Bernstein, Jonathan A.

Abstract Background: Systemic mastocytosis (SM) comprises a spectrum of subtypes characterized by neoplastic mast cell (MC) infiltration of tissues and release of MC mediators. Non-advanced SM (NonAdvSM), including indolent SM (ISM), smoldering SM (SSM), and bone marrow mastocytosis (BMM) subtypes, is the most prevalent form of SM. NonAdvSM can be associated with debilitating symptomology which can significantly impair quality of life. The gain-of-function somatic KIT c.2447 C>T (p.D816V) mutation is found in up to 95% of patients with SM. Bezuclastinib (CGT9486) is an oral, potent, and selective type 1 tyrosine kinase inhibitor with activity against KIT D816V. Results from Summit (NCT05186753) Part 1 informed the recommended phase 2 dose (100 mg QD bezuclastinib) for Part 2. We report topline results from the 24-week assessment of Summit Part 2. Methods: Summit is a multi-center, randomized, double-blind, placebo (PBO)-controlled Phase 2 trial of bezuclastinib in patients with NonAdvSM who had inadequate symptom control despite best supportive care (BSC) medications. The primary endpoint was 24-week mean change from baseline in Mastocytosis Symptom Severity Daily Diary (MS2D2) total symptom score (TSS) (range 0–110), which is a fit-for-purpose patient-reported outcome measure of NonAdvSM symptom severity. Key secondary endpoints included the proportion of patients with ≥50% reduction in serum tryptase, KIT p.D816V variant allele frequency (VAF), bone marrow (BM) MC burden, and MS2D2 TSS, ≥30% TSS reduction. Patients were randomized 2:1 to receive 100mg QD bezuclastinib + BSC or PBO + BSC. Results: As of May 22, 2025, 179 patients were enrolled in Part 2: 119 were randomized to receive bezuclastinib and 60 to placebo. Patients enrolled were representative of the NonAdvSM population with moderate to severe symptoms. Median age (range) was 51 (23-78) years; 65.9% female; mean (SD) baseline MS2D2 TSS 55.6 (19.8); 82% of patients had ISM, 11% had BMM, and 7% had smoldering SSM. At baseline, median (range) KIT p.D816V VAF in whole blood, BM MC burden, and serum tryptase was 0.25% (0-34%), 10% (1-75%), and 40 (6-692) ng/mL, respectively. Bezuclastinib demonstrated statistically significant superiority to placebo on all primary and key secondary endpoints. At Week 24, bezuclastinib led to significantly greater symptom improvement vs placebo (LS mean [95% CI] MS2D2 TSS change: –24.3 [–27.6 to –21.1] vs –15.4 [–19.6 to –11.2]; placebo-adjusted difference: –8.9 points; P=0.0002). A ≥50% reduction in serum tryptase was achieved in 87.4% of bezuclastinib-treated patients vs 0% on placebo (P<0.0001). Significantly more patients receiving bezuclastinib achieved ≥50% reductions in KIT D816V VAF, serum tryptase, BM MCs (P<0.0001), MS2D2 TSS (P=0.01), and ≥30% reduction in MS2D2 TSS (P=0.0004). Most treatment-emergent adverse events (TEAEs) were low grade (gr; 70% Gr 1) and reversible. The most common TEAEs (≥10%) in any treatment group and occurring in greater frequency in the bezuclastinib arm were hair color changes (69.5% vs 5.0%), altered taste (23.7% vs 0%), nausea (22.0% vs 13.3%), increased ALT/AST (22.0% vs 6.6%), headache (17.8% vs 11.7%), alopecia (11.9% vs 3.3%), and increased ALP (10.2% vs 3.3%). TEAEs (≥10%) that occurred more often in the placebo group were diarrhea (13% vs 18%), dizziness (10% vs 12%), fatigue (7% vs 12%), and arthralgia (6% vs 15%). ALT/AST elevations ≥Gr 3 were experienced by 5.9% of patients. The only hepatic adverse events (AEs) reported were transient lab abnormalities; none required hospitalization. Treatment-related AEs requiring dose reductions occurred in 11% of patients receiving bezuclastinib. All discontinuations (5.9%) due to treatment-related AEs were due to transaminase elevations; all fully resolved. Conclusions: At 24-weeks, bezuclastinib 100 mg QD demonstrated statistically and clinically significant improvements in symptom burden and biomarkers of disease vs placebo in patients with NonAdvSM. The treatment was generally well-tolerated and effective across a population that is representative of the real-world NonAdvSM population, including SSM. These results support the use of bezuclastinib to reduce SM burden and symptoms in pts with NonAdvSM, and a potentially disease-modifying impact.

Abstract Background In the 5 years that have passed since the publication of the 2018 International Consensus Statement on Allergy and Rhinology: Allergic Rhinitis (ICAR‐Allergic Rhinitis 2018), the literature has expanded substantially. The ICAR‐Allergic Rhinitis 2023 update presents 144 individual topics on allergic rhinitis (AR), expanded by over 40 topics from the 2018 document. Originally presented topics from 2018 have also been reviewed and updated. The executive summary highlights key evidence‐based findings and recommendation from the full document. Methods ICAR‐Allergic Rhinitis 2023 employed established evidence‐based review with recommendation (EBRR) methodology to individually evaluate each topic. Stepwise iterative peer review and consensus was performed for each topic. The final document was then collated and includes the results of this work. Results ICAR‐Allergic Rhinitis 2023 includes 10 major content areas and 144 individual topics related to AR. For a substantial proportion of topics included, an aggregate grade of evidence is presented, which is determined by collating the levels of evidence for each available study identified in the literature. For topics in which a diagnostic or therapeutic intervention is considered, a recommendation summary is presented, which considers the aggregate grade of evidence, benefit, harm, and cost. Conclusion The ICAR‐Allergic Rhinitis 2023 update provides a comprehensive evaluation of AR and the currently available evidence. It is this evidence that contributes to our current knowledge base and recommendations for patient evaluation and treatment.

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.