Citations

Abstract Background The Joint Propagation Model (JPM)‐based CenTauR scale was recently introduced to harmonize tau‐PET quantification across different radiotracers. This study examined how CenTauR harmonization enhances the comparability of tau‐PET quantification across matched cohorts using different tracers. The evaluation focused on three key aspects: (1) comparing tau‐PET positivity rates as defined by CenTauR, (2) evaluating its diagnostic accuracy for symptomatic AD, and (3) analyzing longitudinal changes in tau‐PET rates over time. Method The JPM, developed by the CPAD‐led Tau PET Harmonization Working Group (Leuzy et al., Alzheimers Dement. 2024; Figure 1A), models relationships between anchor point subjects and head‐to‐head tau‐PET SUVR data onto the CenTauR scale, providing conversion equations for multiple tracers. JPM equations were applied to [¹⁸F]flortaucipir SUVR (Meta‐temporal ROI) data from 561 cognitively impaired participants in the ADNI and OASIS‐3 studies. Using ROC analysis, we determined the CenTauR cut‐off for positivity (T+) that maximized the Youden index for discriminating between FDA‐approved positive/negative visual reads. Three separate cohorts, scanned using [¹⁸F]flortaucipir (ADNI), [¹⁸F]MK‐6240 (CPAS), and [¹⁸F]RO‐948 (BioFINDER‐2), were matched 1:1 by age, MMSE, amyloid‐β, and clinical diagnosis. CenTauR‐based metrics were compared across these cohorts. Result A cut‐off of 18 CenTauRs was found to optimally classify [ 18 F]flortaucipir PET visual reads (Figure 1B). The matching procedure identified 1089 participants (363 per cohort). The frequency of T+ using the 18 CenTauRs cut‐off for the Meta‐Temporal ROI was highly comparable across tracers across groups, except for the Aβ‐positive cognitively unimpaired group, where variability was more pronounced due to a smaller sample size (Figure 2A). Similarly, tau‐PET discriminative accuracy for symptomatic AD vs controls remained similar across [ 18 F]flortaucipir and [ 18 F]MK‐6240 (Figure 2B). In a separate sample of 212 matched participants from ADNI ([¹⁸F]flortaucipir) and AIBL ([¹⁸F]MK‐6240) with baseline and 1‐year follow‐up tau‐PET scans, 1‐year change in CenTauRs was comparable (Figure 2C). An exploratory voxelwise transformation, utilizing the Meta‐Temporal conversion equation in a representative case scanned with both [¹⁸F]flortaucipir and [¹⁸F]MK‐6240, demonstrates the potential for voxelwise CenTauR harmonization (Figure 3). Conclusion These analyses suggest that CenTauR harmonization increases the comparability of tau‐PET data acquired with different tracers. Additional validation analyses with larger cohorts including other radiotracers ([¹⁸F]PI‐2620) are underway.

ABSTRACT Chimeric antigen receptor T-cell (CART) and T-cell engager (TCE) therapies targeting B-cell maturation antigen (BCMA) are transforming the treatment landscape for relapsed multiple myeloma (MM). However, despite impressive initial response rates, most patients eventually relapse. To investigate this unmet medical need, we applied whole-genome sequencing (WGS) to MM cells from cohorts of 102 relapsed patients treated with anti-BCMA CART and TCE therapies. Several genomic alterations were associated with clinical outcomes, particularly primary refractoriness, including high genomic complexity and mutations in genes regulating plasma cell identity, which predicted resistance to therapy. Single-cell RNA sequencing further revealed that MM cells from refractory patients exhibited high proliferation signatures and reduced expression of TNFRSF17 (encoding BCMA), while were less enriched for plasma cell–associated transcriptional programs, a phenomenon we term “plasma cell identity escape.” This profile was strongly associated with immune dysregulation of CD8 T cells including increased activation and exhaustion. This evolution of MM toward a more proliferative and lineage-divergent state, refractory to the anti-BCMA T-cell redirecting therapies, was functionally validated in preclinical MM mouse models. Collectively, our results comprehensively define the cellular and molecular mechanisms underlying primary resistance to anti-BCMA therapies.

Adoptive cell therapy (ACT) has shown remarkable success in the treatment of some malignancies, particularly leukemia. However, there are multiple factors that limit the durability of ACT in solid tumors, including dose-limiting toxicities, the immunosuppressive tumor microenvironment, and T-cell exhaustion. As the manufacture and preparation of adoptive T-cell therapies allows time and adequate conditions for ex vivo T-cell engineering, forward genetic screens can identify novel genetic targets that could improve their effectiveness. CRISPR is a commonly used functional genomics tool that has been successfully used to both enhance our understanding of mechanisms of resistance and to discover potential genetic edits to improve ACT. A complementary approach, Sleeping Beauty transposon mutagenesis provides additional opportunities to identify novel genetic edits without being constrained by the annotated human genome. Here, we summarize forward genetic screens and their tools to uncover strategies to enhance ACT. Complementary approaches can be combined and improved on to identify translatable genetic editing strategies through studies that accurately recapitulate disease-specific challenges.

Abstract Chimeric antigen receptor (CAR) T-cell therapy has demonstrated remarkable response rates in relapsed/refractory aggressive B-cell non-Hodgkin's lymphoma. However, durable remissions occur in only 40% of treated patients, highlighting mechanisms of therapeutic resistance and immune escape. While cytotoxicity is principally executed by CAR T-cells, monocytes shape CAR-T cell efficacy and orchestrate cytokine-driven immunity. In this study, we defined distinct metabolic profiles of T-cell and monocyte subsets based on clinical response. Single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing (scTCR-seq) were performed on peripheral blood mononuclear cells at three timepoints: before lymphodepletion (BL), at peak CAR-T expansion (PK), and one-month post-infusion (M1). Data were processed with CellRanger v7.0.1 and analyzed with the immunopipe pipeline (Wang et al., 2025). Seurat v4.3.0 was utilized for unsupervised hierarchical clustering analysis; subsets identified included classical monocytes (CM), intermediate monocytes (IM), non-classical monocytes (NM), and monocytic myeloid derived suppressor cells (mMDSC). Metabolic profiles were compared across patients achieving ≥6-month complete remission (CR, n=16), primary refractory disease (PD1, n=4), or relapsed after a prior response (PD2, n=12). A total of 107035 T cells and 129981 monocytes from 77 serial samples in 32 patients were analyzed. CR patients had a higher T-cell:monocyte ratio than PD1/PD2 at all time points, especially at BL and PK (BL 1.2 vs 0.4, p=0.011; PK 1.3 vs 0.3, p=0.027). Clinical responses were compared with metabolic pathway analysis and identified oxidative phosphorylation (OXPHOS) as the dominant pathway. OXPHOS was consistently enriched in PD cohorts across T-cell subsets, particularly in PD1 vs CR at BL (mucosal-associated invariant T-cell (MAIT) and T peripheral memory (Tpm)), and at PK (CD4/CD8 memory precursor effector cells (MPEC) and activated MPECs (MPECa), CD4 T-helper 1 proliferating (Th1p), CD4 Th2 activated (Th2a), regulatory T-cell (Treg), CD8 naive senescent (CD8NS), CD8 T effector memory (Tem) tumor recirculating (TR), CD8 Tpm, CD8 T resident memory (Trm) TR and MAIT Tpm). By M1, OXPHOS enrichment in CD4/CD8MPECa, CD4Th2a, CD8NS, CD8TemTR reversed, now predominant in CR although CD8Tpm and CD8TrmTR remained enriched in PD1. In the monocyte subsets at BL, PD2 showed OXPHOS enrichment in CD163+ monocytes (mono), IM IL1, mMDSC SIRPA, mMDSC TGFβ, and CM IL6 subsets compared to PD1 and CR, while PD1 showed OXPHOS enrichment in IM CD38, CM TGFβ, and mMDSC HIF1A vs CR and PD2. This persisted at PK. By M1, the pattern reversed and mirrored that of T-cells, with CR patients showing OXPHOS enrichment in CD163+mono, CM IL6, CM TGFβ, IM CD38, mMDSC HIF1A, mMDSC SIRPA and mMDSC TGFβ, and additionally in CM EMT, CM p53, NM, NM CD36 vs PD1/PD2. Glycolysis/gluconeogenesis (GLY) was also enriched across subsets. In T-cells, PD1 vs CR showed GLY enrichment in CD4Th2a, CD8Tpm, CD8Tpm proliferating and MAIT Tpm at PK. In monocytes, GLY was enriched in PD1/2 vs CR at BL (CD163+mono, CM IL6) and PK (CD163+mono, IM CD18, mMDSC SIRPA). By M1, GLY metabolism was enriched in CR vs PD1/PD2 in CD163+mono, CM IL6, mMDSC SIRPA. Additional GLY enriched subsets at CR vs PD1 included CM, CM p53, EMT, IM CD38, IM IL1, mMDSC HIF1A, NM, NM CD36. Inositol phosphate metabolism (IP) was predominantly enriched in PD2 vs CR at BL (CD8NS, CD8Tcm, CD8Tpm activated), PK (CD4Th2, CD8NS, CD8Tem TR, CD8Tpm proliferating, γδT Tem) and M1 (CD4/CD8 MPECa, CD4 Th1/Th2, CD8NS, CD8Tpm, CD8 Tpm proliferating, Treg and MAIT Tpm). Notably, Treg was the only T-cell subset enriched for IP at PK in CR vs PD1/PD2. Additionally, the TCA cycle was enriched in PD1 Tregs and Th2 cells at BL and PK vs CR/PD2. A higher T-cell:monocyte ratio in CR vs PD1/PD2 supports prior evidence that elevated pre-lymphodepletion lymphocyte:monocyte ratios predict better outcomes. We identified distinct metabolic signatures in T-cells and monocytes between CR and PD1/PD2. OXPHOS enrichment in T-cells and monocytes at M1 in CR patients may reflect oxidative programming as a hallmark of sustained anti-tumor immunity. Conversely, GLY enrichment in PD1 T-cells at PK may reflect short-lived effector states lacking persistence. Overall, these findings highlight metabolic profiling as a promising predictive biomarker and therapeutic programming target to enhance CAR T-cell outcomes.

Abstract Background: Treatment of multiple myeloma (MM) has advanced dramatically over the past decade with median overall survival (OS) for newly diagnosed MM patients (pts) now exceeding 10 years. However, outcomes in pts with high-risk disease remain poor. While most pts with high-risk disease are identified through baseline cytogenetic risk stratification, presence of extramedullary disease, or R-ISS stage, there is also a population of pts who may or may not have these traditional high-risk factors who relapse earlier than expected and have similarly poor outcomes. These pts are often delineated as “functional high-risk,” but a standardized definition of this population in the era of modern myeloma therapy is lacking. Methods: Using the ASH Research Collaborative (ASH RC) Data Hub, we retrospectively searched 7,249 pts across 10 participating institutions for those with newly diagnosed multiple myeloma (NDMM) treated with a triplet or quadruplet induction regimen (with or without autologous stem cell transplant) who had response data available. We evaluated duration of response from first line therapy (PD1) on post-PD1 clinical outcomes such as: time to next treatment (TTNT), time to subsequent progression and/or death (PFS2), and OS. We also analyzed characteristics of those who did vs. did not progress at prespecified time points of interest (12-, 18-, 24-, and 36-months) from the start of induction. We utilized recursive partitioning analyses to iteratively explore all possible cutpoints and identify which one(s) provide the greatest differentiation in the risk of subsequent progression and/or death. Results: We identified 1,305 pts who met the eligibility criteria. Of these, 264 had PD1 data including 201 who had response follow-up (f/u) after PD1. Median f/u after PD1 in this population was 3.2 years, and median PFS2 f/u after PD1 (n=201) was 4.4 years. Months to PD1 was significantly associated with PFS2 (p=0.038). All prespecified time points examined showed inferior PFS2 compared to those with PD1 >36 mos, although each subgroup was not statistically significant, likely due to limited numbers in each group: PD1 <12 mos HR=1.44 (n=43; 95% CI: 0.90 – 2.30; p=0.126), PD1 12-24 mos HR=1.65 (n=30; 95% CI: 0.95 – 2.85; p=0.073), and PD1 24-36 mos HR=1.58 (n=52; 95% CI: 0.98 – 2.53; p=0.059). Similarly, timing of PD1 was also associated with OS post-PD1; pts with PD1 <12 mos had significantly lower OS compared to those with PD1 >36 mos (HR=2.35, 95% CI: 1.27 – 4.32; p=0.006). Our recursive partitioning analysis identified 30-months at the cutoff that produced the greatest differential in outcomes between those above vs. below the landmark. Approximately 23% of the pts analyzed had PD1 within 30 mos, and these pts had significantly lower OS compared to those with PD1 ≥30 mos (HR=1.99, 95% CI: 1.21 – 3.27; p=0.006). Similarly, pts who progressed within 30 mos of starting 1L therapy (n=98) had significantly shorter PFS2 (median=12.5 mos vs 22.8 mos; HR=1.55, 95% CI: 1.09 – 2.20; p=0.014) than those who did not (n=103). Those pts who progressed within 30 mos were more likely to have a higher R-ISS stage at diagnosis (p=0.048), but were not more likely to have high-risk cytogenetics (p=0.66) compared to pts with PD1 ≥30 mos. Interestingly, receiving SCT as part of 1L therapy was not significantly associated with improved PFS2 (HR=0.89, 95% CI: 0.62 – 1.29; 0.54) but was significantly associated with improved OS (HR=0.53, 95% CI: 0.31 – 0.90; 0.018) by univariate analysis. Conclusion: Our study is the first to use a large, multicenter, cohort to evaluate the definition of functional high-risk MM in the era of novel induction therapies. Our data suggest that pts who progress within 30 mos of induction on triplet or quadruplet regimens (irrespective of whether they underwent stem cell transplant) have poorer outcomes than those who progress at 30 mos or later, and that progression prior to 30 mos represents functional high-risk disease. These pts represent a clear unmet medical need, and additional focus should be taken to identify them early with the goal of designing trials to optimize their subsequent therapies.

Abstract Introduction: CTCLs are rare, heterogeneous non-Hodgkin lymphomas (NHL) with significant regional variability in treatment patterns. Prospective studies characterizing CTCL management, particularly in racially and ethnically diverse populations, remains limited. The LEO-MER multi-center prospective cohort study (NCT02736357) is designed to address the persistent disparities in outcomes research by enrolling historically underrepresented groups of patients diagnosed with lymphoma across the United States (US). Here, we present a real-world analysis of CTCL patients that reflects US academic practice, evaluating treatment patterns, as well as prognostic factors influencing survival outcomes. Methods: Patients aged ≥18 years with newly diagnosed CTCL were prospectively enrolled in either the University of Iowa/Mayo Clinic MER cohort (2002-2015) or the expanded LEO cohort (2015-2020), which included 8 US academic centers. Standardized protocols were used to abstract clinical, pathologic, treatment, and outcome data from medical records. ANOVA/Kruskal-Wallis and Fisher's/chi-square tests were used to compare patient distribution across demographic and clinical characteristics based on data distribution and sample size. Overall survival (OS) was calculated from diagnosis to death or last follow-up. Survival analyses employed Kaplan-Meier estimation supplemented by Cox proportional hazards modeling. Results: The LEO-MER cohort enrolled 223 CTCL patients (91 MER and 132 LEO). Subtypes included mycosis fungoides (MF, n=155, 69.5%), Sézary syndrome (SS, n=22, 9.9%), primary cutaneous anaplastic large-cell lymphoma (n=17, 7.6%), subcutaneous panniculitis-like T-cell lymphoma (n=11, 4.9%), cutaneous CD4+ small/medium T-cell lymphoproliferative-disorder (n=9, 4%), and other rarer CTCL subtypes (n=9, 4%). Among the MF/SS cohort, median age was 64 years (Range: 18-89 years), 58.2% (n=103) were male and race/ethnicity distribution included White (n=123, 69.5%), Black (n=29; 16.4%) and others/unknown (n=25; 14.1%). Stage distribution included 62.7% with early-stage (ES) MF (IA-IIA, n=111), 37.2% with advanced-stage (AS) MF (IIB-IVB, n=66). To complete diagnostic workup, T-cell receptor (TCR) testing was performed in 52.6% of skin biopsies (n=92) and 62.5% of blood samples (n=110), with clonal detection rates of 75% (69/92) in skin and 51.8% (57/110) in blood. Paired TCR matching between skin and blood samples was performed in 31.6% (n=56) of cases, demonstrating 53.6% (30/56) concordance. Blood flow cytometry data were reported in 80.1% (89/111) and 84.4% (56/66) of ES and AS MF cases, with T-cell population being detected in 7.2% (8/111) and 62.1% (41/66) of ES and AS cases. Nodal biopsies were obtained in 23.4% (n=41) of patients and clonality assessment was reported in 18.6% (33/177) of these cases. The MF/SS cohort's lifetime treatment exposure data (n=160) revealed topical skin-directed therapies alone (n=49, 31.8%) as the most common approach followed by lifetime exposure to topical skin-directed and systemic therapies (n=45, 29.2%) followed by multimodal exposure of topical skin-directed, radiation and systemic treatments (n=30, 19.5%). Only 5.6% of patients were enrolled in a clinical trial. First-line (1L) systemic regimens were predominantly a) immunomodulatory agents (n=47, 29.3%); including oral retinoid (n=20), extracorporeal photopheresis (n=18), interferon (n=9) followed by b) chemotherapy (n=30, 18.7%) and c) targeted therapies (n=17, 10.6%) including Brentuximab Vedotin (n=6), Romidepsin (n=5), Mogamulizumab (n=3), Vorinostat (n=2) and Pralatrexate (n=1). Multivariable analysis predicting 1L systemic treatment initiation demonstrated a significant association with presence of N2/N3 stage (N2/N3 vs N0/N1: Odds Ratio (OR): 5.45) and elevated LDH (OR: 5.30). At median follow-up of 91.1 months (mon), median OS was 122.3 mon (95% confidence interval 67.2-159.2 mon). In subset analyses, Black race (p=0.001) and SS (p=0.0001) were associated with worse OS outcomes. Conclusion: We present initial data from our prospective LEO-MER cohort, a large US-based multicenter consortia. Our findings demonstrate variability in both diagnostic staging and treatment approaches for MF/SS patients. The cohort demonstrated worse outcomes with high-risk disease and Black race/ethnicity. These findings warrant further study on the impact of underlying social determinant factors, given the variability noted in this population.

Abstract Introduction: Patients with triple-class exposed (TCE) relapsed/refractory multiple myeloma (RRMM) have historically experienced poor clinical outcomes, prompting the development of novel therapeutic options. Idecabtagene vicleucel (ide-cel) was the first chimeric antigen receptor (CAR) T cell therapy approved for this population, while teclistamab became the first approved bispecific antibody. Both target B-cell maturation antigen (BCMA) and are increasingly used in real-world (RW) settings. Most comparative evidence to date is derived from single-arm clinical trials with cross-trial adjustments. RW studies offer an opportunity to directly compare these therapies and assess their relative effectiveness in routine clinical practice. Methods: We conducted a comparative effectiveness analysis of ide-cel and teclistamab in patients with TCE RRMM using RW data from the United States Flatiron Health electronic health record-derived, deidentified database (January 2011 to April 2025 data cut). Adults who received either index therapy at any line of treatment after becoming TCE (ie, previously exposed to an immunomodulatory agent, a proteasome inhibitor, and an anti-CD38 monoclonal antibody) were included. Exclusion criteria were prior exposure to CAR T cell therapy, bispecific antibodies, or belantamab mafodotin; absence of index treatment; or lack of post-index follow-up. Index dates (T0) represent the date of infusion for ide-cel and the start of treatment for teclistamab. Seventeen prognostic covariates were selected a priori based on published rankings and used to balance treatment groups via inverse probability of treatment weighting (IPTW) with average treatment effect weights. Cox proportional hazards models were used to estimate unadjusted and IPTW-adjusted HRs with 95% CIs for progression-free survival (PFS) and overall survival (OS). As the ide-cel cohort only included infused patients, additional analyses were performed to emulate a real-world intention-to-treat population given the potential immortal time bias (patients in the ide-cel cohort were required to survive between apheresis and infusion). Specifically, patients in the teclistamab cohort who died within the first 24 days (median turnaround time for ide-cel manufacturing in United States in 2024) were excluded and 2 scenarios were performed to re-align T0 based on this 24-day period (either shifting teclistamab T0 forward or ide-cel T0 backward). Lastly, sensitivity analyses assessed differences in restricted mean survival time (dRMST) at 12 and 24 months. Results: A total of 281 patients met the inclusion criteria (ide-cel, N=106; teclistamab, N=175), with median follow-up of 22.4 and 13.7 months, respectively. IPTW adjustment balanced all covariates between groups (effective sample size: ide-cel, n=68; teclistamab, n=135). Adjusted analyses showed improved PFS with ide-cel versus teclistamab (HR, 0.67; 95% CI, 0.47–0.97), with median PFS of 11.3 versus 6.5 months. OS was also improved with ide-cel (HR, 0.59; 95% CI, 0.35–0.98); median OS was not reached in either group due to insufficient follow-up. There was a consistent trend of HRs favoring ide-cel versus teclistamab for both PFS and OS in both scenario analyses addressing the potential immortal time bias. Further, sensitivity analyses using dRMST confirmed statistically significant improvements in both PFS and OS with ide-cel across all scenarios at all time points evaluated. Conclusions: In this RW analysis, ide-cel was associated with superior PFS and OS compared with teclistamab in patients with TCE RRMM. These findings support emerging RW evidence favoring BCMA-directed CAR T cell therapies over bispecific antibodies and may inform treatment sequencing decisions in this high-risk population.

Abstract BACKGROUND Early disease progression within 24 months following chemoimmunotherapy (CIT) is an established adverse prognostic factor for overall survival (OS) in patients (pts) with indolent non-Hodgkin lymphomas. Initially reported in pts with follicular lymphoma, progression of disease (PD) within 24 months in pts with CLL treated with CIT (occurring in ~1-out-of-4 pts) is also associated with inferior OS. The prognostic utility of early event status in pts with CLL treated with targeted therapies is unknown. Recently, we reported worse than expected outcomes with BCL2 inhibitor (BCL2i) treatments in an international cohort of pts with covalent BTK inhibitor (BTKi)-resistant, CIT-naïve CLL. We hypothesize that early disease progression on first-line (1L) targeted agent treatment will identify additional pts with high-risk disease beyond conventional prognostics in the current era. METHODS We identified pts in the Mayo Clinic CLL Database with the following 1L treatments a) BTKi (+/- anti-CD20 monoclonal antibody [CD20mAb]); b) BCL2i + CD20mAb; c) BTKi + BCL2i +/- CD20mAb. PD was defined by a) new or progressive lymphadenopathy or splenomegaly; and/or b) ≥ 50% increase from nadir absolute lymphocyte count (ALC) with persistent (>2 months), and otherwise unexplained ALC ≥ 10x109/L; and/or c) Richter transformation. Logistic regression model evaluated association between clinical factors and POD36 status. OS in pts with PD within 36 months of 1L start (POD36) was evaluated and compared to those without early PD (non-POD36) with analyses: a) starting from time of PD (POD36) and starting from 3 years after 1L initiation (non-POD36); and b) Kaplan-Meier landmark analysis amongst pts alive 3 years post 1L initiation. Cox regression analyses compared a) OS from POD36 by groups and b) OS from 1L treatment with POD36 as a time-dependent covariate. RESULTS A total of 787 pts with CLL initiated 1L targeted therapy (n=538 [68%] BTKi +/- CD20mAb; n=151 [19%] BCL2i + CD20mAb; n=98 [13%] BTKi + BCL2i +/- CD20mAb. The median age at 1L start was 67 years (range 26-92 years), and 67% of pts were male. Among pts with complete CLL-IPI data (n=519), 44% and 15% had high- and very high-risk CLL-IPI risk scores, respectively. Specific pre-1L treatment disease characteristics included TP53 disruption (del17p or TP53 mutation) in 120/639 (19%), del11q in 103/634 (16%), unmutated IGHV in 406/591 (69%), complex karyotype (≥3 clonal structural or numerical abnormalities on karyotype) in 70/273 (26%), and positive CD49d expression in 229/449 (46%). The median pre-treatment beta-2-microglobulin level was 3.3 mcg/mL (range 1.2-24.4 mcg/mL). The median follow-up from 1L start was 50 months (95% CI 46-54 months). 496 pts met criteria for defining POD36 status; 72 (15%) had PD, and 424 did not. TP53 disruption (OR 2.9; 95% CI 1.5-5.7, P=0.001) was associated with POD36 on univariate analysis; complex karyotype, unmutated IGHV status, elevated serum lactate dehydrogenase level, age, sex, and inclusion of CD20mAb were not associated with POD36 status. Median OS from the time of determination of POD36 status was not reached. OS was significantly shorter after POD36 compared to non-POD36 pts (HR 3.5; 95%CI 2.1-6.0, P<0.0001), with 4-year OS estimates of 65% and 88%, respectively. When assessed by landmark analysis at the 3-year timepoint following 1L start (n=50 POD36), OS was also shorter in pts with POD36 compared to non-POD36 pts (HR 3.5; 95%CI 1.8-6.8, P=0.0002). In the overall cohort (n=787), when evaluating OS from 1L treatment with POD36 as a time-dependent covariate, POD36 status was associated with an increased risk of death (HR 4.3; 95% CI 2.6-7.1, P<0.0001) on univariable analysis; and remained an independent marker of shorter OS in multivariable analyses after adjusting for age, sex, TP53 disruption status, and IGHV status (HR 4.2; 95% CI 2.1-8.4, P<0.0001). CONCLUSIONMost pts achieved durable CLL disease control with 1L targeted treatments, and early PD occurs much less frequently than previously reported with CIT. However, among pts who receive 1L targeted therapies for CLL, PD within 36 months is associated with a ~4-fold higher risk of death. These results, if validated in larger data sets, will provide a practical measure for identifying a high-risk subgroup of pts in need of novel treatment strategies in future trials.

Abstract Introduction: Pirtobrutinib, a highly selective non-covalent BTK inhibitor, demonstrated encouraging efficacy in Richter transformation (RT) of chronic lymphocytic leukemia (CLL) in the BRUIN trial (Wierda et al, Lancet Haematology, 2024). However, a control arm was not included in this phase 1/2 trial, and how pirtobrutinib compares to usual care is unknown. To address this gap of knowledge, we sought to compare efficacy outcomes in BRUIN to that in a control cohort consisting of RT patients treated with usual care at Mayo Clinic. Methods: The study was approved by the Mayo Clinic IRB. Patient-level data from BRUIN (n=79; investigator-assessed) were obtained from the study sponsor. Patients with histologically confirmed RT (large B-cell lymphoma) who received at least one line of therapy (n=230) were identified from the Mayo Clinic CLL Database. Multivariable logistic regression was employed to calculate propensity scores for baseline covariates (ie, age at RT treatment line, number of prior lines of CLL treatment [truncated at 3], number of prior lines of RT treatment [truncated at 3], and LDH). For each Mayo patient, propensity scores for each line of RT therapy were calculated, and the line with the highest propensity score was chosen as the index RT treatment line. Using the inverse probability treatment weighting (IPTW) methodology, individual weights were computed, and standardized mean differences (SMDs) were examined for each of the unadjusted and weighted baseline covariates to ensure that balance was obtained between BRUIN cases and Mayo controls. Overall survival (OS; the primary endpoint) and progression-free survival (PFS) were analyzed using unweighted and weighted Cox proportional hazards models. Unweighted and weighted overall response rates (ORRs) and complete response (CR) rates were analyzed using logistic regression. Results: The final analysis dataset contained 79 BRUIN cases (median age 67 [range 26-95], 66% male) and 204 Mayo controls (median age 69 [range 30-89], 74% male). The BRUIN cohort had more patients with ECOG PS ≥1 (61% vs 40%, p=0.001) and elevated LDH (81% vs 63%, p=0.003) than the Mayo cohort. The proportion of patients with TP53 aberration was not statistically different in both cohorts (57% vs. 44%, p=0.15). The index line of RT treatment in the Mayo cohort included chemoimmunotherapy (n=167, 80%) and novel agent-based therapy (eg, cBTKi, venetoclax, PI3Ki, immune checkpoint inhibitor, etc; n=42, 20%). Median lines of prior CLL therapy were 2 (IQR 1-4) vs 1 (IQR 0-3) in the BRUIN and Mayo cohorts, respectively; median lines of prior RT therapy were 2 (IQR 1-2) vs 0 (IQR 0-2). The SMDs of the weighted baseline factors met pre-determined criteria (-0.25≤SMD≤0.25), indicating that balance between the two cohorts was achieved. The median follow-up was 18.3 months (range 0.7-32.9) in the BRUIN cohort and 122.8 months (range 0-280.2) in the Mayo cohort. The unweighted median OS was 12.5 months (95% CI 7.0-20.6) in the BRUIN cohort and 5.7 months (95% CI 3.9-10.7) in the Mayo cohort. The unweighted HR was 0.76 (95% CI 0.54-1.07, p=0.12). After IPTW, the weighted HR was 0.63 (95% CI 0.50-0.78, p<0.001), significantly favoring the BRUIN cohort. The unweighted median PFS was 3.6 months (95% CI 2.8-5.1) in the BRUIN cohort and 3.1 months (95% CI 2.5-4.3) in the Mayo cohort. The unweighted HR was 0.98 (95%CI 0.72-1.34, p=0.92). After IPTW, the weighted HR was 0.78 (95% CI 0.64-0.95, p=0.01), again favoring the BRUIN cohort. Response was evaluable/available in 69 patients in BRUIN and 182 patients in Mayo cohort. The unweighted ORR was 58% vs 53% in BRUIN and Mayo cohorts, respectively (OR=0.83, 95% CI 0.47-1.45, p=0.51), and the CR rate was 16% vs 36% (OR=2.94, 95% CI 1.43-5.88, p=0.003). After IPTW, the weighted OR was 0.65 (95% CI 0.45-0.93, p=0.02) for ORR, favoring the BRUIN cohort, and 1.89 (95%CI 1.23-2.86, p=0.02) for CR rate, favoring the Mayo cohort. Conclusions: This individual patient-level IPTW-based analysis demonstrated that single agent pirtobrutinib is associated with improved OS, PFS, and ORR compared to usual care in patients with RT. These results support the choice of pirtobrutinib over traditional therapies for RT. Although these results are encouraging, the durability of response to pirtobrutinib remains suboptimal. Ongoing trials and other future research will evaluate the efficacy of pirtobrutinib in combination with other treatments in this setting.