, pathologists expressed strong interest (mean score: 4.3) in incorporating DP into their workflow if readily accessible. This limited study demonstrated high concordance between digital and glass slide interpretations of BM cases in MM and suggests that DP systems designed for FFPE cut sections might have utility in the interpretation of BM cases. Future studies should include cases within the original exclusion criteria and should be expanded to the CAP-recommended guidelines of at least 60 cases with a target of > 95% concordance.

Publicly available, general-use, generative artificial intelligence (GAI) large language models can serve as a quick reference for information, including that for pathologists, laboratorians and trainees. This pilot study sought to test the accuracy of different models, including free and paid tiers, when queried for specific diagnostic criteria that are well defined in the 5th edition of the World Health Organization (WHO) classification of haematolymphoid tumours. Systemic mastocytosis (SM) and T large granular lymphocytic leukemia (TLGLL) were employed as diagnostic test cases given their criteria are straightforward, providing a clear-cut gold standard. Additionally, these criteria incorporate minor updates in the most recent WHO classification in 2022, enabling the assessment of the GAIs when it comes to latest changes in current diagnoses. OpenAI, Perplexity AI, and Google Gemini were the GAI models studied. A simple, straight forward prompt (SFP) was first employed. Then, a more complex, AI-generated prompt (AIP) was used to investigate whether more lengthy and detailed prompts would yield different and/or more accurate answers. The answers were then compared with the 5th edition WHO diagnostic criteria which served as the gold standard. For SM, accurate responses were obtained with OpenAI (free;SFP/AIP, paid;AIP), Perplexity (free;SFP/AIP, paid;SFP/AIP), and Gemini (free;SFP, paid;SFP/AIP). For TLGLL, only Perplexity (free;SFP, paid;SFP/AIP) gave accurate results. Additionally, paid versions tended to give longer answers with more explanations, and sometimes including extraneous information. While this small pilot study suggested that Perplexity AI was more accurate than the other GAIs in free or paid versions, it remains unclear if this finding can be generalized across other diagnostic categories. We found that extracting complete accurate information from the tested general-use GAI models can currently be a challenge. Thus, reliance on the tested GAI models even for a seemingly simple task of listing diagnostic criteria for hematologic neoplasms seems unwise at this time. Domain-specific GAI models for use by pathologists, laboratorians and their trainees may prove to be more appropriate resources in the future. Given the ease of accessibility of the WHO 5th edition online, with current pricing that is similar, if not less expensive than paid GAI subscriptions, as well as the listed essential and desirable diagnostic criteria within its chapters, we would favor its use over the tested GAI models at this point. Likewise, traditional textbooks and scientific literature in the field still serve as robust resources for obtaining accurate diagnostic criteria.

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.

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.

Diffuse large B-cell lymphoma (DLBCL) arises at an earlier age and is associated with inferior survival in African American patients (pts). These disparities reflect socioeconomic and genetic factors. For example, SETD2, and other DNA damage-linked mutations are highly enriched in U.S. pts with African ancestry (AA) but are exceptionally rare in European ancestry (EUR) DLBCLs (Lee et al, 2020). We showed that SETD2 mutations disrupt repair of AICDA-mediated DNA damage in germinal center (GC) B cells, causing DLBCLs with genomic instability (Leung et al, 2022). We now report these mutations are equally enriched in DLBCLs from Malawi vs EUR pts (p<0.001), supporting ancestry dependence. We generated a BCL2;Setd2+/- (SB2) mouse model for AA-DLBCLs and analyzed mice tumors at 6 and 12 months by IHC, IF and flow cytometry. Compared to BCL2-only, SB2 mice showed enriched exhausted CD4+ T cells at 6 months (p<0.0001) and exhausted CD8+ T cells at 12 months (p=0.0009). We developed luciferase+ SB2 lymphoma cell line that engrafts in syngeneic mice and 5 isogenic human SETD2+/- DLBCL cell lines to broaden our AA-DLBCL models. IV injection of SB2 cells killed mice within 5 weeks and displayed abundant CD4/CD8 effector/exhausted (Eff/Exh) T cell infiltration. Both murine and human SETD2+/- DLBCLs showed marked genomic instability vs controls (COMET assay, p<0.001), a known trigger of senescence and inflammation. Senescence is not reported as a characteristic of DLBCLs, however primary SB2 tumors (p=0.02), murine, and human lines (p<0.0001) had high levels of senescence by β-galactosidase (β-gal) staining and C12FDG flow cytometry. RNA-seq, proteomic, and phospho-proteomic studies in SB2 and human SETD2+/- cell lines vs controls showed enrichment for senescence-associated secretory phenotype (SASP) signatures and activation of p38 MAPK, JAK-STAT, TLR4, TNFα, and NFκB (p<0.01). CODEX imaging of a tissue microarray (TMA) with 25 AA- and 97 EUR-DLBCLs showed a significantly enriched inflammatory microenvironment of Eff/Exh CD4+ and CD8+ (both p<0.0001) cells in AA-DLBCL. RNA-seq showed upregulation of SASP associated kinases in AA vs Eur DLBCL pts. To test if primary AA-DLBCLs also featured abundant senescent cells, we performed GLB1 (β-gal) IHC in TMAs from three large independent AA-DLBCL cohorts, including one from Malawi, vs two EUR cohorts. Each AA-DLBCL cohort showed striking SASP enrichment (>20% GLB1+ cells; p<0.0005), confirmed with an independent functional senescence marker (SentraGor). SASP+ tumor cell abundance correlated with exhausted CD4+ (p=0.02) and CD8+ (p=0.001), suggesting a link between SASP and immune modulation. To test this, we sorted top-quartile SASP+ and SASP– SB2 cells. Both proliferated similarly, indicating SASP does not impair DLBCL growth. Upon transplantation, only SASP+ cells formed tumors in immunocompetent C57BL/6 mice (p=0.02), while both SASP+ and SASP- engrafted in RAG1KO immunodeficient mice, showing SASP is required to evade immune surveillance. SASP+ cells secreted CD4-activating cytokines (IL20, IL12, IL16) and canonical SASP factors (IL1β, IL6, IL10, TNFα). We hypothesized that CD4 exhaustion is critical for SASP-driven immune evasion. Accordingly, in vivo depletion of CD4+ T cells impaired lymphoma progression, whereas CD8+ depletion accelerated it. Though checkpoint inhibitors (CPI) generally fail in DLBCL, we reasoned the SASP phenotype might confer susceptibility. Indeed, SB2 DLBCLs but not GCB DLBCLs were highly sensitive to murine-optimized PD1 inhibitors (p=0.04), with prolonged complete remission. We tested whether SETD2+/- DLBCLs would show sensitivity to SETD2 inhibitor due to defective DNA repair and found that SETD2i selectively depleted SB2 SASP⁺ cells by inducing overwhelming DNA damage (p=0.01), delayed tumor growth (p=0.002), and restored CD4/CD8 functionality (p=0.01 and p=0.02). Combinatorial CPI + SETD2i studies are underway. In summary, we identified a novel DLBCL subtype almost entirely restricted to AA individuals, driven by a novel SASP-like program that promotes lymphomagenesis via CD4 exhaustion. This subtype is readily diagnosed by IHC or flow cytometry using validated senescence markers. Recognizing these “ancestry variant” cases is critical, as they may respond to CPI and senolytic therapies as an ancestry-informed precision immunotherapy strategy for this population historically underrepresented in clinical trials and often unable to access state-of-the-art care.

Marginal zone lymphoma (MZL) is an uncommon non-Hodgkin B-cell lymphoma accounting for 7-10% of lymphoma diagnoses. Extranodal MZL (EMZL) of mucosa-associated lymphoid tissue (MALT) is the most common subtype (61%) of MZL. While the mutational landscape, chromosomal aberrations and transcriptome of nodal and splenic MZL have been extensively evaluated, the mutational landscape of EMZL has only been evaluated in a small number of patients and mainly by targeted sequencing. Consequently, the comprehensive genomic landscape of EMZL remains largely uncharacterized. Herein, we performed whole exome sequencing followed by targeted sequencing of potential tumor driver genes, copy number and/or RNA transcriptome analyses in 165 patients with pretreatment EMZL tumors involving 16 anatomic locations. All samples were collected and underwent expert review as part of the Atlas of Blood Cancer Genomes consortium. The most common anatomic locations were ocular adnexa (OAMZL) (n=35), gastric (n=25, including 6 positive for Helicobacter pylori), salivary glands (n=25), and lungs (n=24). Using common criteria for variant mutation calling and significant focal copy number (CN), we identified 1218 variants (1030 missense and 188 truncation mutations) across 174 genes and 2837 CN focal alterations (1614 copy gains and 1223 copy number losses). Of these genes, 44 and 11 were mutated in >5% and >10% of specimens, respectively. We detected variants identified previously by targeted sequencing in EMZL from different locations (e.g. TNFAIP3 (A20) (12%), TBL1XR1 (13%), SPEN (10%), CARD11 (7%), TET2 (7%) and CREBBP (6%)). We detected mutations in KLF2 (10 mutations in 8 EMZL patients) and PTPRD (7 mutations in 7 EMZL patients) that were previously suggested to be specific for splenic and nodal MZL, respectively. We also detected variants not previously reported in EMZL, including a transcriptional factor ZEB2, LRP1B,and others. The most frequently mutated gene in our study (25% of tumors) was IGLL5. Some mutations were limited to specific locations (e.g. ZEB2 mutations seen exclusively in gastric and salivary gland EMZL), while most were observed across all anatomic locations. There was no association between specific mutations and clonal IGHV, in contrast to previous reports. Using Enrichr tool, we observed enrichment of mutations in genes belonging to the B cell receptor activation, NOTCH signaling, Wnt-beta catenin signaling, NF-kB signaling , PI3K AKT signaling, DNA repair and other pathways. Chromosomal and copy number changes were also commonly observed including previously reported trisomy of chromosomes 3 and 18. Combining DNA mutations and CN alterations, the number of genetic lesions per tumor sample in the 174 mutated genes ranged from 0 to 95, with an average load of 17 lesions per case. RNA sequencing was successful in 159 EMZL tumors from 16 distinct anatomic locations. Unsupervised clustering using all genes with a median log2-normalized gene expression value greater than 5 and a standard deviation greater than 1 (1323 genes) demonstrated that the majority of gastric EMZL with and without H. pylori infections clustered together on 2 dendrograms as did most of the samples of OAMZL. Since the clustering could be forced by organ-specific and not tumor-specific gene expression, we next focused on the expression of the 345 genes from the LM22 matrix that passed our transcriptomic row filtering. Unsupervised clustering resulted in clustering of most gastric EMZL irrespective of H. pylori positivity together in the same dendrogram branch, accompanied by few additional EMZL from other anatomic locations. Most of the EMZL samples from other locations did not show preferential co-clustering together. On comparison of gene expression between gastric and OAMZL, there was enrichment of the B-cell receptor signaling pathway, B-cell activation, B-cell naïve and B-cell memory cells, B-cell proliferation and NF-kB signaling in the latter. Immune microenvironment analysis showed a statistically significant increase in resting mast cells and decrease in M1 macrophages in gastric EMZL and increase in regulatory T cells in salivary EMZL. The broad genomic studies reported here underscore the biological similarity of EMZL across anatomical sites with the potential exceptions of gastric EMZL (regardless of H. Pylori status). These data provide valuable genomic and transcriptomic resources to inform future diagnostic and therapeutic strategies.

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 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.