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Introduction: Corticosteroids (CS) are the standard first-line treatment for patients (pts) with chronic graft-versus-host disease (cGvHD), but pts can be unresponsive or become refractory to or dependent on CS (SR/D).Ruxolitinib (RUX), a JAK1/2 inhibitor, is approved for the treatment of pts ≥12 years of age with SR/D-cGVHD, based on the primary outcomes from the randomized, phase III REACH3 (NCT03112603) study, which demonstrated the superior efficacy of RUX vs best available treatment (BAT) in pts with SR/D-cGVHD. Here, we present the final, long-term efficacy and safety outcomes from REACH3. Methods: Pts ≥12 years of age with moderate or severe SR/D-cGVHD were randomized 1:1 to receive either RUX 10 mg twice daily (BID) or investigator-selected BAT and followed for 3 years, till discontinuation or death. The primary analysis was conducted at week 24 (Cycle 7 Day 1 [C7D1]) in randomized pts, then pts entered the extension period (C7-39) in which they continued treatment, switched from BAT to RUX (crossover cohort), or discontinued treatment and entered long-term survival follow-up (FU). Failure-free survival (FFS; key secondary endpoint), duration of response (DOR), overall survival (OS), non-relapse mortality (NRM), malignancy relapse (MR), and safety were analyzed at 3 years (week 156; final data cut off 15 Dec 2022). Overall response rate (ORR) and best overall response (BOR) during the crossover treatment period were analyzed for pts who switched from BAT to RUX on or after C7D1. Results: Of 329 pts randomized, 53 completed the treatment period and 276 discontinued, 115 entered survival FU (RUX: 73/165; BAT:42/164); 70 pts crossed over from BAT to RUX of which 16 completed the crossover treatment period and 24 entered survival FU. Median FFS was longer in the RUX vs BAT arms (38.4 vs 5.7 months; hazard ratio [HR]=0.361, 95% confidence interval [CI]: 0.268, 0.485) with 12-month FFS probabilities of 64.0% (95% CI: 56.1, 70.8) and 28.8% (95% CI: 21.8, 36.1), respectively. Median OS was not reached and there was no difference in risk of death between the arms (HR=0.851, 95% CI: 0.544, 1.331) [Table 1]. Median DOR was 6.4 months (95% CI: 4.9, 11.4) in the BAT arm but was not reached for the RUX arm; notably, the probability of maintaining DOR at 3 years was higher in RUX (59.6%; 95% CI: 50.4, 67.6) vs BAT (26.7%; 95% CI: 18.5, 35.5). NRM event rates were similar between the arms (RUX: 29/165; BAT 34/164), and MR events were similar and low in both arms (13/156 and 11/160, RUX and BAT respectively) up to 3 years. The ORR at week 24 after crossover from BAT to RUX was 50.0% (95% CI: 37.8, 62.2), including complete response (CR) in 4 (5.7%) pts and partial response (PR) in 31 (44.3%) pts. The BOR during crossover was 81.4% (95% CI: 70.3, 89.7), including CR of 7.1% and PR of 74.3%; disease progression only occurred in 1 pt. Almost all pts treated during the main treatment period (RUX: 100%; BAT: 93.7%) experienced ≥1 adverse event (AE) and, in general, AE rates were higher in the RUX vs BAT arms [Table 2], likely due to prolonged FU and exposure to RUX (median exposure to treatment of 52.9 weeks vs. 24.1 weeks for RUX and BAT, respectively).Anemia was the most common AE (RUX: 33.9%; BAT: 15.8%) and grade ≥3 AE for RUX (17.6% vs BAT 9.5%, respectively); grade ≥3 neutropenia, thrombocytopenia, alanine aminotransferase increase, and gamma-glutamyltransferase increase were also ≥5% higher for RUX than BAT. Anemia (24.2%; grade ≥3, 10.3%) and thrombocytopenia (3.8%) were the most common RUX and BAT treatment-related AEs, respectively. Infections, excluding tuberculosis, were the most common AE of special interest (77.6% vs. 68.4%; grade ≥3, 31.5% and 26.6%, for RUX and BAT, respectively). On-treatment deaths were mainly due to cGvHD (n/N, RUX: 10/18; BAT 6/12). Conclusions: After 3 years of treatment in REACH3, the longer FFS and higher DOR with RUX vs BAT indicated that cGVHD was more in control with RUX treatment. Notably, efficacy was demonstrated in pts who switched from BAT to RUX with an ORR similar to that in pts randomized to RUX. RUX was well tolerated with no unexpected toxicities and safety that was consistent with earlier studies. Overall, the long-term control of cGVHD and tolerability of RUX was demonstrated for pts ≥12 years of age with SR/D-cGvHD.

Introduction: Intravenous (IV) iron is routinely used throughout various medical specialties in addition to hematology, including nephrology, cardiology, obstetrics, gastroenterology, and neurology. While all formulations are considered safe, those with iron dextran (ID) are reported to have a relatively higher incidence of anaphylaxis, often prompting a test-dose prior to full administration. Recently, there has been an ongoing national shortage of ID, leading to higher usage of alternate formulations and need for further characterization of usage and safety. Methods: The Epic electronic health record was searched using the Slicer Dicer function to obtain information regarding intravenous iron administrations from 01/01/2021 to 08/31/2022 at the various Mayo Clinic sites throughout the United States. Adverse events were evaluated through the internal patient safety reporting system for adverse drug reactions. Serious adverse events (SAEs) were defined as those events requiring epinephrine administration, anaphylaxis, hypotension, tachycardia, or an allergic reaction (hives, rash, chest tightness, eye swelling) within 24 hours of IV iron infusion. Non-serious adverse events (NSAEs) were defined as those events requiring administration of an antihistamine, steroid, or reported gastrointestinal disturbance within 24 hours of IV iron infusion. Results: A total of 49,310 infusions were administered during the analyzed period and included the use of five formulations: ID, iron sucrose (IS), ferumoxytol (FM), ferric carboxymaltose (FC), and ferric gluconate (FG). Infusions were distributed amongst Rochester (n=23,899; 16%ID, 77%IS, 5%FM, 2%FC, 0%FG), Florida (n=5,755; 6%ID, 43%IS, 34%FM, 9%FC, 8%FG), Arizona (n=5,123; 4%ID, 81%IS, 3%FM, 11%FC, 1%FG), and the Health System (n=14,533; 3%ID, 85%IS, 9%FM, 2%FC, 1%FG). A total of 49 AEs were reported (59% SAEs; 41% NSAEs), representing 0.099% of all infusions. Most AEs were from IS (n=20; 41%), with ID (19; 39%), FM (9; 18%), and FC (1; 2%) accounting for the remainder. Both SAEs (n=13) and NSAEs (n=7) were reported with IS, with most SAEs occurring on the first dose (85%) and classified as hypotension (39%), allergic (31%), anaphylaxis requiring epinephrine (15%), and tachycardia (15%); no pre-medications were given. These IS AEs were dose independent (Table 1). The incidence of AEs for all IV iron formulations was less than 0.01% (Table 2). Conclusions: While ID was found to have a relatively higher incidence of AEs, all IV iron formulations were found to be safe. The most frequently used formulation was IS, which had a low incidence of AEs even at higher doses, suggesting feasibility for minimizing the number of infusions required to achieve therapeutic levels. Although all formulations demonstrated safety, each institution will likely individualize formulary preferences based upon location of administration (inpatient vs. outpatient), input from the various medical specialties, patient comorbidities, reimbursement patterns, and logistical constraints such as infusion chair time.

[Background] The current standard first-line treatment for acute graft-versus-host disease (GVHD), systemic high-dose steroids, induces clinical responses in a majority of patients. Flares of GVHD after initial improvement often occur during tapering or discontinuation of immunosuppression. There is no consensus regarding the definition of GVHD flare and little has been published regarding its natural history. [Methods] We retrospectively evaluated clinical data and blood samples from 968 allogeneic hematopoietic cell transplantation (HCT) recipients from 23 Mount Sinai Acute GVHD International Consortium (MAGIC) transplant centers who achieved complete response (CR) or very good partial response (VGPR) within 4 weeks of acute GVHD treatment between 2014 and 2021. VGPR was defined as the complete resolution of acute GVHD manifestations except residual stage 1 skin disease. Flares were defined as a recurrence of acute GVHD after achievement of CR/VGPR if (1) patients had an increased symptom severity of at least 1 organ stage; (2) received intensified treatment (increase in steroid dose ≥ 0.25 mg/kg or initiation of additional systemic immunosuppression); and (3) had no prior history of primary disease relapse or donor lymphocyte infusion preceding the flare. Serum samples obtained at the time of CR/VGPR and at the time of flares were analyzed for ST2 and REG3α concentrations that generated MAGIC algorithm probabilities (MAPs) resulting in previously validated Ann Arbor (AA) scores (1, 2, and 3). [Results] The median recipient age at HCT was 55 years (range: 0 to 79); 18.6% of patients had grades III-IV acute GVHD before CR/VGPR. The median maximum daily dose of corticosteroids before CR/VGPR was 1 mg/kg methylprednisolone equivalent (range, 0.1 to 3.2 mg/kg). Flares developed within 6 months following CR/VGPR in 210/968 (21.7%) patients with a median onset of 28 days (range: 2 to 448). Symptom severity at the onset of flare symptoms varied widely (grade I: 22%; grade II: 38%; grade III-IV: 41%) and the development of a flare was associated with a five-fold increase in NRM (hazard ratio [HR], 4.84 [95% CI, 3.19-7.36], P < 0.001) when considered as a time-dependent covariate in a multivariate regression model. The large majority of non-relapse deaths after flares (54/71, 76%) were due to acute GVHD or complications from its treatment. The AA scores at the time of first CR/VGPR successfully stratified patients for risk of six-month NRM (AA1: 5%, AA2: 11%, AA3: 34%, P < 0.001) (Figure A). Increasing AA score at CR/VGPR was also associated with significantly increased risk of GVHD flares (Figure B). Not only did the risk of flare increase with each rising AA score, but the number of patients with severe (grade III/IV) symptoms at flare onset also increased (AA1: 34%, AA2: 43%, AA3: 54%). We next generated a multivariate regression model of risk factors for the development of flares. High AA scores at the time of CR/VGPR (AA2: HR, 1.81 [95% CI, 1.32-2.48], P = 0.001; AA3: HR, 3.14 [95% CI, 1.98-4.98], P < 0.001), HCT from HLA mismatched unrelated donor (HR, 1.74 [95% CI, 1.00-3.02], P = 0.049), and interestingly, rapid achievement of CR/VGPR from the time of initial treatment (≤14 days) (HR, 1.84 [95% CI, 1.21-2.80], P = 0.004) were all identified as significant risk factors. Meanwhile, no other transplant, GVHD, or treatment characteristics associated with the development of flares including maximum GVHD severity, maximum steroid dose, and use of additional immunosuppressive agents other than steroids before CR/VGPR. AA scores measured at the onset of flare symptoms in 98 patients also predicted six-month NRM (AA1, 6%; AA2, 19%; AA3 42%, P = 0.01). [Conclusion] Despite advances in treatment, flares of GVHD symptoms following excellent (CR/VGPR) responses still occur in over one fifth of patients in current practice and are associated with a five-fold increase in six-month NRM. AA scores from serum biomarkers predict outcomes despite the absence of symptoms, suggesting that MAGIC biomarkers detect subclinical damage to GI crypts that can drive later recrudescence of clinical GVHD. Measurement of the MAP at the time of response to GVHD treatment may thus help to risk-stratify tapering strategies of immunosuppressive therapy.

The overall response rate (ORR) 28 days (D28) after treatment has been adopted as the primary endpoint for clinical trials of acute graft versus host disease (GVHD). ORR combines complete response (CR) and partial response (PR) because CR and PR have very similar non relapse mortality (NRM). D28 ORR has some disadvantages: first, physicians usually decide to modify immunosuppression much earlier than D28, and second, NRM does not always correlate well with ORR at D28, particularly for patients who present with intermediate risk or low risk disease. MAGIC serum biomarkers at day 14 (D14) of GVHD treatment have been shown to correlate better with NRM than clinical symptom response (Srinagesh et al, Blood Advances, 2019). We therefore hypothesized that a combination of clinical symptom severity and biomarkers at D14 of treatment would predict NRM at least as well and possibly better than clinical response at D28. We studied 1144 patients from 23 MAGIC sites who were systemically treated with at least 0.25 mg/kg/day of systemic steroids (prednisone equivalents) and had clinical data and serum samples available in the MAGIC database and biorepository. We divided the patients into a training set (n=764) and a validation set (n=380). We used 12-month NRM from the time of acute GVHD onset as the primary outcome of interest. We first trained a recursive partitioning algorithm in the training set to create a response model (MAGIC D14 clinical response) according to overall GVHD grade at both onset and D14 that predicted 12-month NRM and then applied it to the validation set. Patients that either progressed to grade III/IV GVHD, continued having grade III/IV GVHD, or only improved to grade II at D14 from grade III/IV at D0 had high NRM and were classified as non-responders. Patients with grade I/II GVHD at day 0 who had grade 0-II GVHD at day 14 and patients who improved to grade 0/I at day 14 from grade III/IV at day 0 had low NRM and were classified as responders. Although counterintuitive, responders included patients whose GVHD remained at grade II because the 12 month NRM of this group was only 20%. The new clinical model predicted NRM as well as the D28 standard response model in the validation set. When we integrated the D14 MAP biomarker score (low: ≤ 0.290 vs high: >0.290) with the new D14 clinical response (D14 MAGIC integrated response), we observed three response groups of integrated response with strikingly different 12 month NRM (8%, 35%, 76%, p<0.001), in contrast to the D28 standard response (Figure 1A, 1B). D14 complete response required MAGIC clinical response with low MAP; D14 partial response required either MAGIC clinical response with high MAP or MAGIC clinical non-response with low MAP; and D14 non-response required MAGIC clinical non-response with high MAP. The D14 response groups also displayed significant differences in 12 month OS (82%, 58%, 14% respectively, p<0.001) We then compared the D14 integrated response with the D28 standard response for 12 month NRM prediction. This D14 integrated response model was superior for time-dependent AUC (0.78 vs 0.71, P=0.03), sensitivity (0.71 vs 0.54), positive predictive value (0.52 vs 0.48) and negative predictive value (0.92 vs 0.89), with minimal loss in specificity (0.85 vs 0.87) in the prediction of 12-month NRM compared to the D28 standard response model. Using decision curve analysis, the D14 integrated response displayed higher net benefit (correct identification of patients that will experience NRM by 12 months) over the whole range of threshold probabilities/preferences for changing immunosuppression when 12-month NRM was used as the outcome. We conclude first, that the definition of response that uses onset and D14 grades is as accurate as D28 ORR model; and second, that a model using clinical grades and biomarkers on D14 more accurately predicts long term NRM than the standard D28 definition and may be useful as a clinical trial endpoint.

Introduction: CAR-T therapy is the standard of care for pts with relapsed LBCL as early as in the second line in those with early relapse or with primary refractory disease. In practice, pts who are intended to receive CAR-T, commonly require interim therapy before leukapheresis, wherein a small fraction may achieve a complete remission (CR). Having chemosensitive disease, these pts can be considered for auto-HCT. Also, there are reports indicating the efficacy of CAR-T therapy in CR pts (Strati et al., Haematologica, 2023; Wudhikarn et al., Blood Adv, 2022). We compared the outcome of pts with LBCL who received CAR-T vs. auto-HCT while in a CR. Methods: Pts aged 18-75 years with DLBCL or primary mediastinal lymphoma who received CAR-T (between 2018-2021) or auto-HCT (between 2015-2021) while in a CR by PET or CT were included in this analysis using the data from the Center for International Blood & Marrow Transplant Research (CIBMTR) registry. Primary endpoints included progression-free survival (PFS) and overall survival (OS). Treatment-related mortality (TRM) and relapse rate were among the secondary endpoints. Results: We identified 360 pts with LBCL who were in a CR before receiving CAR-T (n=79, tisa-cel 53%, axi-cel 46%, and liso-cel 1%) or auto-HCT (n=281). Median follow-up was 24.7 months (range 3.3-49.4) for the CAR-T cohort and 49.7 months (range 3.0-95.4) for the auto-HCT cohort. Selected baseline characteristics are shown in Table 1. CRs were confirmed by PET scan in 90% of CAR-T pts and 99.6% of auto-CAR-T pts (p < 0.01). The most common lymphodepletion regimen for CAR-T was Cy/Flu (82.3%) and the most common conditioning regimen for auto-HCT was BEAM (77.6%). Thirty-seven (13.2%) of auto-HCT pts had a later CAR-T but no pts from the CAR-T cohort had subsequent auto-HCT. In univariate analysis, treatment with CAR-T was associated with a higher rate of relapse at 2 years (48% vs. 27.8%; p < 0.001), a lower rate of 2-year PFS (47.8% vs. 66.2%; p < 0.001) and lower 2-year OS (65.6% vs. 78.9%; p=0.037). There was no difference in rates of 2-year TRM (4.1% vs. 5.9%; p=0.673). Similarly, focusing on patients with early (12 months) treatment failure (CAR-T =57 and auto-HCT=163), treatment with CAR-T was associated with a higher 2-year relapse rate (45.9% vs. 22.8%; p <0.001) and an inferior 2-year PFS (48.3% vs.70.9%.; p <0.001) compared to auto-HCT (figure-2) while there was no difference in 2-year OS or TRM. In the multivariable analysis of outcomes, treatment with CAR-T was associated with higher risk of relapse (HR 2.18; p < 0.0001) and an inferior PFS (HR 1.83; p=0.0011) compared to auto-HCT. There was no difference in the risk of TRM (HR 0.59; p=0.36) or OS (HR 1.44; p=0.12). Conclusions: In pts with relapsed LBCL who achieve a CR, treatment with auto-HCT is associated with a lower relapse rate and an improved PFS compared to CAR-T, including in pts with early treatment failure (within 12 months). These results are in line with previously reported improved clinical outcomes with auto-HCT compared to CAR-T in pts in partial remission (Shadman et al. Blood, 2022). The data support utilization of auto-HCT in pts with relapsed LBCL achieving a CR.

Background: Waldenström Macroglobulinemia (WM) is an indolent lymphoma with heterogeneous outcomes. The recently developed, Revised International Prognostic Scoring System for WM (rIPSS-WM) did not examine the prognostic impact of MYD88L265P, a somatic alteration present in most patients with WM. Moreover, rIPSS-WM could only be partially validated in an external cohort. Here, we report the performance of rIPSS-WM and propose a refined prognostic model with external validation. Methods: We reviewed medical records of treatment-naïve patients with active WM consecutively seen at Mayo Clinic, Rochester (MCR) between 01/01/1996 and 12/31/2017. We applied the rIPSS-WM model in patients with data available for all required parameters, including age, serum beta-2 microglobulin (β2M), serum lactate dehydrogenase (LDH) and serum albumin at diagnosis to assess the prognostic utility of this model. We then identified the dichotomized clinical and laboratory parameters prognostic for overall survival (OS) by univariate analyses (UVA) in our cohort. The significant parameters were analyzed to independently predict OS in a multivariable analysis (MVA) and to create a prognostic model, which was subsequently validated in an independent multi-institutional cohort. Results: We identified 889 patients with active WM at MCR, with a median follow-up of 8.2 [95% confidence interval (CI): 7.5-9] years. The estimated median OS for this cohort was 10.6 (95%CI: 9.7-11.4) years. Patients with available data in this cohort for the validation of rIPSS-WM (n=241) were risk stratified into very low (n=46), low (n=64), intermediate (n=58), high (n=46) and very-high risk groups (n=27) per rIPSS-WM, with the respective 5-year OS rates of 96%, 76%, 72%, 77% and 32%, demonstrating overlapping survival curves for the low, intermediate and the high-risk groups. Because rIPSS-WM could not be validated, we used the data from the MCR cohort and identified age at diagnosis of active WM, LDH >upper limit of normal (ULN), β2M >3µg/mL and albumin <3.5g/dL as statistically significant prognostic markers for OS on UVA. Notably, the presence of MYD88 L265P did not impact OS [median 11.4 years (95%CI: 10.1-not reached (NR) for MYD88 L265P genotype (n=231) versus 10 years (95% CI: 8.1-NR) for MYD88 WT genotype (n=65); p=0.33]. On MVA, LDH >ULN (HR 2.34), serum albumin <3.5 g/dL (HR 1.5) and age groups 65-75 years (HR 1.4) and >75 years (HR 2.6) were independently prognostic. Based on comparable HRs, we assigned a score of 1 point each to serum albumin <3.5 g/dL and age group 66-75 years and similarly, 2 points each for age >75 years and serum LDH >ULN per their impact on OS. Patients with the composite scores of 0, 1 and 2 were categorized as low risk, low- intermediate risk and intermediate risk, respectively. Due to similar OS for the scores of 3 to 5, these were combined to form the high-risk group of our proposed model: Modified Staging System for WM (MSS-WM). The median OS was 14.6 years [95%CI: 9.1 years-NR] for low-risk (score 0, n=71, 21%), 11.2 years (95% CI: 9.1-15.2 years) for low-intermediate risk (score 1, n=110, 32%), 8.1 years (95% CI: 6.4-12.2) for intermediate risk (score 2, n=81, 24%) and 5.5 years (95 % CI: 3.9-11 years) for the high-risk group (score ≥3, n=79, 23%); p<0.0001. In this derivation cohort, the 5-year OS rate was 93%, 82%, 69% and 55% and 10-year OS rate was 60%, 53%, 45% and 30% for the low, low-intermediate, intermediate, and high-risk cohort, respectively ( Figure 1A). We also validated MSS-WM using competing risk analysis (p=0.001) and in the cohort of rituximab treated patients (p<0.0001). We then used data from an independent series of 335 treatment-naïve symptomatic patients from academic institutions (n=5) across the US and Europe for external validation of the MSS-WM model. The median follow-up for the validation cohort was 6.3 years (95% CI: 5.5-7.2 years). The 5-year OS was 93%, 90%, 75% and 57% and the estimated 10-year OS was 91%, 80%, 64% and 35% for the low risk (n= 86, 26%), low-intermediate (n=107, 32%), intermediate (n=86, 26%) and high-risk (n=59, 18%) cohorts, respectively (p<0.0001, Figure 1B). Conclusions: Our proposed model, MSS-WM, is a simple, clinically useful, externally validated model that reliably risk stratifies previously untreated patients with active WM into four groups that have distinct outcomes based on the composite scores derived from the patients' age, serum albumin and serum LDH at diagnosis.

Background: Monoclonal B-cell lymphocytosis (MBL) is a precursor condition to chronic lymphocytic leukemia (CLL) characterized by the presence of circulating monoclonal B-cell populations in the peripheral blood of otherwise healthy individuals. MBL increases risk of several adverse clinical outcomes, including development of hematological malignancies. Mosaic chromosomal alterations (mCAs) are a form of clonal hematopoiesis which affect large segments of DNA and include gains, losses, and copy number neutral loss of heterozygosity events. mCAs can be detected from SNP-array genotyping. Prior work has suggested mCAs as a potent risk factor for hematological malignancies. However, the nature of the relationship between mCAs and MBL is unknown. We sought to determine 1) the association between mCAs and MBL and 2) their combined effect on risk of hematological malignancies, in a large, prospectively collected, and well-annotated cohort of individuals with known MBL, mCA, and clinical outcomes. Methods: We examined the prevalence of mCA in a cohort of individuals from the Mayo Clinic Biobank who were screened for MBL using a sensitive eight-color flow cytometry assay. We classified MBL by the size of the clone relative to total B-cells, with high count (HC) defined as those individuals who had a percent clonal B-cell count ≥85% out of total B-cell count and low-count (LC) otherwise. Autosomal mCAs were detected from whole blood DNA collected at the time of MBL screening using a SNP-array-based assay. The MoChA pipeline was used to identify mCA events. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). To examine incident hematological cancers, we identified and validated all hematological cancers through medical record abstraction using the International Statistical Classification of Diseases codes. Cox regression was used to calculate hazard ratios (HR) and 95% CIs, stratified by MBL status or autosomal mCA status. All models were adjusted for age and sex. Results: We evaluated the prevalence of autosomal mCA in 3,764 individuals (792 individuals with MBL of whom 64 had HC-MBL and 2,972 without MBL). The prevalence of autosomal mCA was 7.7% ( n=288) with a median mCA cell fraction of 0.09 (range 0.01-1). Among those with and without MBL overall, the prevalence of mCA was 15.5% ( n=123) and 5.6% ( n=165), respectively (Figure 1). Compared to those without an autosomal mCA, individuals with an autosomal mCA were 2.4-fold more likely to have MBL (95% CI 1.9-3.2; P =2.0x10 -11; Figure 1). CLL-associated mCA (i.e., those commonly altered in CLL including trisomy 12 and deletion of 6q, 11q, 13q, and 17p) were present in 42 individuals, of whom 38 (90.5%) had MBL overall and 30 (71.4%) individuals had HC-MBL. Compared to those without a CLL-associated mCA, individuals with a CLL-associated mCA were 539.39-fold more likely to have HC-MBL (95% CI 190.3-1975.9; P <2.0x10 -16) and 6.7-fold more likely to have LC-MBL (95% CI 2.0-26.5; P =0.0031; Figure 1). Next, we evaluated the relationship between MBL and mCA with risk of developing a hematologic malignancy in 3,009 individuals with follow-up data (median 10 years). Forty-one individuals developed an incident hematological malignancy (68.3% lymphoid). When we evaluated the effect of autosomal mCA stratified by MBL status we observed elevated but non-significant risk of hematological malignancies (Figure 2). When we evaluated the effect of MBL stratified by autosomal mCA status we observed elevated and significant increased risk of developing a hematological malignancy (Figure 2). Conclusions: We found that the presence of an autosomal mCA is highly associated with having MBL. In particular, >90% of CLL-associated mCA carriers had MBL with ~7- and ~540-fold increased association for LC- and HC-MBL, respectively. These results suggest that almost all individuals in large biobanks with CLL-associated mCAs have undiagnosed MBL. However, not all individuals with MBL have an mCA. When evaluating risk of hematological malignancies, we found autosomal mCAs had >2-fold elevated but non-significant effects when stratified by MBL status while MBL remained a significant risk factor regardless of autosomal mCA status. Collectively these results support that MBL remains an important risk factor and suggests that mCAs hold potential to identify a subgroup of individuals at greater risk of developing a hematological malignancy.

Background: Data on the clinical activity of venetoclax (ven) in lymphoplasmacytic lymphoma (LPL) are primarily limited to a phase 2 trial of ven monotherapy for a 2-year duration in 32 patients (pts) with relapsed/refractory IgM LPL who received a median of 2 prior treatments (tx), including 16 pts with prior BTK inhibitors (BTKi) (Castillo et al, JCO 2021). Overall response rate (ORR) was 84% and median progression-free survival (PFS) was 30 months (mos). We report the clinical activity of ven and prognostic factors associated with outcomes in a larger cohort. Methods: We included pts with LPL treated with ven alone at 9 US centers. The primary outcome was ORR, which included minor response (MR), partial response (PR), very good PR (VGPR), and complete response (CR) per IWWM-7. Secondary outcomes included PFS, overall survival (OS), safety of ven, and predictors of ORR, PFS, and OS. Results: Sixty-two pts were included. Twenty pts (32%) received ven on a clinical trial. At ven initiation, median age was 65 years (range 38 - 87) , 61% were male, serum monoclonal (M) protein was IgM in 50 pts (91%) (IgG/IgA in 3 (5%), absent in 2 (4%), missing n=7), median hemoglobin (Hb) was 10.4 g/dL (range 5.7-16.4), and median serum IgM was 2580 mg/dL (range 5-9300). Mutations of MYD88 and CXCR4 were present in 52 (95%; missing n = 7) and 19 (38%; missing n = 12) pts, respectively. Median lines of tx (LOT) before ven was 3 (range 1-11, 58% ≥3) including antiCD20 monoclonal antibody n=54 (87%), BTKi n=48 (77%), proteasome inhibitor n=40 (65%), and bendamustine n=31 (50%). Pts who received ven on a clinical trial were less heavily pretreated (median prior LOT = 1.5, 20% ≥3) compared with pts treated off trial (median prior LOT = 4, 76% ≥3). ORR to prior BTKi was 71% (CR 4%, VGPR 10%, PR 35%, MR 21%) (missing n=5), with a median duration of tx of 14 mos (range 0.5-119). BTKi was stopped due to progressive disease (PD) in 60% and toxicity in 40%. ORR to most recent tx before ven was 58% (CR 3%, VGPR 8%, PR 32%, MR 15%); 21% SD, 7% PD, and 15% missing. BTKi was the most frequently used tx immediately before ven (48%). Six pts (10%) required plasmapheresis up to 30 days before starting ven. Median time from diagnosis to ven initiation was 5.9 years (range 0.3-23). Ven starting dose was 200 mg in 33 pts (55%), 20 mg in 11 (18%), and 100 mg in 10 (17%) (other n=6, missing n=2). Ten pts (17%) were admitted for ven tx initiation. Maximum ven dose was 400 mg in 16 (27%) and 800 mg in 38 pts (63%) (other n=6, missing n=2). ORR to ven (missing n=3) was 73% (95% confidence interval [CI] 63-86%) (CR 2%, VGPR 21%, PR 44%, MR 7%); 23% were refractory (SD 13%, PD 10%). Median time to best response was 4 mos (range 0.5-30). Median time to peak Hb was 5 mos (range 0.1-24) and to nadir serum M protein level was 8 mos (range 0.5-34). With a median follow-up of 21.9 mos (range 2.3-70.4), the median and 3-year PFS were 30.4 mos (95% CI 11.0-38.6) and 40% (95% CI 25-54%), respectively (Figure). Median and 3-year OS were not reached (NR) (95% CI NR-NR) and 83% (95% CI 70-91%), respectively. Lymphoma was the most common cause of death (n=8/11, 73%). In univariable analyses (UVA), tx with ven on a clinical trial was associated with higher ORR (90% vs 64%; odds ratio = 8.67, 95% CI 1.04-72.16, p=.046) and superior PFS (median 39 mos (95% CI, 28.4-NR) vs 11 mos (95% CI 6.4-NR), p=.028) without a significant difference in OS. Other factors evaluated in UVA to assess association with ORR, PFS and OS were age at ven start, response to last prior tx, prior tx with BTKi, and CXCR4 mutation status. Of these, receipt of prior tx with BTKi was associated with inferior PFS (HR=2.7, 95% CI 1.1-6.5, p=.024), whereas age >65 years at ven start (HR=8.6, 95% 1.1-67.8, p=0.042) and receipt of ≥3 prior tx (HR=12.0, 95% 1.5-95.9, p=.019) were associated with inferior OS. Four pts (7%) developed laboratory tumor lysis syndrome (TLS) including 2 (3%) with clinical TLS. TLS occurred at the 400 or 800 mg dose in 3 pts (missing n=1). Ven dose interruptions and/or reductions occurred in 39%. Three pts (5%) had febrile neutropenia. Ven was stopped due to PD in 21 pts (34%), planned tx completion in 15 (24%) (median tx duration = 25 mos, range 24-28), toxicity 6 (10%), and other 4 (6%); 16 pts (26%) remain on ven. Median duration of tx for those who stopped ven was 12 mos (range 1-33). Conclusion: Ven is an effective tx option for pts with relapsed or refractory LPL. Compared with the phase 2 study, ORR and PFS were lower in this cohort of more heavily pretreated pts.

Background: Prognostic modeling allows personalized risk prediction for individual patients (pt). The A-HIPI model in advanced stage classical Hodgkin lymphoma (AS-HL), developed and validated by the HoLISTIC Consortium (www.hodgkinconsortium.org), generates the individualized probability of a progression-free survival (PFS) event or death (OS) within the first 5 years (y) from diagnosis in pts based on continuous variables (www.qxmd.com/calculate/calculator_869/a-hipi). Clinical prognostic tools in lymphoma (eg, IPS, IPI, FLIPI, etc) typically use groupings of categorical values to define risk. Grouping a continuous value often results in loss of information, and most tools are not predictive for individual pts. However, discrete groupings have clinical utility & practicality for a) defining pt populations for clinical trials & real world studies, b) stratification within clinical trials, and c) crafting treatment guidelines. We studied potential approaches for utilizing the A-HIPI model to generate risk groups with input on strengths & limitations from the HoLISTIC modeling team & clinical experts. Methods: The A-HIPI model was developed via TRIPOD guidelines on 4,022 pts treated on 8 international clinical trials for AS-HL (Rodday. JCO 2023). External validation was performed on a dataset of 1,431 pts from 4 prospective registries. The 5y PFS (PFS5) in the A-HIPI development dataset was 77% (95% CI: 76-78); the 5y OS (OS5) was 92% (95% CI: 91-93). This represented the average outcome for a pt with AS-HL pt naïve to other clinical data at presentation. The distribution of PFS5 & OS5 predictions were heavily skewed (ie, asymmetric distribution) in both the A-HIPI discovery and validation dataset. While not unexpected due to the excellent PFS & OS in this disease setting, this presents challenges in the delineation of risk groups as depicted below . Three approaches were examined for the generation of A-HIPI risk groups. Proposed cutoffs were defined using the distribution of A-HIPI risk scores and data from the model-building cohort (ie, clinical trials). Validation was done using the A-HIPI validation cohort (ie, HL registries). Results: Approach 1: Risk groups based on clinical thresholds. Clinicians were queried what estimates of PFS5 would constitute high vs low risk. The positive, right-skewed distribution of A-HIPI risk scores limited this approach ( Figure), as cutoffs of PFS5 <70 and PFS5> 90 would only identify 15% and <1% of the population, respectively. Approach 2: Risk groups based on deviation from “average” pt. The 5-y PFS was 77% (95% CI: 76-78). We explored defining “standard risk” based on this confidence interval as well as clinical boundaries, with pts above or below this classified as decreased or increased risk, respectively. Results of a +/-5% clinical boundary are presented in the Table. Approach 3: Risk groups based on “ranking” of pts. Here we ranked the A-HIPI risk scores of the 4022 AS-HL pts in the model building cohort and used the distribution of the risk scores as a benchmark. The risk profile for a future pt is then compared to this distribution (eg, how do you rank compared to your peers). Continuous results are often presented this way (eg, tertiles or quartiles). It also allows flexibility for the user to define the size of the risk groups and/or clinical threshold of interest. Application of this approach showed good alignment between the predicted model percentiles and the observed distribution of scores in the validation cohort ( Table). This is also reflected in calibration curves presented in the primary manuscript. An online application (eg, R-Shiny) will be provided at the meeting to allow users to define their own cutoffs to aid in pt prognostication as well as identify populations for clinical trial development. Conclusions: There are challenges with defining risk groups from individual risk prediction modeling in AS-HL. Different applications and purposes, the skewed distribution of events/risk estimates, as well as varying clinical definitions of high risk, make it challenging to define consensus expert-based risk groupings for AS-HL. A flexible “rank-based” approach appeared to provide the most clinical utility & data granularity, which may be leveraged for clinical trial design and pt stratification. Further analysis and discussion of how to optimally define high-risk and low-risk populations in AS-HL will be needed as new therapeutic options emerge.

Background Peripheral T-cell lymphomas (PTCLs) comprise a rare, heterogeneous group of non-Hodgkin lymphomas of mature T-cell origin. Most systemic (s) PTCL subtypes typically have poor outcomes with conventional anthracycline-based chemotherapy. Biomarker-driven and subtype-specific treatments are promising but unmet needs. Few benchmark studies exist to characterize the current real-world landscape of clinical and pathologic practice. We report the patterns of care and updated outcome data for PTCL patients enrolled in the LEO-MER multi-center prospective cohort study (ClinicalTrials.gov NCT02736357). Methods Patients aged 18 years or older with newly diagnosed PTCL were prospectively enrolled in the University of Iowa/Mayo Clinic MER cohort (2002-2015) or the expanded LEO cohort (2015-2020). Clinical, pathology, treatment, and outcome data were abstracted from medical records using a standard protocol in both cohorts. Pathology underwent expert re-review based on WHO criteria. Overall survival (OS) was calculated from date of diagnosis to date of death or last follow-up. Event-free survival (EFS) was calculated from date of diagnosis to disease progression, initiation of 2 nd line therapy, or death from any cause. EFS and OS were evaluated using Cox model and Kaplan-Meier estimator. Log-rank test was used to test the significance of difference between groups. Results LEO-MER enrolled 1132 PTCL patients during the study period (462 MER and 670 LEO). Of these, 722 were sPTCLs (281 MER and 441 LEO), including PTCL-NOS (N=253, 35%), anaplastic large cell lymphoma (ALCL; N=180, 24.9% [74 ALK+, 106 ALK-]), angioimmunoblastic T-cell lymphoma (AITL, N=164, 22.7%), extranodal NK-TCL (N=50, 6.9%), adult T-cell leukemia/lymphoma (N=33, 4.6%), enteropathy-associated TCL (N=19, 2.6%), and hepatosplenic TCL (N=13, 1.8%) ( Table 1). Median age at diagnosis was 60 years. M:F ratio was 1.5. Comparing LEO to MER, African American population was 15.4% vs 0.7%, and Hispanic was 10% vs 2.2%. Clinical characteristics were comparable between MER and LEO overall: PS≥2, 20.9%; elevated LDH, 50.7%; stage III-IV, 67.6%; and IPI 2-5, 65.7%. The most common 1 st line chemotherapy regimens overall were CHOP-based (N=506, 70%), including 60% receiving CHOP-like chemotherapy in both MER and LEO cohorts (CHOP [N=268, 37%], CHOEP [N=91, 13%] or EPOCH [N=75, 10%]), and 16% with CHOP-like in combination with novel agents in LEO cohort (BV+ [N=41, 9.3%], azacitidine+ [N=11, 2.5%], pralatrexate+ [N=10, 2.3%], lenalidomide+ [N=8, 1.9%]) ( Table 1). More patients received etoposide in LEO (40.3%) than in MER (20.3%). 74 patients (10.3%) underwent consolidative SCT following induction chemotherapy (71 auto and 3 allo). 65 patients (11.2%) received frontline therapy on clinical trials. At a median follow-up of 9.4 years in MER and 4 years in LEO, 177 (MER) and 269 (LEO) events, and 150 (MER) and 206 (LEO) deaths were observed, respectively. The 3-year EFS and 4-year OS estimates for sPTCL were 46.3% and 59.1% in MER, and 40.4% and 51.3% in LEO. EFS and OS correlated with IPI scores and differed by sPTCL subtypes ( Figure 1). ALCL had superior survival, with 3-year EFS and 4-year OS of 78.2% and 90.5% for ALK+, and 65.9% and 76.9% for ALK-. Non-ALCL subtypes including PTCL-NOS and AITL had inferior outcomes, with 3-year EFS and 4-year OS of 31.4% and 42.8% for PTCL-NOS, and 33.4% and 50.7% for AITL. In subset analysis, the addition of etoposide to CHOP chemotherapy as either CHOEP or EPOCH was associated with improved OS for ALK- ALCL (p=0.038, log-rank), but not for ALK+ ALCL (p=0.75) or non-ALCL subtypes of PTCL-NOS and AITL (p=0.88). Conclusion The LEO-MER study is the largest prospective cohort study of PTCL to date. Patterns of care in the LEO cohort begin to incorporate novel agents in frontline therapy. Outcomes continue to mature with longitudinal follow-up and ongoing accrual, which poise to shape benchmarks in the contemporary era. The lack of benefit of etoposide adding to CHOP induction and poor overall survival of non-ALCL subtypes underscores the unmet need of therapeutic breakthrough for non-ALCL frontline treatment, particularly through clinical trials with biomarker-guided approaches incorporating novel agents.