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Abstract Introduction: THRLBCL is a rare disease accounting for less than 10% of all diffuse large B-cell lymphoma (DLBCL) subtypes. THRLBCL was associated with poor outcomes in the pre-rituximab era, with limited contemporaneous data. Optimal frontline treatment remains unclear with some studies advocating for intensive regimens. The goal of this international study is to analyze the survival and treatment-related outcomes in patients with newly diagnosed THRLBCL treated with rituximab-containing chemotherapy and to compare with a DLBCL, not otherwise specified (NOS) cohort. Methods: THRLBCL and DLBCL patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) (NCT02736357) (7/2015 to 5/2020), Molecular Epidemiology Resource (1/2010 to 6/2015), and Czech Lymphoma Study Group project (NiHiL) (NCT03199066) (2/2010 to 11/2023) were analyzed. Diagnosis was made in dedicated hematopathology centers in both registries. We excluded patients with prior nodular lymphocyte-predominant Hodgkin lymphoma, central nervous system involvement, and not treated with rituximab-containing therapy. Event-free survival (EFS) and overall survival (OS) were estimated by Kaplan-Meier.Univariate associations were derived via Cox model and multivariate models were constructed by forward selection of significant variables with P≤0.05. Propensity score matching (1:5, caliper 0.2) between THRLBCL and DLBCL NOS patients was performed using IPI score components and treatment as covariates. Results: We identified 158 patients (LEO: 67 and NiHiL: 91) with THRLBCL. Among them, 140 patients received rituximab-containing regimens and were included in this analysis. Median age was 58 years (range, 19-89) with 57% aged ≤60 years. Most patients were male (n= 88; 63%) and had ECOG performance status (PS) of 0-1 (n= 111; 79%), stage III-IV (n= 111; 79%), elevated LDH (n= 92; 66%), and B symptoms (n= 84; 60%). Fifty (36%) patients had ≥2 extranodal (EN) sites, mostly liver (n= 39; 28%) and lung (n= 16; 11%), bone marrow (BM) involvement was observed in 26% (n= 37). Bulky disease (≥7.5cm) was present in 50 (36%) and IPI score ≥3 in 68 (48%) patients. The median diagnosis-to-treatment interval was 23 days (IQ range, 13-38.5). Frequent regimens were R-CHOP (n= 106; 75.7%), followed by intensive regimens such as R-MegaCHOP/ESHAP, R-HyperCVAD/MA, and R-CODOX-M/IVAC (n= 15; 10.7%), and R-CHOEP/EPOCH-R (n= 10; 7.14%). With a median follow-up of 3.92 years, the 4-year EFS & OS were 71% and 80%, respectively. Lymphoma was the main cause of death (n= 15; 11%) among 30 events. No difference in 4-year EFS (70% vs. 76%; P= 0.55) & OS (80% vs 82%; P= 0.96) were observed between R-CHOP and intensive regimens. Factors associated with shorter EFS and OS in univariate analysis for THRLBCL were ECOG PS 2-4: (HR= 3.3; P<.001 & HR= 5.97, P<.001, respectively); ≥2 EN sites (HR= 1.85, P= 0.043 & HR= 2.54, P= 0.014, respectively); B symptoms (HR= 2.35, P= 0.014 & HR= 2.84, P= 0.023) and IPI score (HR= 1.5, P= 0.002 & HR= 2.16, P<.001). Stage III-IV and BM involvement were associated with shorter OS only (HR= 7.36, P= 0.05 & HR= 2.18, P= 0.036, respectively). Among them, only ECOG PS 2-4 (OS: HR= 3.6, P= 0.003) and B symptoms (EFS: HR= 2.3, P= 0.046) were independent predictors of survival in multivariate analysis. Finally, we compared baseline characteristics and survival between THRLBCL (n= 140) and DLBCL NOS (n= 6099; LEO/MER: 2069 & NiHiL: 4030) treated with rituximab-containing regimens. Patients with THRLBCL were younger (≤60 years: 57% vs. 38%; P<.001), more frequently had ECOG PS 0-1 (79% vs 76%; P= 0.012), stage III-IV (79% vs 63%; P<.001), B symptoms (60% vs 38%; P<.001), and liver involvement (28% vs 7%; P<.001), compared to DLBCL NOS. Subtype was not associated with survival (OS HR= 0.79, P= 0.262 & EFS HR= 0.93, P= 0.662) when adjusted for IPI score. With a median follow-up of 4.89 years in the DLBCL NOS cohort, we observed similar 4-year EFS (71% vs 67%; P= 0.197) & OS between histologies (80% vs 77%; P= 0.125). These results were confirmed in propensity matching for EFS (HR= 0.98, P= 0.897) and OS (HR= 1.07, P= 0.732). Conclusions: In this large international analysis of patients with newly diagnosed THRLBCL contemporaneously treated, we observed similar survival rates compared to DLBCL NOS treated with R-CHOP and intensive regimens. ECOG PS and the presence of B symptoms were independent factors associated with survival.

Abstract Introduction: Despite advent of multiple tyrosine kinase inhibitors (TKIs) and newer treatment methods for AML and ALL, the outcomes of patients (pts) with chronic myeloid leukemia in blast phase (CML-BP) remain poor. Consensus guidelines on treatment of CML-BP are scarce. A recent study from the European leukemia network blast phase registry on 240 pts reported marked heterogeneity in treatment patterns and lack of an accepted standard. Hence, we undertook this study through the H Jean Khoury Cure CML Consortium (HJKC3) to describe the treatment patterns and outcomes of pts with CML-BP in the US. Methods: This is a multi-institution, retrospective study. IRB approval was obtained at each institution and data sharing agreements were executed. All pts diagnosed with CML-BP based on modified MD Anderson Criteria (≥30% blasts in the blood or bone marrow or extramedullary (EM) disease) from 2010 to 2025 were included. Categorical variables were compared using Chi-square test. Overall survival (OS) was calculated from time of diagnosis of CML BP to death from any cause. Event free survival (EFS) was calculated from date of best response to event (death or relapse). Results: Of the 283 pts with CML-BP, 96 (33.9%) were female and 187 (66.1%) were males. At the time of diagnosis, 183 (64.6%) had CML-CP, 21 (7.4%) pts had CML-AP and 79 (27.9%) pts had de-novo CML-BP. For the 204 pts that were initially diagnosed with CML-CP or CML-AP, the median time to progression to CML-BP was 22.5 months (1-207 months). Median age at diagnosis of CML-BP was 50 years (range 16-86 years). EM disease was present in 78 (27.6%) pts (38 myeloid sarcoma, 30 central nervous system and 10 skin). Blasts were of myeloid phenotype in 168 (59.4%), lymphoid in 103 (36.4%) and mixed in 9 (3.2%) pts. The bcr-abl protein was p210 in 229 (80.9%), p190 in 8 (2.8%) and p230 in 2 (0.7%) pts. ABL kinase domain mutation was seen in 42.1% (80/190) pts, with T315I being the most common (n=32), followed by E255K (n=16). Next generation sequencing was performed in 117 pts. The most common mutations were ASXL1 (n=27), RUNX1 (n=14), BCOR (n=4), DNMT3A (n=4) and BCORL1 (n=3). Of the 283 pts, 269 underwent CML-BP directed therapy. 63 (23.4%) pts were treated with TKI monotherapy, 184 (68.4%) pts were treated with a combination of chemotherapy (chemo) and TKI and 22 (8.2%) pts were treated with chemo alone. Response rate after CML-BP directed therapy was 75.3% (n=213). Best response was return to CML-CP in 49 pts, CHR with PCyR in 18 pts, CCyR in 31 pts, MMR in 31 pts, MR4 in 18 pts, MR4.5 in 19 pts and MR5 in 47 pts. Rate of response with 2G and ponatinib was significantly better than imatinib (85.3% and 77.3% vs 63.6%; p=0.04). 149 (55.4%) pts proceeded to alloSCT. Of the 213 pts that responded, 59 (27.7%) relapsed. At a median follow-up of 47 months, the median OS for all pts was 19.7 months (95% CI: 16.3-40.2 months), with 5-year OS rate of 38% (95% CI: 32-45%). Pts with myeloid phenotype had a significantly lower OS compared to lymphoid and mixed phenotype (Median OS 14.9 vs 45.9 and 31.1 months respectively; p=0.02). OS of pts that were treated with a combination of TKI and chemo was significantly longer compared to pts treated with TKI or chemo alone (52.9 vs 16.1 or 7.5 months; p<0.0001). Dasatinib (n=99; 34.9%) and ponatinib (n=97; 34.3%) were the most used TKIs followed by imatinib (n=23; 8.1%), nilotinib (n=21; 7.4%), bosutinib (n=8; 2.8%) and asciminib (n=3; 1.1%). Pts treated with ponatinib had a numerically longer OS compared to 2G-TKI and imatinib, however this was not statistically significant (40.1 vs 30.6 and 20.3 months; p=0.52). EFS for pts treated with ponatinib was significantly longer compared to 2G-TKI or imatinib (25.9 vs 17.6 and 15.9 months; p=0.03). In a landmark analysis, pts that underwent alloSCT within 6 months of diagnosis had a significantly longer OS compared to those who did not (69.3 vs 16.0 months; p=0.006). Conclusion: CML-BP continues to have poor prognosis. Treatment is heterogenous involving various combinations of TKI and chemo. In our analysis, treatment with 2G-TKI or ponatinib led to better responses. CML-BP with myeloid phenotype had worse OS. Treatment with ponatinib was associated with a numerically longer OS and significantly longer EFS compared to 2G-TKI and imatinib. In addition, treatment with chemo in combination with TKI and alloSCT led to improved OS.

Abstract Introduction In 2018, our institution implemented a MALDI-TOF mass spectrometry (MS) method (Mass-Fix) to detect myeloma associated M-proteins in blood. Currently, the lab has performed more than 500K tests by Mass-Fix. While Mass-Fix has been found to be more sensitive and specific than IFE, an ESI-Q-TOF (High Resolution Mass-Fix) method has demonstrated the potential to detect M-proteins at significantly lower levels. Blood minimal residual disease (MRD) detection in lieu of bone marrow (BM) is desirable since blood is easier and less expensive to obtain and analyze. This feature can allow for more frequent MRD monitoring for myeloma patients. Methods 66 residual blood samples from myeloma patients with varying M-protein varying isotypes were diluted into healthy blood to estimate the limit of detection of HR-Mass-Fix method. 179 Rochester Mayo Clinic patients who had a clinically ordered BM MRD assessment by next generation flow (NGF) cytometry (2 x 10-6), a blood sample available within 7 days of the BM biopsy, and a pre-treatment measured M-protein mass by Mass-Fix were utilized to assess the concordance of the BM and blood MRD status. Results The average limit of detection (LOD) of the HR-Mass-Fix was found to be significantly lower than Mass-Fix (0.0003 g/dL and 0.01 g/dL, respectively). The treated patient cohort utilized for comparison consisted of 145 myeloma, 21 AL amyloid, 4 LPL lymphoma and 9 other PCDs. Comparing the Mass-Fix and HR-Mass-Fix results, 100% of blood positive MRD results by Mass-Fix were positive by HR-Mass-Fix. HR-Mass-Fix detected residual M-proteins (mass within +/- 1 Da of pre-treatment) in 29 samples (40%) that were negative by Mass-Fix. Thus, HR-Mass-Fix increased the overall blood MRD positivity rate from 57% by Mass-Fix to 78%. The BM NGF MRD positivity was lower at 54%. The overall agreement of blood and BM by Mass-Fix was 71% (kappa 0.4) which decreased to 0.63 (kappa 0.3) with HR-Mass-Fix. Most of the disagreements were HR-Mass-Fix Blood (+)/BM NGF (-). Blood M-protein MRD appeared to be affected by M-protein half-lives. To determine this, the M-protein isotype distribution of Blood/BM MRD status was compared the M-protein isotype distribution of the overall cohort. The half-lives are as follows: IgG 23 days, IgA 6 days, IgM 5 days and FLC 0.25 days. When both blood and BM were positive, the isotype distribution was not significantly different than the overall cohort. For blood(+)/BM(-) patients, IgG (with the longest half-life) were significantly overrepresented compared to the overall cohort (74% vs 51%) . For blood(-)/BM(+) cases, there were no IgG M-proteins, and the majority were FLC patients. These results suggest that patients with shorter half-life M-proteins (non-IgG) are more likely to be Blood MRD(-) than patients with longer half-life M-proteins. M-protein rate changes over time will likely be needed to resolve the M-protein half- life affect. Conclusions HR-Mass-Fix can significantly increase the detection of M-proteins in comparison to our current Mass-Fix method. Ig recycling was found to be a likely reason for the disagreement between BM and blood. Therefore, a negative blood MRD status by HR-Mass-Fix is most likely to be the most significant in predicting patient outcomes.

Abstract Introduction Marginal zone lymphoma (MZL) is an indolent and heterogenous disease. Several prognostic models have been proposed to assess outcomes in MZL, including FLIPI, IPI (primarily designed for overall survival [OS]), and MZL-specific scores such as MALT-IPI (event-free survival [EFS]) and MZL-IPI (progression-free survival). FLIPI24 is a recently developed prognostic index for patients with follicular lymphoma (FL) treated with first-line (1L) immunochemotherapy (IC), identifying a high-risk population with inferior survival and increased risk of lymphoma-related death. FLIPI24 has also demonstrated robust performance in the entire FL population, including patients under observation. This study aimed to evaluate the prognostic utility of FLIPI24 in patients with MZL and to compare its performance with other established indices (FLIPI, MZL-IPI, IPI, MALT-IPI). Methods We pooled harmonized data from newly diagnosed MZL patients with complete available FLIPI24 variables (age, white blood cell count [WBC], hemoglobin [HGB], serum lactate dehydrogenase [LDH], and beta-2-microglobulin [B2M] levels) treated with 1L IC. Data were collected from three prospective international cohorts: NiHiL (Czech Republic; n=897; enrolled 2005–2023), LEO (USA; n=62; 2015–2020), and MER (USA; n=32; 2010–2015), forming a pooled cohort of 991 1L IC-treated patients. The analysis was then extended to include all newly diagnosed MZL patients (n=2,116), regardless of treatment. The primary endpoint in the 1L IC-treated cohort was EFS at 24 months (EFS24), and for all MZL patients, it was OS. Secondary endpoints included OS24 for 1L IC treated cohort, lymphoma-related mortality by FLIPI24 risk groups, and comparative prognostic performance of FLIPI, IPI, and MALT-IPI, by C-statistics; performance of MZL-IPI was assessed on a subgroup of NiHiL patients with available data (n=877 all MZL, n=485 1L IC-treated). Results Among the 991 1L IC-treated patients, the median age at diagnosis was 66 years (range 22–94); 47% were male; 11% had ECOG performance status ≥2, 68% clinical stage III–IV, 42% elevated LDH, 40% IPI 3–5, 42% FLIPI 3–5, and 62% MALT-IPI 2–3. The median B2M level was 2.8 mg/L, WBC 7.0 × 10⁹/L, and HGB 13.1 g/dL. MZL subtypes were: 64% extranodal (EMZL), 22% nodal (NMZL), and 14% splenic (SMZL). Most common 1L IC regimens were R-CVP (46%), R-CHOP-like (32%), R-chlorambucil (9%), and B-R (9%). FLIPI24 stratified patients into low- (18%), intermediate- (37%), and high-risk (45%) groups. High-risk patients were older (median 54 vs 65 vs 71 years for low-, intermediate-, and high-risk groups, respectively; P<0.01), had more frequent adverse baseline features, and were more likely to have the SMZL subtype (2% vs 7% vs 25% for low-, intermediate-, and high-risk groups, respectively; P<0.01). After a median follow-up of 7.2 years, EFS24 was 89%, 85%, and 65% (P<0.01) across low-, intermediate-, and high-risk groups; OS at 2 years was 98%, 97%, and 79%; and OS at 5 years was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 13% in high-risk vs 6% in low-/intermediate-risk groups. FLIPI24 showed better prognostic accuracy for EFS compared with FLIPI, MZL-IPI, IPI and MALT-IPI (C-index: 0.640 vs 0.630, 0.622, 0.620 and 0.603, resp.), as well as for OS (C-index: 0.710 vs 0.672, 0.641, 0.663, 0.652, resp.). Prognostic performance was consistent across MZL subtypes. In the extended cohort of 2,116 newly diagnosed MZL patients (47% receiving IC, 17% rituximab monotherapy, 11% radiotherapy, 8% surgery, 2% antibiotics; 15% observed), FLIPI24 stratified patients into low- (24%), intermediate- (39%), and high-risk (37%) groups. OS at 2 year was 99%, 97%, and 83%, at 5 years it was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 12% in high-risk vs 4% in low-/intermediate-risk patients. FLIPI24 outperformed other indices (OS C-index: 0.754 vs MZL-IPI 0.654, FLIPI 0.700, MALT-IPI 0.694, IPI 0.699). Conclusion FLIPI24 demonstrates strong and consistent prognostic performance across all MZL subtypes, identifying ~40% of patients as high-risk with significantly worse survival and increased lymphoma-related mortality. The FLIPI24 outperforms FLIPI, MZL-IPI, IPI, and MALT-IPI in predicting outcomes and may serve as a practical tool to guide risk-adapted management and selection of patients for novel therapies in MZL. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

Abstract Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors. Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS). Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%). In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era). Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598). We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568). Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients. Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.

In 2023, the American Congress of Rehabilitation Medicine Brain Injury Interdisciplinary Special Interest Group (ACRM BI-ISIG) Mild Traumatic Brain Injury (TBI) Task Force published updated diagnostic criteria for mild TBI. These criteria were developed in collaboration with a panel of 32 subject matter experts in mild TBI using the Delphi method. The 2023 ACRM diagnostic criteria marked the first update since 1993, incorporating three decades of research advancements in our understanding of mild TBI. To facilitate the consistent use of the new diagnostic criteria, the ACRM BI-ISIG Mild TBI Task Force initiated a special project in September 2023 to develop a structured interview to apply the ACRM diagnostic criteria for mild TBI in clinical and research settings. The purpose of this article is to describe the development of the ACRM Structured TBI Interview and the accompanying documents. The ACRM Structured TBI Interview was developed in four phases: (1) initial development of a draft interview by two project leads, (2) review and revision over three rounds by 17 members of the ACRM BI-ISIG Mild TBI Task Force, (3) external review by 19 subject matter experts in mild TBI, and (4) field testing of the ACRM Structured TBI Interview by 11 interviewers who completed 25 diagnostic interviews. In addition to the ACRM Structured TBI Interview, three other documents were developed to help facilitate the administration of the interview (Administration Guide) and to apply the diagnostic criteria (Diagnostic Coding Form and Diagnostic Flow Diagram). A Short Form was also developed for use in contexts where administering the full structured interview is not feasible due to time constraints.

Abstract Background and Aims Patients with catecholaminergic polymorphic ventricular tachycardia (CPVT) are at risk for potentially life-threatening arrhythmic events (AEs) even while treated with β-blockers. The aim was to develop a model for individualized prediction of AEs in patients with RYR2-mediated CPVT on β-blocker monotherapy. Methods The derivation and independent validation cohorts included 743 and 129 patients, respectively. AEs were defined as arrhythmic syncope, appropriate implantable cardioverter–defibrillator shock, sudden cardiac arrest (SCA), and sudden cardiac death. Near-fatal or fatal AEs (nf/fAEs) included all AEs except for arrhythmic syncope. Prediction models using Cox regression were developed and internally and externally validated. Results A total of 102 (13.7%) patients in the derivation cohort and 24 (18.6%) patients in the validation cohort experienced ≥1 AE over a median follow-up of 5.1 [interquartile range (IQR), 7.7] and 2.4 (IQR, 4.4) years, respectively. Predictors of AE were arrhythmic syncope or SCA prior to diagnosis and age at β-blocker initiation. In the derivation and validation cohorts, the optimism-corrected C-indices of the models for AE were 0.67 [95% confidence interval (CI) 0.62–0.72] and 0.59 (95% CI 0.48–0.71), respectively. For nf/fAEs, ventricular arrhythmia severity before β-blocker initiation was a fourth independent predictor, and C-indices of the models in the derivation and validation cohorts were 0.74 (95% CI 0.68–0.80) and 0.60 (95% CI 0.47–0.72), respectively. In the derivation cohort, calibration slopes were 1.00 (95% CI 0.59–1.41) for AE and 1.00 (95% CI 0.69–1.32) for nf/fAE. Conclusions These externally validated risk prediction models using clinical parameters accurately distinguished CPVT patients on β-blocker monotherapy at low and high risk for future AEs while treated with β-blockers. These models provide guidance for implementation of clinical management therapies to prevent AEs in patients with CPVT.

Abstract Background We examined real-world utilization of treat-to-target (TTT) strategies and conducted a quality improvement (QI) project to improve uptake of TTT strategies in a learning health system, IBD Qorus. Methods We implemented a structured QI intervention to increase uptake of TTT in 41 gastroenterology practices in the United States, over a 13-month intervention period (November 2020 to November 2021; modified breakthrough series [BTS] collaborative), and a 10-month post-BTS observation period (December 2021 to October 2022). Through encounter-level surveys, we examined providers’ “intention to TTT” based on discussion of TTT with patients, documentation of inflammation, and intention to change therapy to TTT. We examined changes in rates of “intention to TTT,” and whether improvement in intention to TTT influenced site-level rates of remission. Results Over 13 months, there were 7932 patient visits (55% with Crohn’s disease; 47% in clinical remission); patients in 2160 visits (27%) were not in endoscopic remission. Overall, rates of intention to TTT increased from 31% to 54% (P = .06) with considerable site-to-site variability and was maintained at 49% in the post-BTS observation period. The increased rate was attributable to higher rates of testing for inflammation. Despite an increase in the rate of intention to TTT, there was no significant change in site-level achievement of remission over the same time. Conclusions Through a QI initiative in a learning health system, rates of intention to TTT increased significantly over 12-months, though overall rates remained low. Assessing patient-, provider- and practice-level barriers and facilitators for successful implementation of a TTT strategy is warranted to improve clinical outcomes.

Objective To assess real‐world effectiveness of switching disease‐modifying therapy (DMT) in pediatric multiple sclerosis (MS) and clinically isolated syndrome (CIS) initially treated with platform injectables on disease activity. Methods Of 2615 pediatric‐onset demyelinating disease patients at 12 clinics in the United States (US) Network of Pediatric MS Centers, those with MS/CIS on initial therapy with a platform injectable who switched to another class of platform injectable, oral or infusion DMT were analyzed. Relapse rate was modeled with negative binomial regression, adjusted for preidentified confounders. Results A total of 212 children switched DMT before age 18 (67% female, 95% MS). Ninety‐three switched from injectable to injectable, 76 injectable to oral, and 43 injectable to infusion. Switchers to oral or infusion were older at onset (injectable 12.3 years, oral 13.5 years, and infusion 14.2 years) and switch (injectable 14.6 years, oral 16.0 years, and infusion 15.7 years). Switchers to infusion DMT were more likely to have enhancing lesions (injectable 45%, oral 28%, and infusion 67%). Compared to injectable (annualized relapse rate [ARR] = 0.88, 95% confidence interval [CI] = 0.52–1.48), relapse rates were lower for injectable to oral (ARR = 0.34, 95% CI = 0.20–0.57; rate ratio: 0.38, 95% CI = 0.21–0.69) and injectable to infusion (ARR = 0.18, 95% CI = 0.09–0.37; rate ratio: 0.21, 95% CI = 0.10–0.44) ( p < 0.001). Adjusted number needed to treat in person‐years to prevent 1 relapse with oral over injectable was 1.84 (95% CI = 1.03–8.69) and infusion over injectable 1.43 (95% CI = 1.00–3.88). Interpretation Switching from platform injectable to oral or infusion compared to other platform injectable DMT led to better disease control in pediatric MS. Long‐term safety data are required. ANN NEUROL 2026;99:715–729