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Abstract Background: Although progression-free survival (PFS) in early-stage (ES) classic Hodgkin Lymphoma (cHL) is high, there remains a subset of patients (pts) at higher risk of worse outcomes, particularly in those with unfavorable risk disease. Leveraging pt-level data from within the HoLISTIC (Hodgkin Lymphoma International STudy for Individual Care) Consortium, the E-HIPI was developed in clinical trial pts and validated in real-world registry pts to predict 2-year (y) PFS (Rodday. NEJM Evidence 2025). Continuous, objective, and readily measurable pre-treatment variables were considered, with sex, maximum tumor diameter, albumin, and hemoglobin included as significant predictors. Using the E-HIPI, interactive calculators for pt risk, comparison, and stratification were created (https://rtools.mayo.edu/holistic_ehipi/). Although the E-HIPI was developed and validated in both unfavorable and favorable ES cHL pts, the clinical predictors are primarily markers of unfavorable disease. In the development and initial validation cohorts, 2y PFS was 93.7% and 90.3%, respectively, the C-statistic was 0.63 in both cohorts, calibration was strong with slight underprediction of events in the validation cohort, and the E-HIPI outperformed the historic binary classification of patients as favorable or unfavorable using EORTC criteria. However, since pts in the original E-HIPI development and validation were primarily treated with ABVD chemotherapy protocols, additional validation is needed, particularly among pts with unfavorable ES cHL who were treated initially with more intensive chemotherapeutic platforms (e.g., BEACOPP-based). Thus, we conducted an external validation of the E-HIPI in pts treated on recent unfavorable ES cHL GHSG trials. Methods: The validation cohort included 2367 adults (ages 18 to 60y) with newly-diagnosed unfavorable cHL from randomized phase 3 trials conducted by the GHSG (HD14 von Tresckow. JCO 2012; and HD17 Borchmann. Lancet 2021). We calculated the predicted probability of 2y PFS events based on the E-HIPI model equation (scale 1-100%). Model performance was assessed using discrimination and calibration. Discrimination, which is the model's ability to separate high and low risk pts, was assessed using Harrell's C-statistic. Calibration, which is the model's ability to accurately predict absolute risk, was assessed by comparing observed and predicted probabilities of 2y PFS events within quintiles of predicted probabilities and estimating calibration-in-the-large (predicted minus observed event rate) and the calibration slope. Results: For pts treated on unfavorable GHSG trials, mean age was 33y, 95% had stage II disease, mean baseline E-HIPI score (i.e., predicted 2y PFS event rate) was 6.0% (SD=2.3%), and the observed 2y PFS rate was 96.2% (95%CI: 95.4-97.0%). The C-statistic was 0.65 (95% CI: 0.59-0.70), calibration-in-the-large was 0.02, and the calibration slope was 1.08 (95% CI: 0.52, 1.64). Within the lowest risk E-HIPI quintile, the observed 2y PFS event rate was 1.6%, compared with 6.1% in the highest risk quintile. Conclusions: In external validation of the recently published E-HIPI in pts with cHL treated on unfavorable GHSG trials using more intensive BEACOPP-based protocols, discrimination was similar to the original development and validation cohorts. Collectively, the E-HIPI is a treatment-agnostic prediction tool across varied treatment regimens for unfavorable ES cHL pts. Better 2y PFS in the GHSG trials than in the E-HIPI development and initial validation cohorts may have contributed to mild misclassification, likely reflecting differences in treatment regimens. This may be resolved with recalibration or incorporating granular treatment variables into future models. Additional research is needed to understand E-HIPI performance in pts with favorable disease who have even lower event rates as well as to more fully predict individualized pt outcomes across varied chemotherapy platforms and radiation received for all ES cHL pts.

Abstract Introduction: While the incidence of multiple myeloma (MM) is 2-3 fold higher in Black compared to white individuals, the impact of racial differences on treatment outcomes remains unclear due to the confounding effect of socioeconomic barriers and disparities in access to effective therapies and clinical trials. In this study, we explored the relationship between race, social deprivation, and outcomes in newly diagnosed MM (NDMM) patients (pts) receiving modern therapies with triplet or quadruplet regimens. Methods: Pts with NDMM diagnosis, who received first line treatment between 2015-2025, and had data available on response and survival outcomes were identified through the ASH Research Collaborative MM Data Hub (a real-world database with pts across 11 U.S. institutions). Data on patient demographics (age, race, ethnicity, sex), disease risk status (ISS/R-ISS stage, FISH cytogenetics), treatment regimens (triplet vs quadruplet, anti CD38 monoclonal antibody-based vs not), and disparity measures were abstracted from electronic medical records. Race and ethnicity were self-reported by pts. Social Deprivation Index (SDI) score was calculated based on ZIP code, where higher scores reflect greater deprivation. Progression free survival (PFS) was defined as time from start of treatment until progression or death. Overall survival (OS) was defined as time from start of treatment until death from any cause. Kaplan-Meier methods were used to compare PFS and OS between groups, and cox regression models with log-rank tests were used to evaluate the influence of various factors on outcomes. Results: A total of 1,743 patients were identified; 1,116 (63.8%) identified as non-Hispanic White (NHW) and 402 (23.3%) as non-Hispanic Black (NHB) [note: 85 pts (4.9%) were Hispanic but not included due to limited numbers]. The median age (years) at the start of treatment (61.8 vs. 65.6) was lower for NHB compared to NHW pts (p<0.001). The proportion of females was greater in NHBthan NHW pts(53.5% vs. 41.1%, p=0.0016). Median SDI scores were significantly higher for NHBcompared to NHW pts (68.4 vs. 39.4; respectively; p<0.001), reflecting significantly higher rates of social deprivation. While NHB ptshad higher rates of advanced stage disease (ISS III 26.9% vs. 20.9%, p=0.009), lower rates of autologous stem cell transplant (ASCT) (56.7% vs. 63.6%, p=0.014), and longer median time from treatment initiation to ASCT (6.5 vs. 5.9 months, p=0.043), the rates of standard risk cytogenetics on FISH (72.3% vs. 77.6%), and utilization of CD38 monoclonal antibody-based regimen (29.9% vs. 27.7%) were similar between the two groups. Best response after treatment initiation was similar between the NHB and NHW pts (p=0.12) with complete response 45.7% vs. 52.6% and very good partial response 37.3% vs 34.7%; respectively. However, time to best response (months) was longer in NHB pts (7.2 vs. 6.5, p=0.005). Median follow-up for OS was 4.2 years (95% CI 3.9-4.4; 182 OS events) and for PFS was 1.3 years (95% CI: 1.1-1.6; 302 PFS events) across the two groups. Unadjusted PFS was similar for NHB vs NHW pts (HR=1.05, 95% CI: 0.81- 1.36; median: 5.0 vs 4.9 years; 3-year PFS: 66% vs. 71%). Similarly, unadjusted OS was not significantly different in NHB vs NHW pts (HR=1.12, 95% CI: 0.79-1.59; 5-year OS: 86.4% vs 85.6%). Higher SDI scores were significantly associated with worse OS (HR=1.07, 95% CI: 1.02-1.12; p=0.0065) but not PFS (HR=0.99, 95% CI: 0.95-1.02; p=0.46). Though not statistically significant, univariate analyses indicated a greater impact of high SDI scores (≥70, 75th percentile across all pts) in NHW (HR=1.45, p=0.068) than in NHB pts (HR=0.78, p=0.35) for OS. Adjusting for age, sex, ISS stage, and SDI, NHB did not appear to have worse OS (HR=0.75, 95% CI: 0.35-1.60; p=0.46) or PFS (HR=1.23, 95% CI: 0.78-1.96; p=0.37) compared to NHW pts. Conclusions: Our study represents a diverse population enriched for pts who received modern day standard of care frontline therapies including triplet and quadruplet regimens with or without ASCT. Based on SDI scores, higher social deprivation levels were seen in NHB compared to NHW pts without a difference in outcomes between the two races. Our analysis supports that higher social deprivation among different races rather than race and ethnicity alone may drive differential outcomes and adjustment for factors like SDI is critical to interpretation of survival outcomes by race.

Abstract Introduction LINVO, a human B-cell maturation antigen (BCMA)xCD3 bispecific antibody, was recently approved for triple-class exposed (TCE) RRMM after ≥3 prior therapies (EU) or ≥4 prior lines of therapy (US), demonstrating high efficacy and a generally manageable safety profile. Combining LINVO with an anti-CD38 mAb, such as DARA or ISA, may provide additional benefit to pts with RRMM. Here we report pooled safety and efficacy results from the LINVO + DARA and LINVO + ISA cohorts during the dose-finding portion of the Phase 1b LINKER-MM2 trial (NCT05137054). Methods Eligible pts were aged ≥18 years with RRMM that progressed after ≥3 lines of therapy (LoTs), or ≥2 LoTs if TCE or double-class refractory (immunomodulatory drug [IMiD] + proteasome inhibitor [PI]). Prior treatment (tx) with DARA or ISA was allowed if previously tolerated and ≥6 months (mos) or ≥3 mos washout, respectively, had elapsed since last exposure. Tx began with LINVO monotherapy (Cycle [C]0; 28-day cycle) consisting of 2 step-up doses (5 mg, 25 mg) and 2 full doses (dose level [DL]1 100 mg; DL1b 150 mg; DL2 200 mg) before standard dosing of DARA or ISA was added at C1. LINVO was given once weekly in C1–3 and once every 2 weeks in C4+. At the end of 2024, dosing once every 4 weeks was implemented after C6 if a very good partial response or better (≥VGPR) was achieved. Dexamethasone premedication was required during the first 2 cycles and then given per label for DARA or ISA. Primary endpoints: dose-limiting toxicities (DLTs) and tx-emergent adverse events (TEAEs). Key secondary endpoints: overall response rate (ORR), duration of response (DOR), progression-free survival (PFS), and rate of minimal residual disease (MRD) negativity. The analyses reported here combine the LINVO + DARA and LINVO + ISA cohorts. Results As of May 7, 2025, 42 pts were enrolled. All pts were included in the safety analysis set: DL1 (DARA, n=12; ISA, n=6), DL1b (n=6; n=10), or DL2 (n=8; n=0); 37 were included in the efficacy analysis set: DL1 (DARA, n=11; ISA, n=5), DL1b (n=5; n=9), or DL2 (n=7; n=0). At baseline, all pts had received ≥1 PI (refractory to ≥1 PI: 76%) or ≥1 IMiD (refractory to ≥1 IMiD: 86%), and 21 pts (50%) had received prior DARA or ISA (refractory to DARA or ISA: 33% [DARA, n=4; ISA, n=10]). Median number of prior LoTs was 3 (range 2–8), including 50% of pts with TCE and 21% with triple-class refractory disease. Median age was 68 years (range 42–86); male, 57%; ISS stage III at study entry, 12%; high-risk cytogenetics, 31%; bone marrow plasma cells ≥50%, 31%; and soft tissue plasmacytomas, 33% (extramedullary, 12%). Median follow-up duration was 14.8 mos for DL1 (DARA 21.3; ISA 11.3), 7.6 mos for DL1b (DARA 13.5; ISA 5.2), and 5.9 mos for DL2 (all DARA), with 44%, 50%, and 63% of pts still receiving tx, respectively. The most common TEAEs were anemia (any grade [Gr] 48%; Gr 3/4 26%), neutropenia (41%; 41%), diarrhea (38%; 2%), and thrombocytopenia (38%; 17%). Cytokine release syndrome was reported in 33% of pts (all Gr 1/2 events except 1 Gr 3 event during the step-up period that fully resolved). No pts experienced immune effector cell-associated neurotoxicity syndrome (ICANS). Infections were reported in 32 pts (any Gr 76%; Gr ≥3 40%), and 3 resulted in death (1 tx related: cytomegalovirus [CMV] pneumonia; 2 tx unrelated: C. diff colitis and lower respiratory infection). One DLT was observed at DL1b in the ISA cohort (Gr 3 Epstein–Barr virus pharyngitis) and 1 was observed at DL2 in the DARA cohort (Gr 5 CMV pneumonia). Among efficacy evaluable pts, ORR was 75% at DL1 (12/16; ≥VGPR rate 75%), 93% at DL1b (13/14; ≥VGPR rate 57%), and 86% at DL2 (6/7; ≥VGPR rate 86%). Of 10 MRD-evaluable pts, all were MRD negative (<10−5by clonoSEQ or EuroFlow). The 12-mo DOR rate was 79% (95% confidence interval [CI] 52–92; median DOR not reached) and 12-mo PFS rate was 73% (95% CI 53–86; median PFS not reached). Pharmacokinetic analyses showed LINVO concentrations were not affected by the addition of DARA or ISA. ConclusionsIn pts with heavily pretreated RRMM, half of whom had prior anti-CD38 mAb exposure, the combination of LINVO and DARA or ISA was feasible, inducing a high rate of deep and durable responses, and exhibiting a safety profile similar to that reported for each individual drug. These preliminary data support continued development of LINVO plus an anti-CD38 mAb for the tx of pts with MM.

Abstract Introduction: BL and DLBCL are the two most common lymphomas associated with HIV infection. Notably, clinical trials often exclude HIV-positive patients and prior retrospective studies often lacked long-term follow-up on overall survival (OS). This has limited our knowledge about the influence of HIV status on survival in BL and DLBCL. Survival outcomes can also vary significantly across ethnic groups, influenced mostly by disparities in healthcare access and socioeconomic status. Additionally, survival rates differ among age groups, which may be attributed to tolerance to intensive chemotherapy and the presence of comorbid medical conditions. Our study primarily focused on comparing OS between HIV-positive and negative patients with DLBCL and BL in the real world. We also examined OS disparities among diverse ethnicities and age groups. Method: Patients diagnosed with DLBCL and BL were identified from the Cerner Health Facts database over five years from 2013 to 2018 using ICD-9 and ICD-10 codes. Within this cohort, individuals with a positive HIV status were identified through specific ICD-9 and ICD-10 codes. Demographic characteristics including age, gender, and ethnicity were collected for all patients, and they were stratified into distinct age groups: <20 years, 20-39 years, 40-59 years, 60-79 years, and 80+ years. OS was calculated for all patients from the time of diagnosis to time of death or hospice discharge. A multivariate cox regression model was employed to adjust for confounding variables. Results: The total number of patients diagnosed with DLBCL and BL was 10,534. Of these patients, 45.3% were female. The ethnic composition included 77% Caucasian, 10.3% African American and 12.7 % from other ethnicities. Among this population, 315 patients were HIV positive. In the cohort of DLBCL patients, 8,275 were HIV negative and 185 were HIV positive. In the cohort of BL patients, 1,944 were HIV negative and 130 were HIV positive. Among patients with DLBCL, HIV positive status had more than two-fold higher mortality rate compared to their HIV negative counterparts (HR=2.1, 95% CI 1.31 to 3.36, p=0.0018). Patients with BL who were HIV positive had no difference in OS in comparison to the HIV negative group (p=0.575). African American patients with DLBCL had almost 40% increased risk of mortality compared to Caucasian patients (HR=1.39, 95% CI 1.05-1.83, p=0.017). African American patients with BL had no difference in OS compared to Caucasian patients (p=0.3). Patients aged 60-79 years were found to have 44% higher risk of mortality compared to 40-59 age group (HR=1.44, 95% CI 1.13-1.83, p=0.0033) and patients aged 80 years or above were found to have more than two-fold higher risk of mortality in the DLBCL cohort (HR=2.16, 95% CI 1.63-2.87, p<0.0001). For patients with BL, those aged 20-39 had half the risk of mortality as compared to the 40-59 age group (HR= 0.50, 95% CI 0.28 - 0.87, p=0.014) whereas patients aged 80 or older had almost three times higher risk of mortality (HR = 2.87, 95% CI 1.81-4.57, p<0.0001). Conclusion: HIV status can significantly influence survival outcomes in patients diagnosed with DLBCL. Early identification of HIV infection, along with the initiation of prompt antiretroviral therapy and the administration of appropriate intensive chemotherapy regimens, is crucial for optimizing treatment outcomes in this patient population. Notably, our study indicates that African American patients exhibit a higher mortality rate compared to their Caucasian counterparts with DLBCL. This could be related to disparities in access to healthcare and treatment resources across different ethnicities. Moreover, it also indicates possible lymphoma biological heterogeneity in various ethnicities. Furthermore, elderly patients demonstrate increased mortality rates likely attributed to a greater prevalence of frailty, indicating the need for innovative less intense regimens for these patients with DLBCL and BL.

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 The benefit of high-dose chemotherapy and autologous stem cell transplantation (ASCT) as a consolidation strategy after initial chemotherapy in peripheral T-cell lymphoma (PTCL) is currently unclear, and a randomized trial (EA4232/PTCL-STAT) to answer this question is currently underway. Angioimmunoblastic T-cell lymphoma (AITL) is a rare, aggressive subtype of nodal PTCL with poor prognosis and unique features. Here, we report a large-scale, real-world evidence on the role of ASCT in frontline AITL management. Methods We analyzed a national cohort of 5,827 patients diagnosed with AITL between 2004 and 2020 from the National Cancer Database (NCDB). Baseline demographic, clinical, and socioeconomic characteristics were assessed. Treatment modalities included chemotherapy alone, chemotherapy with ASCT, and no treatment. Overall survival (OS) was evaluated using Kaplan-Meier method and multivariable Cox proportional hazards regression. Propensity score matching (PSM) was performed to validate ASCT's treatment effect. Results Among patients with complete treatment information (n = 5,224), the median age at diagnosis was 68 years (range 20–90). Frontline treatments included chemotherapy alone (68.6%, n = 3,584), chemotherapy with ASCT (14.6%, n = 761), and no treatment (16.8%, n = 879). Compared with patients who did not receive ASCT, those who underwent ASCT were significantly younger (median 60.0 vs 68.0 years), more frequently treated at academic centers (81.5% vs 57.9%, p < 0.001), and more likely to reside in areas with higher educational attainment (p < 0.001). They exhibited lower Charlson-Deyo comorbidity scores (CDS), with a higher proportion having a score of 0 (82.8% vs 73.6%, p < 0.001), and were more likely to have advanced-stage disease (93.0% vs 86.9%, p < 0.001). Furthermore, a higher proportion of patients who received ASCT were diagnosed in more recent years (p < 0.001). Sex, race, and IPI score distribution showed no significant baseline differences. Median follow-up time was 81.1 months (95% CI: 77.4–84.9), and the median OS was 23.3 months (95% CI: 21.3–25.2) for the entire cohort. For patients receiving chemotherapy with ASCT, the median OS was 139.2 months (95% CI: 104.2–174.2). In comparison, chemotherapy alone yielded a median OS of 23.6 months (95% CI: 21.4–25.8), while patients who received no treatment had a median OS of 4.0 months (95% CI: 2.7–5.2); overall p < 0.001. Median OS also significantly improved with more recent diagnosis eras: 20.1 months for patients diagnosed in 2004–2009 (95% CI: 16.8–23.4), 23.9 months for those diagnosed in 2010–2015 (95% CI: 21.0–26.7), and 26.7 months for patients diagnosed in 2016–2020 (95% CI: 23.1–30.4) (p < 0.001). Analyses consistently demonstrated longer median OS in female patients (27.5 vs. 20.7 months in males, p <0.001), and in patients treated at academic centers (27.5 vs. 16.4 months at non-academic centers, p < 0.001). Median OS varied by race (White: 24.0 months vs. Black: 15.2 months vs. Others: 30.3 months; p = 0.017). Patients with higher household income and higher educational attainment experienced significantly improved survival (p = 0.005 and p = 0.017, respectively). Patients with early-stage disease, lower IPI scores, and lower CDS also showed significantly longer survival (p < 0.001 for all comparisons). Multivariate Cox regression showed that chemotherapy with ASCT significantly reduced mortality risk compared to chemotherapy alone (HR = 0.438, 95% CI: 0.364–0.527, p < 0.001). No treatment significantly increased mortality risk (HR = 1.941, 95% CI: 1.634–2.305, p < 0.001). PSM analysis further validated that chemotherapy with ASCT significantly lowered mortality risk compared to chemotherapy alone (HR = 0.608, 95% CI: 0.503–0.736, p < 0.001), after matching for age at diagnosis, sex, race, income, education level, academic center, stage, CDS, and diagnosis era. Conclusion This large-scale, real-world analysis suggests that chemotherapy followed by ASCT is associated with significantly improved overall survival in patients with AITL, supported by unadjusted Kaplan-Meier analysis, adjusted multivariate Cox regression, as well as PSM analysis. These data support ASCT as an important consolidation strategy for AITL in real-world practice.

Abstract Background Mosaic chromosomal alterations (mCAs) are large-scale somatic gains, losses, or copy-neutral loss of heterozygosity (CNLOH) detectable by genotyping of peripheral blood DNA. They represent a form of clonal hematopoiesis and are observed in 0.5-5% of cancer-free individuals. The presence of any autosomal mCA has been associated with >3-fold risk of hematological malignancies. In particular, mCAs occurring in regions related to lymphoid malignancies have an 11-fold increased risk of lymphoid malignancies and a 68.6-fold risk for chronic lymphocytic leukemia (CLL). Monoclonal B-cell lymphocytosis (MBL), the precursor state to CLL, is defined by <5×10⁹/L clonal B cells in otherwise healthy individuals and is classified as low-count (<0.5x109/L) or high-count (0.5-5x10⁹/L) based on clonal B-cell count. MBL is also associated with increased risk of lymphoid malignancy (beyond CLL), with 4.3-fold and 74-fold risk in individuals with low- and high-count MBL, respectively. We previously reported a significant enrichment of autosomal mCAs in MBL, demonstrating a 1.7-fold association in those with low-count MBL and a 50.5-fold association in those with high-count MBL. Whether mCAs independently predict lymphoid malignancy risk after accounting for MBL status is unknown. Here, we evaluated the impact of mCAs on risk of incident lymphoid malignancies in individuals with MBL and in individuals screened negative for MBL. Methods CLL-type MBL (CD5 positive) was identified using flow cytometry assay on peripheral blood. Participants were age ≥40, had no prior hematologic malignancy, and were enrolled through the Mayo Clinic Biobank or the Division of Hematology at Mayo Clinic, Rochester. Participants were followed for incident lymphoid malignancy, including CLL, with diagnoses confirmed by medical record review. mCAs with cell fraction >1% were detected from array-based genotyping of whole blood DNA. Cox proportional hazards models, adjusted for age and sex, estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of developing an incident lymphoid malignancy in individuals with autosomal mCA versus those without an autosomal mCA. Results In 4,331 participants with available MBL and mCA status, the median age was 67 years, and 45% were male. Flow cytometry identified 3,231 individuals who screened negative for MBL, 754 individuals with low-count MBL, and 346 individuals with high-count MBL. Autosomal mCAs were present in 6.5% of individuals without MBL, 7.6% with low-count MBL, and 71.1% with high-count MBL. Over a median follow-up of 6.9 years, 237 individuals developed an incident lymphoid malignancy. The most common types were CLL, multiple myeloma, and diffuse large B-cell lymphoma. Ignoring MBL status, the presence of an autosomal mCA was associated with increased risk of lymphoid malignancy (HR = 2.65; 95% CI: 1.45–4.86; P = 0.002), replicating previous results. However, after excluding individuals with MBL, this association attenuated; those with mCA alone did not have a significantly elevated risk (HR = 1.60; 95% CI: 0.57-4.52; P = 0.38) compared to individuals without MBL or mCA. We next examined the effect of mCAs among individuals with MBL. In those with low-count MBL, the most frequent mCA events were 13q loss (2.1%), 12 gain (1.9%), and 4q CNLOH (1.2%), and individuals with an mCA had a borderline significant risk of developing a lymphoid malignancy (HR = 2.78; 95% CI: 1.01–7.67; P = 0.049) compared to those without an mCA. Similarly, in those with high-count MBL, the most frequent mCA events were 13q loss/CNLOH (31.2%), 12 gain (13.0%), and 11q loss (4.9%), and the presence of an mCA conferred an increased risk compared to those without mCA (HR = 1.51; 95% CI: 1.09-2.08; P = 0.012). Conclusions Autosomal mCAs were more frequent in individuals with high-count MBL compared to those with low-count or no MBL. mCAs showed limited predictive value for lymphoid malignancy among individuals without MBL. In contrast, in individuals with low-count MBL, autosomal mCAs emerged as a potential biomarker for identifying those at risk of developing a lymphoid malignancy. In high-count MBL, mCAs were also a biomarker, but were driven by known chromosomal abnormalities identified through clinical testing. These findings suggest that the utility of mCAs as a predictive marker for lymphoid malignancy is contingent on the presence of MBL and may inform risk stratification and surveillance strategies in this population.

Abstract Introduction: Monoclonal gammopathy of undetermined significance (MGUS) affects over 2 million individuals aged ≥70 in the US. Earlier detection of smoldering multiple myeloma (SMM) and multiple myeloma (MM) in individuals with suspected MGUS via bone marrow biopsy allows for earlier active monitoring and potential intervention, including with daratumumab for high-risk SMM. Risk prediction for the presence of SMM or MM with the iStopMM and Mayo Clinic models leads to decreased individual-patient and population-level resource utilization burden of bone marrow testing with the tradeoff of some missed non-MGUS diagnoses. We sought to quantify the value of earlier diagnosis, while additionally accounting for the recent results of the AQUILA trial, by assessing the lifetime cost-effectiveness of bone marrow testing strategies for patients with suspected MGUS. Methods: In this independent analysis free of industry influence, we used a decision tree with nested Markov cohort models to evaluate diagnosis and disease progression from MGUS and SMM to MM across 3 diagnostic strategies employing: (1) iStopMM risk prediction model versus (2) Mayo Clinic risk stratification and prediction model versus (3) a test-all strategy. Both risk prediction model performance characteristics were derived from the largest population-level prospective cohort study. Individuals in the MGUS state were monitored annually for disease progression with blood tests. The SMM state included two groups: those correctly diagnosed through biopsy and those misclassified as MGUS due to not undergoing biopsy under the prediction model triage rules (missed SMM diagnosis). As recommended by guidelines, diagnosed patients with non–low-risk SMM were monitored with blood tests every three months; those with low-risk SMM were tested every six months. All diagnosed SMM patients underwent imaging for bone lesions at diagnosis and annually for up to five years. Missed SMM patients were monitored at the same frequency as those with MGUS until disease progression. Early versus delayed myeloma diagnosis complications were informed by real-world multi-institutional quasi-experimental data of consecutively diagnosed patients with MM. MM treatment and outcomes across up to four lines of therapy were modeled exactly as previously published in a validated model. In additional scenario analyses, we assessed the impact of daratumumab monotherapy in the care of people with high-risk SMM across all 3 testing strategies by incorporating the progression free survival and overall survival benefit as reported in the phase 3 AQUILA study. The primary outcome was the incremental net monetary benefit (iNMB), reported across all accepted US willingness-to-pay (WTP) thresholds from a US health system perspective. We concluded with extensive deterministic sensitivity analyses and additionally quantified uncertainty across all model parameters simultaneously with 10,000 Monte Carlo simulations. Results: The iStopMM model was the cost-effective strategy yielding the highest NMB of all strategies at every WTP threshold, with per-patient cost and effectiveness of $188,300 and 10.21 QALYs, respectively. This strategy was dominant—costing less and producing more QALYs—than both the Mayo Clinic and test-all strategies. At the population level, use of the iStopMM model over the Mayo Clinic model and the test-all strategy yields iNMBs of $0.67 [95% CI: 0.2 – 1.14] billion and $3.13 [95%CI: 2.80-3.47] billion, respectively, in favor of the iStopMM strategy. The iStopMM strategy was the cost-effective strategy in 100% of 10,000 second order Monte Carlo iterations. In deterministic sensitivity analyses, the top three parameters the iNMB was most sensitive to were prediction model test characteristics (i.e., sensitivity and specificity) as well as the baseline prevalence of SMM. However, no parameter variation could change the conclusion that iStopMM is the cost-effective strategy. In scenario analyses incorporating benefit of daratumumab monotherapy in the care of individuals with high-risk SMM, the iStopMM model remained the cost-effective strategy. Conclusion: Using the iStopMM risk prediction model for marrow sampling in patients with suspected MGUS leads to cost savings per patient evaluated, both with and without incorporating daratumumab benefit in the care of individuals with high-risk SMM, as compared to both the Mayo Clinic model and testing all with bone marrow biopsy.

Abstract Introduction: TERT promoter (pTERT) variants are among the most frequent genetic alterations in human cancers, where they drive oncogenesis through telomerase reactivation. However, somatic, pathogenic pTERT variants have also been seen in non-cancerous conditions such as telomere biology disorders (TBD), where they attempt to rescue the bone marrow failure phenotype (adaptive compensation). We conducted this study to assess the phenotype and outcomes of pTERT mutations in TBD patients. Methods: After IRB approval, the Mayo Clinic institutional TBD database was queried to identify all patients with somatic pTERT mutations. We have designed a customized error corrected sequencing panel that covers somatic mutations (52 genes) associated with adaptive and maladaptive outcomes in TBD patients. This covers the promoter region for TERT and can detect variants down to 0.5% variant allele fraction (VAF) with 10,000 X sequencing depth. Clinical data was retrospectively abstracted. Results: We identified 7 pTERT variants (3 hotspots) in 6 (two females (33%), mean age 61 years, 4 alive). The three hotspots were: (1) c.-57A>C (2 individuals, mean VAF 17.1%; range 11.6%-22.6%), (2) c.-124C>T (4 individuals, mean VAF 12.9%; range 1.9%-41.3%), and (3) c.-146C>T (1 individual, VAF 1.2%). One individual had both the c.-124C>T (VAF 41.3%) and the c.-146C>T somatic pTERT variants, occurring in the context of a germline TERT variant. The median VAF for all 7 pTERT variants was 6.1% (range 1.2%-41.3%). The hotspot, c.-57A>C, occurred in the context of pathogenic germline TERT (VAF 49.9%) variants with pathogenic somatic co-variants in PPM1D (avg. VAF 1.5%). The second hotspot, c.-124C>T, occurred in the context of germline TERT (avg. VAF 49.6%) and RTEL1 (VAF 47.3%) variants with pathogenic somatic co-variants including ASXL1 (VAF 1%), DNMT3A (VAF 8%), and PPM1D (VAF 4%). Five of six assessable patients with pTERT variants had shortened telomere lengths (TL), with results pending for one individual. Among those with the c.-57A>C variant, granulocyte TLs were at or below the 10th percentile, while lymphocyte TLs were below the 10th percentile in one patient and below the 1st percentile in another. For those with the c.-124C>T variant, all granulocyte TLs were below the 1st percentile. Lymphocyte TLs in this group included one at the 10th percentile and two at or below the 1st percentile. The median follow up for all patients was 2 years. Hotspot 1 (c.-57A>C) variants were associated with normocellular bone marrow biopsies with one patient having normal blood counts and the other having chronic macrocytic anemia (grade 2) and thrombocytopenia (< grade 1). In patients with hotspot 2 and 3 somatic variants, bone marrow cellularity ranged from 15–50% (1 patient had grade 2-3 hypocellularity), with normal bone marrow morphology, except for polytypic plasma cells (10–15%) identified in a patient with IgG kappa multiple myeloma (currently MRD negative on maintenance therapy). This patient also had a history of head and neck cancer and follicular lymphoma. Of these four patients, only one had normal blood counts (co-occurring c.-146C>T variant); the rest had cytopenias (n=3, the worst being grade 2 thrombocytopenia), progressive macrocytosis (n=3), or eosinophilia (n=1). Comorbidities encountered in these patients included myasthenia gravis (1), hypogonadism (1), and sarcoidosis (1). Moreover, four patients (2 each for hotspots 1 and 2) presented with idiopathic pulmonary fibrosis, while liver fibrosis was seen in 4 patients (also 2 each for hotspots 1 and 2). At last follow up, none of these patients had documented progression to myelodysplastic syndrome or acute myeloid leukemia. Conclusions: We describe the spectrum and clinical features of somatic pTERT mutations in TBD patients. pTERT mutations involved the following hotspot regions, c.-124C>T, c.-146C>T, and c.-57A>C, and co-occurred with other somatic variants (i.e., PPM1D and DNMT3A). None of the 6 patients with pTERT mutations had a severe bone marrow failure phenotype or developed myeloid neoplasms at last follow up, exemplifying a unique mechanism of adaptive somatic rescue.

Abstract Mutations in non-coding regulatory elements are increasingly recognized as critical drivers of cancer development and progression. Among these, structural alterations such as duplications of super-enhancers (SEs), large clusters of enhancers that regulate key oncogenes, have emerged as significant contributors to oncogenesis. In T-cell acute lymphoblastic leukemia (T-ALL), a particularly aggressive hematologic malignancy, SE duplications have been identified in approximately 5% of human cases. These duplications frequently involve a non-coding region located approximately 1.3 megabases downstream of the Myc oncogene, a region known as N-Me. Despite the growing recognition of the role of SE duplications in T-ALL, functional studies to determine their molecular origins and contributions to leukemogenesis have been limited, largely due to the absence of suitable and genetically tractable preclinical models. This gap in knowledge hinders both our understanding of disease pathogenesis and our ability to design targeted therapeutic interventions. Here, we report the generation and characterization of a novel genetically engineered mouse model of T-ALL that spontaneously develops oncogenic SE duplications at the Myc locus. This model offers the first spontaneous in vivo system to investigate the origin, regulation, and oncogenic function of SE duplications. This model was created by conditionally stabilizing β-catenin in CD4⁺CD8⁺ double-positive (DP) thymocytes in combination with targeted deletion of the transcription factor HEB. This combination is sufficient to drive the development of aggressive T-cell leukemias that consistently harbor duplications of the N-Me super-enhancer. This finding recapitulates the genomic alteration observed in a subset of human T-ALL and provides a unique platform for mechanistic studies. We further demonstrate that the molecular events leading to SE duplication and oncogenic Myc activation unfold in a stepwise manner. At the preleukemic stage, stabilization of β-catenin alone is sufficient to enhance recruitment of HEB to the N-Me region. The simultaneous loss of HEB greatly increased chromatin accessibility at the N-Me enhancer. This altered chromatin landscape permits aberrant binding of transcription factors including TCF-1, which plays a critical role in T-cell development and leads to N-Me SE activation associated with significant three-dimensional chromatin reorganization. Chromosome conformation analyses in the leukemic cells reveal the formation of a novel chromatin loop that brings the activated N-Me SE into close spatial proximity with the Myc promoter, enabling oncogenic Myc transcription. These findings uncover a novel mechanistic pathway by which β-catenin and HEB interact to reshape the enhancer landscape and three-dimensional chromatin architecture, ultimately promoting SE duplication and aberrant Myc expression in T-ALL. β-catenin appears to play a dual role, first facilitating HEB recruitment under physiological conditions and then, upon HEB loss, permitting the reprogramming of enhancer activity through chromatin opening and ectopic transcription factor binding. Our data suggest that the cooperative interplay between signaling pathways and transcriptional regulators at enhancer elements can initiate structural genomic changes that drive malignancy. This work provides a long-sought preclinical model that faithfully mirrors key features of human T-ALL. Our findings open new avenues for understanding how non-coding regulatory mutations arise and exert oncogenic effects and have the potential to provide insights that may extend beyond T-ALL to other cancers driven by enhancer dysregulation. Moreover, by revealing molecular intermediates such as β-catenin, HEB, and TCF-1 in the regulation of enhancer activity, our findings identify potential therapeutic targets to disrupt the oncogenic enhancer-promoter interactions that underlie Myc-driven leukemogenesis.