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e14626 Background: Despite advancements in neoadjuvant therapy and surgical techniques, patients with pancreatic ductal adenocarcinoma (PDAC) often experience high recurrence rates after total neoadjuvant therapy (TNT) and resection. Existing tumor response scoring systems, such as the College of American Pathologists (CAP) guidelines, fail to stratify recurrence risk effectively, emphasizing the need for novel, objective approaches. Methods: This study evaluated spatial characteristics of residual cancer and stroma in a multi-site cohort of 203 patients with resected PDAC following TNT, not having achieved a major pathologic response (CAP 2 or 3). Whole slide images (WSI) of hematoxylin and eosin-stained sections were digitized and analyzed using artificial intelligence to perform tissue segmentation. Metrics quantifying spatial morphology and configuration, inspired by principles of landscape ecology, were computed to explore spatial features of the tumor microenvironment (TME). Statistical models (recursive partitioning and regression tree [RPRT] model and Cox model with backwards eliminations) incorporating these features were developed to stratify recurrence risk. Results: Five metrics were used for risk classification model build. Three models successfully classified patients into high- and low-risk groups based on spatial metrics. Models demonstrated moderate discriminatory power (C-statistics: 0.560–0.566) and showed that increased tumor fragmentation, like stromal patch density and cancer patch shape index, were strongly associated with improved outcomes. Conclusions: Integrating spatial metrics of cancer-stroma configuration enhances risk stratification beyond conventional scoring systems. Given increased tumor fragmentation is associated with improved outcomes, these data indirectly suggest ecological mechanisms of treatment resistance. This approach offers a pathway toward personalized post-operative management strategies to improve outcomes in PDAC. Risk classification models. Model Description Event/n Median DFS (95% CI) HR(95% CI) p-value C-statistics 1(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 87 / 101 8.22(5.72 – 10.1) 1.64(1.20 – 2.25) 0.002 0.562 Low risk: log standard deviation of the stroma shape index ≤ 0.651 71 / 102 11.90(9.24 – 25.1) Ref 2(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 & mean cancer shape index ≤ 1.775 58 / 63 7.23(5.19 – 9.63) 1.82(1.31 – 2.52) 0.0003 0.560 Low risk: (log standard deviation of the stroma shape index > 0.651 & mean cancer shape index > 1.775) or log standard deviation of the stroma shape index ≤ 0.651 100 / 140 11.57(9.24 – 17.92) Ref 3(Backwards elimination) High risk: PI * > median 86 / 101 8.02(6.08 – 9.86) 1.73(1.26 – 2.37) 0.0007 0.566 Low risk:PI * ≤ median 72 / 102 15.72(9.97 – 25.05) Ref *PI: (0.2701 * log mean stroma area) + (0.3905 * log edge density).

Abstract Infection is increasingly recognized as a significant cause of morbidity and mortality in patients with relapsed/refractory (R/R) large B-cell lymphoma (LBCL) receiving CD19 chimeric antigen receptor (CAR) T-cell therapy. The current study analyzed the natural history, risk factors, and outcomes of infection in 3350 patients with R/R LBCL receiving commercial CD19 CAR T-cell therapy (n = 2804 axicabtagene ciloleucel [axi-cel], n = 546 tisagenlecleucel) from December 2017 to June 2022. Infection developed in 834 patients (24.9%) within 100 days after infusion, resulting in an infection density of 0.43 per 100 patient days and a 100-day cumulative incidence of 22%. Bacterial, viral, and fungal infections were recorded in 527 (15.7%), 374 (11.2%), and 108 patients (3.2%), respectively, with corresponding infection densities of 0.23, 0.15, and 0.04 per 100 patient days. After a 24-month median follow-up, 1482 patients (44%) had died, with infection as the primary cause in 173 cases (12%). The 100-day infection-related mortality (IRM) was 1.6% (95% confidence interval, 1.2-2.0). Patients with a Karnofsky performance score of ≤80, infection history before CAR T-cell therapy, axi-cel therapy, severe cytokine release syndrome (grade ≥3), and severe immune effector cell–associated neurotoxicity syndrome (grade ≥3) had increased infection risk. Infections within 100 days were an independent risk factor for inferior overall survival beyond day 100 after CD19 CAR T-cell therapy. In conclusion, study results show a significant incidence of infection and IRM in patients with R/R LBCL treated with CD19 CAR T-cell therapy. Furthermore, results identify patients at a heightened risk of infection, offering insights to guide potential interventions aimed at mitigating infection and improving patient outcomes after CAR T-cell therapy.

6554 Background: SER-155 is an investigational, oral, live biotherapeutic product (LBP) comprised of 16 bacterial strains designed to decolonize gastrointestinal (GI) pathogens, improve epithelial barrier integrity, and modulate immune responses to prevent bloodstream infections (BSI). In the placebo-controlled cohort 2 of the phase 1b study, SER-155-001 (NCT04995653), SER-155 was generally well tolerated with a safety profile similar to placebo and the incidence of BSIs, a secondary endpoint, was significantly lower after treatment with SER-155 when compared to placebo. We report exploratory analyses of biomarkers of T cell expansion relevant for immune reconstitution after HCT. Methods: Participants were randomized 1:1 to receive 4 days of oral vancomycin (for microbiome conditioning) and 10 days of SER-155 or placebo/placebo administered pre-HCT (course 1) and post-neutrophil engraftment (course 2). Primary endpoints were safety and SER-155 strain engraftment (PK). Exploratory endpoints included plasma cytokine concentrations measured by ELISA and analysis of peripheral blood mononuclear cells (PBMCs) by flow cytometry. Results: Demographics were comparable across treatment arms. 34 of 45 randomized participants were treated and received allo-HCT (SER-155, 20; placebo, 14); 28 received course 2 (SER-155, 19; placebo, 9). SER-155 strain engraftment was observed in the peri-transplant period (median 11.5 strains after course 1) and post-HCT (median 11 strains after course 2 and HCT Day 100). Significant differences and trends in cytokines of systemic inflammation and immune homeostasis were observed relative to placebo prior to HCT Day 0 and post-HCT. On HCT Day 0, both arms had similar concentrations of IL7 and IL15 (Table 1). However, after course 2, and at HCT Day 100, significantly higher concentrations of IL7 were observed in the SER-155 arm relative to placebo (p=0.02, and p=0.003, respectively). In a preliminary analysis of PBMCs from a subset of participants, a high frequency of CD4+ T cells were observed in the SER-155 arm at the same timepoints. For homeostatic cytokine IL15, no significant differences were observed between arms. Conclusions: The significantly higher concentrations of IL7 with SER-155 treatment and observed frequency of CD4+ T cells support the potential role of the GI microbiome in promoting homeostatic expansion of peripheral T cells and immune reconstitution important for successful HCT. Clinical trial information: NCT04995653 . Median plasma IL7 and IL15 (pg/mL), SER-155 vs. placebo (generalized linear model). HCT Day or event SER-155 IL7 Placebo IL7 SER-155 IL15 Placebo IL15 D0 13.8 13.0 31.9 30.4 D7 15.1 14.6 50.9 62.6 D14 12.8 15.5 56.6 69.8 Post-neutrophil engraftment 13.4 9.0 16.3 15.4 Post-course 2 7.4* 3.9 6.2 9.1 D100 7.1** 3.5 6.2 6.2 *p<0.05, **p<0.01.

e13890 Background: Many oncology practices have reported continued use of telemedicine since onset of the COVID-19 pandemic. However, the future sustainability of telemedicine within oncology practices remains unclear, particularly because federal policies that enabled adoption in response to the public health emergency (PHE) have not been made permanent. Understanding similarities and differences in telemedicine utilization at high-volume oncology centers is crucial for shaping evidence-based policy that enables equitable access to oncology care across varying geographies. Methods: This is a cross-sectional, year-over-year, retrospective cohort analysis of trends in telemedicine utilization across all medical oncology clinical appointments conducted among adult patients (age >18) from January 2019 to December 2023 at Stanford Medicine Cancer Center (SM) – comprising multiple campuses in the California Bay Area – and the Mayo Clinic Comprehensive Cancer Center (MC) – a multiregional cancer practice with tertiary referral campuses in Minnesota, Florida, and Arizona, as well as community-based clinics throughout the Upper Midwest. Results: Both institutions exhibited a similar trend in telemedicine adoption over time. This was characterized by an initial surge in utilization following the PHE declaration in March 2020, followed by sustained utilization rates from 2021 to 2023. However, telemedicine use as a proportion of the overall practice differed significantly between institutions. At SM, the rate of telemedicine visits as a proportion of overall clinical practice was 60.3% (49,136/ 81,502) in 2021, 59.9% (52,247/ 87,215) in 2022, and 57.2% (55,007/ 96,163) in 2023. At MC, the proportion of telemedicine utilization was 12.8% in 2021 (23,873/186,086), 14.7% in 2022 (28,985/196,777), and 14.0% in 2023 (30,208/215,941). Deployment in the setting of new versus return visits also differed between institutions. In 2023, telemedicine accounted for 53.7% (6,440/11,998) of new and 57.7% (48,567/84,165) of return visits at SM, compared to 15.5% (3,359/21,728) and 13.8% (26,849/194,213) at MC. Additionally, while video visits were the predominant modality used to conduct telemedicine visits at both institutions from 2021 onward, in 2023 phone visits still made up 17.9% (5,394/30,208) of all telemedicine visits at MC, compared to just 5.4% (2,990/55,007) at SM. Conclusions: Stanford Medicine and Mayo Clinic exhibited a pattern of initial growth of telemedicine adoption in 2020, followed by sustained utilization from 2021-2023. We observed unique differences in the overall proportion, visit type deployment, and modality of telemedicine utilization between institutions. However, this study confirms telemedicine visits have remained a fixture of medical oncology care for many patients at these institutions since the COVID-19 pandemic.

5041 Background: Prior studies suggest that chemotherapy-naïve pts with mCRPC treated with AA have a higher CV event-related hospitalization risk than those treated with ENZA. To further explore this association, this real-world, comparative causal inference study used a large US dataset to assess CV event risk in chemotherapy-naïve pts with mCRPC who initiated treatment (Tx) with ENZA or AA and provide outcome data based on history of (h/o) CV disease (CVD). Methods: Using US Medicare fee-for-service claims (Jan 2010–Dec 2022), we identified chemotherapy-naïve pts aged ≥65 years with mCRPC who initiated ENZA or AA between Sep 2014 and May 2017. The primary endpoint was a 4-point major adverse CV event (MACE-4; composite of acute myocardial infarction [AMI], stroke, unstable angina/revascularization [UA/R], and heart failure). Atrial fibrillation (AFib), venous thromboembolism (VTE), and all-cause death were also analyzed. Groups were propensity score matched (PSM) to adjust for differences in pt characteristics, assessed using standardized mean difference (SMD). Cause-specific Cox proportional hazards models were used to comparethe risk of CV outcomes between intention-to-treat cohorts, with death as a competing event. Subgroup analyses were conducted based on h/o CVD. Sensitivity analysis was performed with a MACE-5 endpoint, defined as MACE-4 or CV-related death. Results: Of 6319 pts in the total study population (ENZA: 2934; AA: 3385), 2913 PSM pts were included from each group. The ENZA and AA cohorts had similar baseline characteristics even before PSM (SMD<0.1), with a mean (standard deviation) age of 78.8 (7.3) years; 76% of pts had prior CVD. Compared with pts on ENZA, pts on AA had a significantly higher risk of experiencing MACE-4—particularly UA/R—as well as a higher risk of AFib and VTE (Table). Similar results were found in the subgroup of pts with a h/o CVD and the sensitivity analyses. Additionally, pts on AA had a higher risk of all-cause death than pts on ENZA, regardless of CVD history (h/o CVD hazard ratio [HR]: 1.14, 95% confidence interval [CI]: 1.07–1.21, P =0.0001; no h/o CVD HR: 1.12, 95% CI: 1.01–1.26, P =0.036). Conclusions: This matched analysis of US Medicare beneficiaries showed an increased risk for MACE-4, AFib, and VTE in pts with mCRPC treated with AA compared to ENZA, in the overall pt population and pts with a h/o CVD. The risk of all-cause death was higher with AA in all pts. These findings provide insights into Tx decision-making for pts with mCRPC, especially those at high risk of CV events. Outcomes HR* (95% CI) P -value MACE-4 1.12 (1.02–1.24) 0.028 AMI 1.01 (0.76–1.32) 0.987 Stroke 0.92 (0.70–1.20) 0.505 UA/R 1.13 (1.01–1.26) 0.041 Heart failure 1.19 (0.90–1.58) 0.237 AFib 1.73 (1.31–2.29) 0.0001 VTE 1.37 (1.02–1.85) 0.037 All-cause death 1.13 (1.07–1.19) 0.0001 *ENZA = reference group.

5013 Background: There is no established role for the use of docetaxel with ADT and RT for HRLPC, with mixed results seen in prior RCTs. Prior work from ICECaP (Ravi et al, Eur Urol 2024) has shown that patients (pts) with very high-risk disease (i.e. 2 or 3 risk factors [RFs]: Gleason ≥8, PSA >20, ≥cT3 and/or cN1) have the poorest outcomes with RT+ADT for HRLPC, with 5-year metastasis-free survival (MFS) of ≤80%. We aimed to perform an IPD meta-analysis of the role of docetaxel with ADT+RT for HRLPC and specifically evaluate whether patients with very high-risk disease benefit from the addition of docetaxel. Methods: IPD from RCTs involving pts with HRLPC treated with RT+ADT +/- docetaxel collated by ICECaP were analyzed. “High-risk” disease was defined as presence of 1 RF and “very high-risk” disease as 2-3 RFs and/or cN1 disease. The primary outcomes of interest were MFS and overall survival (OS). Hazard ratios (HR) for MFS and OS were estimated using Cox regression, stratified by year of randomization and adjusted for age at randomization and ECOG performance status. 5-year MFS and OS rates were estimated using the Kaplan-Meier method. Subgroup analyses were performed according to the severity of disease (high- and very high-risk), and p-values for interaction were tested using the likelihood ratio test. Results: 1690 pts treated on 4 RCTs (GETUG-12, DFCI 05-043, STAMPEDE, RTOG-0521) between 2002-2015 were eligible. Median age was 65, median PSA was 23 (IQR 10-48); 154 (9%) pts had cN1 disease and 1444 (85%) received long-term ADT with RT. Median follow-up was 10 years (range: <1-15). Overall, the addition of docetaxel to RT+ADT was not associated with a significant benefit in MFS (HR=0.89 [0.76-1.05], p=0.160) or OS (HR=0.88 [0.74-1.05], p=0.167). Though there was some evidence for favoring docetaxel in pts with very high-risk disease (n=1054; MFS HR=0.86 [0.71-1.05]; OS HR=0.85 [0.68-1.07]) compared to high-risk disease (n=636; MFS HR=0.97 [0.74-1.27]; OS HR=0.95 [0.71-1.28]), there was no evidence of a significant difference in treatment effect by risk group (p-interaction >0.1). 5- and 10-yr MFS and OS in pts with high- and very high-risk disease, stratified by receipt of docetaxel, are shown in the Table. Conclusions: Some HRLPC pts with very high-risk disease may benefit from the addition of docetaxel to RT+ADT. Biomarker evaluation within this group may identify those who are candidates for treatment intensification with docetaxel with RT+ADT (+/- androgen receptor pathway inhibitors) in HRLPC. % (95% CI) High risk Very high-risk RT+ADT RT+ADT+docetaxel RT+ADT RT+ADT+docetaxel 5yr MFS 87 (82-90) 90 (86-93) 74 (71-78) 80 (76-83) 5yr OS 90 (86-93) 93 (90-96) 84 (80-86) 89 (86-92) 10yr MFS 67 (61-72) 71 (65-76) 51 (46-55) 55 (49-60) 10yr OS 74 (69-79) 77 (72-82) 62 (57-67) 67 (62-72)

e17511 Background: Cervical cancer is a significant public health concern in Sub-Saharan Africa (SSA), where it remains the leading cause of cancer-related mortality among women. SSA has the highest global incidence and mortality rates, with an estimated 110,300 new cases and 76,700 deaths in 2020. Despite this burden, data on patient characteristics and treatment outcomes remain limited. This study aims to address these gaps by analyzing current treatment patterns and outcomes for cervical cancer in SSA. Methods: A cancer dataset was established at 4 major teaching hospitals in Ghana, Kenya, Ethiopia, and Rwanda to capture data on patient demographics, disease characteristics, and treatment modalities. The dataset encompasses all cancer patients seen between 2016-2023, with over 9,000 cases collected to date. The primary objective of the dataset was to assess impact of COVID-19 pandemic on cancer care in SSA. This study conducted a retrospective analysis of cervical cancer cases within the dataset utilizing descriptive metrics. Results: A total of 2,326 patients were analyzed, with a median age at diagnosis of 56 y (48–65) and 53% having health insurance. The majority had squamous cell carcinoma (87%) and presented with locally advanced disease (FIGO stages IIB–IVA, 88%). Treatment primarily consisted of concurrent chemoradiotherapy (CRT, 34%) or radiotherapy (RT) alone (30%), while smaller proportions received chemotherapy (CT) alone (1.2%) or surgery (1.3%). A total of 33% of patients received no cancer therapy. Among 1,524 patients treated with RT, 1,180 received external beam RT with a median dose of 46 Gy in 23 fractions, using 2D planning in 60% and 3D planning in 40% of cases. Additionally, 25 patients underwent brachytherapy, with 58% receiving low-dose-rate and 42% high-dose-rate treatments. Of 1,011 patients treated with CT, 85% (n=844) completed the intended course, with a median of 4 cycles, primarily delivered concurrently with RT (95%). Only a few received CT as adjuvant (4.8%), neoadjuvant (1.6%), or palliative (3.4%) therapy. Platinum-based regimens were most common, with 43% receiving platinum monotherapy and 5% receiving platinum-taxane combinations. By the end of treatment, 27% (n=633) achieved disease-free status. After a median follow-up of 47 months (range,37–55), 42% were alive, 7% had died, and 53% were lost to follow-up with unknown vital status. Conclusions: This study reveals significant challenges in management and follow-up of cervical cancer in SSA. Most patients were diagnosed at advanced stages, with 32% receiving no treatment and 53% of treated patients lost to follow-up. These findings highlight barriers to early diagnosis, treatment access, and continuity of care. Addressing these issues requires expanding early diagnostic services, increasing vaccination coverage, strengthening healthcare infrastructure, and improving patient retention.

e23345 Background: Telemedicine enables patients to attend visits remotely and is associated with shorter wait times (i.e. scheduling-to-appointment duration). However, its impact on patient–clinic distance and wait times for new patients in high-volume surgical oncology centers remains unclear. In these centers, where appointment availability and travel distance significantly influence care decisions, understanding telemedicine’s impact on access is essential as federal policies supporting telemedicine continue to be under legislative review. To address this, we examined the relationship between new patient visit modality, distance, and wait time across demographics, providing insights to guide policy makers, and clinical practice. Methods: We extracted visit data from a multispecialty surgical oncology center in Northern California from 2019 to 2023 and used linear models with fixed effects for clinician and patient characteristics to assess the association of NPV modality with distance and wait times. We calculated distance using geodesic measurements between residential ZIP codes and care sites and derived median household income and education levels from the American Community Survey. Results: There were 10596 NPVs in 2019, and 13982 in 2023, conducted by 78 and 100 clinicians respectively. The proportion of NPV visits conducted by telemedicine increased from 0% to 28% during this period. From 2021–2023, NPVs conducted by telemedicine were more likely to fall outside the center’s 2019 catchment area (80th percentile of distance) with an adjusted odds ratio of 1.89 (95% CI 1.62, 2.21). Wait times for telemedicine NPVs was 3.0 days shorter (95% CI [2.0, 3.9]) than in-person visits. Compared to the reduction in wait times for patients aged 45–65 (2.8 days, 95% CI [1.8, 3.8]), those 80 and older had a smaller reduction (1.9 days, 95% CI [0.9, 2.8]), while patients aged 65–79 had a greater reduction (3.4 days, 95% CI [2.4, 4.5]). This effect did not significantly vary by sex, race, ethnicity, education, income, or insurance status. Conclusions: At this multispecialty surgical oncology center, new patients seen via telemedicine were more likely to reside outside the center’s traditional catchment area and had shorter wait times, with these differences varying by demographic characteristics. Strategic telemedicine integration tailored to patient needs could enhance access by reducing wait times and expanding specialized surgical oncology care to patients across broader geographic distances.

4185 Background: Elraglusib is a first-in-class inhibitor of GSK-3ß, a well-credentialed target in cancer implicated in intrinsic oncologic processes and tumor immune response. Preliminary results of the 1801 Part 3B trial (NCT03678883) showed statistically significant benefits for elraglusib+GnP versus GnP for 1-year survival and mOS in mPDAC (companion abstract: Mahalingam et al.). We investigated plasma levels of cytokines/chemokines/soluble cell receptors/growth factors (CCSG) as potential biomarkers of favorable outcomes on elraglusib. Methods: Forty CCSGs were evaluated in pre-dose plasma from patients with previously untreated mPDAC enrolled in 1801 Part 3B treated with GnP (n = 78) or elraglusib+GnP (n = 155) using a Luminex immunoassay. Using Kaplan-Meier statistics and cutpoint determination, CCSGs were assessed for OS predictive ability in the elraglusib+GnP arm. Multivariate models were constructed to predict binarized survival at 12 months using machine learning (ML). Fivefold cross-validation was used in both analyses, and all methods were applied to the GnP arm to identify elraglusib+GnP specific predictors. Results: Data shown as of November 15, 2024. Multiple CCSGs significantly stratified elraglusib+GnP patients. The most extreme prognosticators were IFN-ß (average HR = 2.34), and PD-L1 (average HR = 0.52) (HR shown as high CCSG vs low CCSG). Screening of different ML approaches ranked logistic regression at the top, and hyperparameter grid search identified stochastic gradient solver with ridge regularization as the optimal method. The model had an accuracy of 88% (SD: 3.9%) and a balanced accuracy of 80% (SD: 8.5%). IFN-beta had the most substantial effect size (odds ratio (OR) = 72.28), followed by IL-18 (OR = 23.38) and PD-L1 (OR = 15.32). All other CCSGs had an OR between 0.03 and 6.71. When this model was applied to patients in the GnP arm, accuracy was 68.4%, and balanced accuracy was 43.1%. Conclusions: Many CCSG biomarkers were identified as promising predictors of survival benefit in mPDAC patients treated with elraglusib+GnP. Both univariate statistical and multivariate ML approaches show predictive significance with high interpretability. The initial ML model is specific to elraglusib treatment, not GnP alone. These results indicate that patients’ initial immune state plays a role in response to elraglusib+GnP. However, single CCSGs for enrichment currently exclude too many patients ( > 75%), and thus, panels of biomarkers are being investigated with ML to overcome this limitation. The 1801 Part 3B clinical trial recruitment has been completed, and updated biomarker models reflective of topline OS data, available by April 2025, will be presented.

2085 Background: Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive non-Hodgkin lymphoma with no approved treatments for relapsed/refractory (R/R) patients, representing a critical unmet need. MyD88 mutations in ~70% of PCNSL patients drive Interleukin-1 receptor associated kinase 4 (IRAK4) activation, promoting NF-κB signaling, inflammation, and tumor progression. Emavusertib, a potent oral IRAK4 inhibitor, crosses the blood-brain barrier and shows preclinical synergy with Bruton tyrosine kinase inhibitors (BTKi), re-sensitizing BTKi-resistant cell lines. This study evaluates the molecular and pharmacokinetic (PK) data associated with responses to emavusertib + ibrutinib combination therapy in R/R PCNSL patients. Methods: The safety, clinical activity, and potential biomarkers of emavusertib in R/R PCNSL are being investigated in the ongoing open-label, Phase 1/2 TakeAim Lymphoma trial (NCT03328078). Pre-dose and 1.5-hour post-dose plasma samples were collected on Cycle 3 Day 1, Cycle 5 Day 1 and Cycle 7 Day 1. Cerebrospinal fluid (CSF) samples were obtained via a lumbar puncture within 1.5 hrs of collection of the post-dose plasma PK sample on Cycle 3 Day 1. Mutation analysis was based on patients’ molecular pathology reports provided by trial sites. Sequencing of archival tissues, CSF and plasma are in progress. Results: As of 06 December 2024, CSF concentration data were available for 7 PCNSL patients. The mean emavusertib concentration in CSF was 81.3 ng/ml (54.7-104.0) in patients receiving 100 mg emavusertib BID (n = 4). In patients receiving 200 mg emavusertib BID (n = 3), the mean emavusertib concentration in CSF was higher at 175.7 ng/ml (114.8-209.4), which is 2.2X the mean value in patients who received 100 mg emavusertib BID (p-value = 0.02). All 7 patients received 560 mg ibrutinib QD, and the ibrutinib concentrations in the CSF were consistent with findings from previously published clinical studies. MyD88 mutation status was available for 7 patients of which all had prior exposure to BTKi regimens. Among these, 6 patients had MyD88 mutation of which 4 patients had responded (3 complete responses and 1 partial response) to emavusertib + ibrutinib combination with duration of response (DOR) up to 18.9 months with data collection ongoing. Conclusions: Preliminary CNS pharmacokinetic data demonstrates that emavusertib concentration in CSF increases with increasing emavusertib dose. Patients with MyD88 mutations showed expected promising preliminary efficacy to emavusertib + ibrutinib combination and may overcome BTKi resistance. Enrollment in this trial is ongoing. Clinical trial information: NCT03328078 .