Citations

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

Abstract Introduction: Outcomes for FL have markedly improved, and the 10-year (yr) overall survival (OS) for patients (pts) diagnosed in the rituximab era is about 80%. Historically, FL is the leading cause of death in the first decade after diagnosis (dx); however, modern outcomes beyond 10 yrs after dx remain unknown. Here we report long-term outcomes of FL from a large prospective cohort of pts with FL from the rituximab era. Methods: Pts with biopsy-proven FL 1-3A at dx were prospectively enrolled within 9 months of dx from 2002-2015 in the MER. Outcomes of interest were OS, event-free survival (EFS), histologic transformation (HT), and cause of death. HT was defined as subsequent biopsy-proven FL 3B, diffuse large B cell lymphoma, or high-grade B cell lymphoma. Analyses were performed using Cox models and KM curves; cause of death was evaluated using a competing risk approach. A subset analysis was performed in younger (18-59 yrs) vs older (60+ yrs) pts. A landmark analysis was conducted in pts alive at 10 yrs. Results: 1,155 pts with FL 1-3A were enrolled in the MER from 2002-2015. Median age at dx was 60 yrs (IQR 51-69). Clinical characteristics were: 67% stage III/IV, 12% grade 3A, 4% ECOG PS 2-4, and 19% elevated LDH. Initial management was 35% observation (obs), 12% R-monotherapy (R-mono), 39% immunochemotherapy (IC; 43% R-CHOP, 28% R-CVP, 27% BR), and 14% other. FLIPI scores were 40% low, 33% intermediate (int), and 27% high; FLIPI24 risk categories were 49% low, 25% int, and 26% high. At a median follow-up of 14 yrs (IQR 11-18 yrs), 751 events, 148 HTs, and 402 deaths were observed. EFS estimates (95% CI) were: 10-yr: 40% (37-43), 15-yr: 31% (28-35), and 18-yr: 27% (24-31). 15 yr & 18 yr EFS by initial txs were 22% (18-27) & 18% (14-25) for obs, 30% (23-40) & 18% (11-30) for R-mono, and 40% (35-46) & 38% (33-45) for IC. The incidence (95% CI) of HT was 12% (10-14) at 10 yrs, 13% (11-16) at 15 yrs, and 14% (12-17) at 18 yrs. OS (95% CI) for the entire cohort was 77% (75-80%) at 10 yrs, 63% (60-66) at 15 yrs, and 55% (51-59) at 18 yrs. The incidence of non-lymphoma-related death (non-LRD) surpassed lymphoma-related death (LRD) after 12 yrs in pts with known cause of death. Estimates (95% CI) for LRD were 11% (10-13) at 10 yrs, 14% (12-17) at 15 yrs, and 16% (14-19) at 18 yrs, while estimates for non-LRD were at 8% (7-10) at 10 yrs, 17% (15-20) at 15 yrs, and 22% (19-26) at 18 yrs. Among pts diagnosed before age 60, LRD remained the predominant cause of mortality into the second decade following dx, with incidences (95% CI) of LRD vs. non-LRD of 7% (5-9) vs 3% (2-4) at 10 yrs, 10% (8-13) vs 5% (3-8) at 15 yrs, and 13% (9-17) vs 6% (4-10) at 18 yrs, respectively. In patients age >60 non-LRD was the predominant cause of mortality in the second decade. Incidence of LRD vs. non-LRD in those aged ≥60 at dx were 15% (13-19) vs 13% (10-16) at 10 yrs, 18% (15-22) vs 28% (24-32) at 15 yrs, and 20% (16-24) vs 35% (31-41) at 18 yrs, respectively. In the landmark analysis of pts alive at 10 yrs from dx (n=720), median age was 69 yrs (IQR 60-77). 63 pts (9%) had HT prior to landmark. The median number of prior treatments was 1 (IQR 1-2, range 1-8). Risk of death (95% CI) was 19% (15-22) in the next 5 yrs (i.e. 15 yrs from dx) and 29% (24-33) in the next 8 yrs (18 yrs from dx). The risk of LRD vs non-LRD was 4% (3-6) vs 12% (9-15) at 5 yrs and 7% (3-9) vs 18% (10-23) at 8 yrs.Conclusions: Long-term outcomes for pts with FL remain excellent into the second decade from dx. HT risk decreases significantly after 10 yrs, though late HTs still occur. At 15 yrs from dx, 40% of pts remained alive and event-free after 1L IC. Nearly a quarter of pts observed at dx remained treatment-free. The most common cause of death after 10 yrs from dx was from non-lymphoma causes, notably in older pts aging into their 70s and 80s. While younger pts have a lower overall risk of LRD compared to older pts, FL represents the leading cause of death in this population during the second decade following dx. These results provide critical insights into the natural history of FL diagnosed in the modern era.

Abstract Introduction: cBTKi have made a substantial impact in pts w/ MCL, but pts who develop PD while on treatment w/ cBTKi have historically had poor responses to subsequent lines of therapy (LOT). Brexucel, lisocel, and the non-covalent BTKi pirto have been approved in this population. While two RW studies have substantiated the benefit of brexucel, similar data for pirto are lacking. Accordingly, we aimed to evaluate the outcomes of pts treated w/ pirto in the RW setting. Methods: We performed a multi-center retrospective cohort study of adult pts w/ a diagnosis of MCL who experienced PD after any approved cBTKi and subsequently received pirto. Pts who received pirto w/ bridging intent and those who switched to pirto due to intolerance of cBTKi were excluded. The 95% exact binomial confidence intervals (CI) were calculated for overall response rate (ORR) and complete response rate (CRR). Progression-free survival (PFS) and overall survival (OS) were defined as the time from pirto start to PD or death, whichever occurred first, and the time from pirto start to death, respectively, and calculated w/ the Kaplan-Meier method. The log-rank test was used to compare survival curves. A multivariate (MV) Cox proportional hazard model was built to calculate adjusted hazard ratio (aHR). Analyses were performed w/ SAS, version 9.4. Results: Data on 111 pts w/ MCL treated across 21 institutions were collected. Median (mdn) age was 72 (range 33 – 93) years. Twenty-seven pts (24%) were female, 3 (3%) were Asian, 5 (5%) Black, 9 (8%) Hispanic, 86 (77%) White. Among the 53 (48%) pts w/ available MIPI-c at diagnosis, 28 (53%) pts were high-risk. Ki67 at diagnosis was available in 84 (76%) pts: of those, 58 (69%) had a Ki67 ≥30%, and 41 (49%) ≥50%. TP53 mutational status was available in 70 (63%) pts: 33 (47%) had documented TP53 mutation and 10/52 (19%) pts had a disease w/ complex karyotype. Pts had a mdn of 3 (range 1 – 9) prior LOT (n=106). Ninety-one pts (86%) received chemo-immunotherapy (CIT), 16 (15%) autologous stem cell transplant, 19 (18%) venetoclax (ven), 29 (27%) chimeric antigen receptor T-cell, 4 (4%) allogeneic stem cell transplant. For cBTKi, 39 (35%) pts received ibrutinib, 56 (50%) pts acalabrutinib, 33 (30%) pts zanubrutinib, and 17 (15%) pts received more than one cBTKi. The mdn time from the last dose of cBTKi to pirto start was 55 (range 0 – 2587) days, w/ 51 (46%) pts who switched from a cBTKi directly to pirto. Thirty (27%) pts had no response (stable disease or PD as best response) to cBTKi, and 40 (36%) pts had no response to the last LOT. Two (2%) pts received pirto in combination w/ CIT, 8 (7%) w/ an anti-CD20 monoclonal antibody (mAb), 11 (10%) w/ ven ± a mAb, while 86 (77%) pts as single agent. In 104 (94%) pts, pirto was given at full dose, 10 (9%) pts had a subsequent dose reduction. A total of 35 serious (grade ≥3) adverse events (AE) were documented in 27 (24%) pts: 4 (4%) pts had a serious bleeding AE, 5 (5%) pts a serious cardiac AE, 10 (9%) a serious GI AE, and 16 (14%) a serious infectious AE. Ninety-eight (88%) pts were evaluable for response. The ORR was 40% (95% CI 30% – 50%) w/ a CRR of 29% (95% CI 20%– 39%). At the last follow-up, 29 (26%) pts remained on pirto w/ a mdn treatment duration of 15.1 months (range 0.4 – 26). Fifty-eight (52%) pts died, 35 (78%) because of PD. At a mdn follow-up of 15.8 (range 0.4 – 26) months among survivors, the mdn PFS was 4.7 months (95% CI 3.3 – 8.2) and the mdn OS was 13 months (95% CI 9.2 – not available). Using the log-rank test, age (quartile groups), number of LOT (1-2 vs. 3-4 vs. 5+), time from cBTKi to pirto (quartile groups), Ki67≥30%, and high MIPI-C did not result in a statistically significant difference in PFS (p>0.05). Presence of TP53 mutation was associated w/ a non-statistically significant adverse trend in PFS (p=0.0585). No response to cBTKi and Ki67≥50% were associated w/ a statistically significant inferior PFS in log-rank test (p=<0.05), which persisted in a MV Cox regression model (aHR 2.4, 95% CI 1.4-4.2, and aHR 2.6, 95% CI 1.6-4.4, respectively). Conclusions: This is the first RW report on pirto in MCL pts. In this high-risk population, ORR to pirto was comparable to the BRUIN trial, while PFS was significantly worse, especially in pts w/ no response to cBTKi and w/ a high Ki67. However, prolonged remissions were seen in a subset of pts, suggesting that a better characterization of this population w/ durable benefit from pirto is needed.

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

Abstract Glioblastoma, IDH-wildtype (GBM), and primary central nervous system lymphoma (PCNSL) are two aggressive brain tumors with distinct treatment strategies but overlapping imaging features on MRI. Accurate preoperative differentiation remains a clinical challenge, due to their overlapping imaging features, even when advanced MRI techniques are employed. This study explored deep learning approaches leveraging multi-sequence MRI to distinguish GBM from PCNSL. Models were developed utilizing 146 PCNSL cases, which were matched to146 GBM by age, sex and year of diagnosis. A 3D-DenseNet121 convolutional neural network was trained using two analytical strategies: (i) loss-based model selection and (ii) ensemble prediction using five-fold cross-validation. Model performance was evaluated on an independent validation set of 256 GBM and 37 PCNSL from the same institution as well as 36 PCNSL cases from an external institution. All MRIs were preprocessed using the FeTS pipeline. Using the independent validation cohort, area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CI) were computed overall and stratified by demographic characteristics. Using both T1 post-contrast (T1Gd) and T2-weighted images, the loss-based model achieved AUC=0.83 (95% CI: 0.77-0.88) and the ensemble model yielded an AUC=0.82 (95% CI: 0.76-0.89). Model performance was similar across males and females; however, model performance was better for subjects older than 50 years of age versus younger than 50. When using only T1Gd images, the loss-based model dropped to AUC=0.55 (95% CI: 0.48-0.63), whereas the ensemble model had AUC=0.79 (95% CI: 0.72-0.85). Models trained with only T2 images achieved AUCs of 0.67 (95% CI: 0.60-0.73) (loss-based) and 0.75 (95% CI: 0.69-0.82) (ensemble). These results highlight the added value of the multi-sequence input. Our results confirm the feasibility of using automated deep learning models to differentiate GBM from PCNSL. Notably, the model generalized well to external MRI data, emphasizing its potential utility as a diagnostic aid in real-world clinical workflows.

ABSTRACT Anaplastic lymphoma kinase‐positive large B‐cell lymphoma (ALK+ LBCL) is a rare, aggressive subtype of diffuse large B‐cell lymphoma with poor outcomes using standard chemotherapy. In this multi‐institutional retrospective study, we analyzed 39 cases of ALK+ LBCL identified at six US academic centers from 2002 to 2024, with treatment including conventional cytotoxic regimens in frontline and biologically informed and nonchemotherapy‐based strategies in the relapsed setting. Ninety‐two percent of patients received frontline anthracycline‐based chemotherapy; 43% received intensified regimens, and 15% underwent upfront autologous stem cell transplantation (ASCT). Despite these approaches, outcomes remained poor. At a median follow‐up of 5.4 years, median event‐free survival (EFS) was 0.6 years (95% CI, 0.4–0.9), and median overall survival (OS) was 1.5 years (95% CI, 1.3–NR). One‐ and five‐year EFS rates were 28% and 17%, while corresponding OS rates were 72% and 42%, respectively. Advanced stage and high IPI scores were associated with inferior outcomes. Twelve patients received ALK inhibitors, with alectinib showing more durable responses than crizotinib. Lenalidomide and immune checkpoint inhibitors also demonstrated activity, including durable complete responses. Five patients underwent allogeneic stem cell transplantation, with three achieving sustained remission. In conclusion, our findings highlight the limited benefit of chemotherapy, even when intensified or followed by ASCT, and support the integration of biologically targeted therapies, which may have contributed to improved OS in our cohort compared to historical outcomes. Prospective, collaborative studies are needed to better understand disease biology and define optimal use of modern therapies in this rare lymphoma.

Abstract The cumulative impact of baseline comorbidities on outcomes of chimeric antigen receptor T-cell (CAR-T) therapy is not well established. Therefore, we developed and validated a Cellular Therapy Comorbidity Index (CT-CI) to predict outcomes following CD19-directed CAR-T therapy for large B-cell lymphoma (LBCL). Patients aged 18 or older receiving commercial CAR-T therapy for LBCL during 2017 to 2020 were selected from the Center for International Blood and Marrow Transplant Research registry. Patients were randomly assigned to training or validation cohorts. Comorbidities given weighted scores comprised the CT-CI, which was then validated for overall survival (OS) prognostication. A total of 1916 patients from 97 medical centers were included, with a median age of 64 years (19-91 years). About 70% of patients had comorbidities, such as cardiac disease (12%); diabetes (14%); hepatic dysfunction (mild, 8%; moderate to severe, 2%); psychiatric disturbance (18%); and pulmonary dysfunction (moderate, 15%; severe, 12%). The CT-CI was calculated, stratified patients in 3 categories, and was associated with increased mortality. Patients with higher CT-CI scores had worse OS (CT-CI 1: hazard ratio [HR], 1.37 [95% confidence interval [CI], 1.16-1.62; P< .001]; CT-CI 2: HR, 1.49 [95% CI, 1.17-1.89; P = .001]; CT-CI ≥ 3: HR, 2.55 [95% CI, 1.90-3.42; P< .001]). Higher CT-CI scores predicted treatment-related mortality and relapse. There was no correlation between the CT-CI score and CAR-T–related toxicities. The novel CT-CI score stratifies the effect of patient comorbidities on survival after CAR-T therapy and can be used for clinical decision-making and treatment selection in high-risk populations. However, comorbidities and fear of increased toxicity should not preclude patients from this effective therapy.