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The International Academy for Clinical Hematology (IACH) is a global, non-profit educational organization dedicated to advancing excellence, equity, and innovation in clinical hematology. Since its creation, the IACH has built an international community spanning more than 130 countries, leveraging digital-first education, scientific collaboration, and professional networking to improve patient care worldwide. This document presents the IACH Strategic Vision for 2026–2030, outlining a structured roadmap for the Academy’s next phase of growth and international leadership. The strategy is built upon six interdependent pillars: scientific excellence and credibility; digital leadership and intelligent learning; academic alliances and global footprint; innovation, visibility, and advocacy; transparency and sustainability; and brand positioning with global impact. By reinforcing scientific rigor, embracing digital transformation, and promoting innovation, the IACH aims to become the most trusted global reference for clinical hematology education and collaboration. This strategic vision positions the IACH as a unifying platform to unite the world hematology community under one banner of knowledge, collaboration, and compassion, for the benefit of every patient, everywhere.

Myeloid sarcoma (MS) is a tumor mass involving any extramedullary site composed of myeloid-lineage blasts with myeloid, myelomonocytic, or monocytic differentiation. Distinguishing MS from malignant histiocytic neoplasms (MHNs) is diagnostically challenging due to morphologic and immunophenotypic overlap, particularly for MS with monocytic differentiation, which can mimic MHNs, especially the subtypes of histiocytic sarcoma and interdigitating dendritic cell sarcoma, leading to potential misdiagnosis and inappropriate management. Cyclin D1 overexpression is implicated in MHNs, but its utility in differentiating these entities has not been systematically characterized. We evaluated cyclin D1 immunostaining in 43 MS cases and 30 MHNs. The median age at MS diagnosis was 59 years (range: 0.1 to 90), while the median age at MHN diagnosis was 62 years (range: 9 to 90), with heterogeneous sites of involvement. Cyclin D1 evaluation showed 100% MHNs with strong cyclin D1 positivity in ≥50% tumor cells, compared with 7% MS with weak-to-intermediate positivity in a minor subset of tumor cells. Additional immunohistochemical evaluation showed no difference in PU.1 expression in MHNs (93%) versus MS (84%) but demonstrated a higher proportion of OCT2-positivity in MHNs over MS (52% vs. 23%, P <0.05). Our study demonstrates a high sensitivity (100%) and specificity (93%) in utilizing cyclin D1 to distinguish MHNs (mature phenotype) from MS (immature phenotype) in diagnostic practice. It is particularly valuable in challenging scenarios of MS with the absence of immature/myeloid lineage-defining markers (MPO, CD34, or CD117) and provides a cost-effective tool to resolve this diagnostic pitfall, ensuring an accurate subclassification.

Abstract Aims This study aimed to identify clinical factors associated with AVC in individuals with T2D. Methods and results This cross-sectional study is a pre-specified substudy of the multicentre randomized Steno INTEN-CT trial (Clinical Trials—INTEN-CT). Participants were eligible if they had T2D without ischaemic heart disease and were aged between 55–69 years (men) or 60–74 years (women). All participants underwent non-contrast cardiac computed tomography. AVC was measured in Agatston Units and categorized as 0, 0–300, ≥ 300. Of the 4570 participants, 46% had AVC &gt; 0. With increasing AVC, patients were older, predominantly males, and with significantly more comorbidities. In multivariable ordered logistic regression age (OR per SD 1.54, 95% CI 1.43–1.66), BMI (OR per SD 1.18, 95% CI 1.11–1.25), hypertension (OR 1.21, 95% CI 1.05–1.40), and chronic kidney disease (OR 1.18, 95% CI 1.03–1.36) were associated with higher AVC. Statin use was also associated with higher AVC (OR 1.50, 95% CI 1.27–1.78). Higher LDL cholesterol showed stronger associations with AVC in men than women (OR 1.39, 95% CI 1.24–1.56 vs. OR 1.16, 95% CI 1.02–1.31, P for interaction = 0.025). T2D severity (Haemoglobin A1c, T2D duration, and number of antidiabetic drugs) was not associated with AVC. Conclusion In individuals with T2D without cardiovascular disease, AVC is prevalent in nearly half of all individuals. Higher AVC was associated with T2D-related comorbidities, but not T2D severity.

ABSTRACT Objective This study assessed the impact of sex and age on weight loss outcomes in patients receiving tirzepatide in real‐world clinical practice. Methods We conducted a retrospective cohort study of adults with overweight or obesity who initiated tirzepatide at Mayo Clinic between June 2022 and May 2024 and completed ≥ 12 months of continuous therapy. Primary outcome was total body weight loss percentage (TBWL%) at 15 months, stratified by sex and age groups (≤ 45, 46–59, ≥ 60 years). Results Among 1039 patients (57% women; mean age 56 ± 11 years), women achieved significantly greater TBWL% than men after 15 months of treatment (15.1% vs. 10.7%, p < 0.001). Patients aged ≤ 45 years had greater weight loss than those ≥ 60 years (15.1% vs. 12.3%, p = 0.024). In multivariable analyses, greater weight loss was independently associated with female sex, absence of type 2 diabetes, no prior obesity medication use, no concomitant weight gain‐promoting medications, and higher tirzepatide dosage. Age was not an independent predictor. Conclusions Sex, but not age, predicted weight loss with tirzepatide among individuals using the medication continuously for ≥ 12 months. These findings underscore the importance of incorporating sex‐specific considerations into personalized obesity treatment strategies.

Introduction To assess and compare the accuracy, readability, and overall performance of large language models (LLMs) in answering questions about functional hypothalamic amenorrhea (FHA) for patients and healthcare professionals. Methods A total of 11 patient-level and 15 clinician-level FHA-related questions were entered separately into four LLMs: ChatGPT 3.5 (free version), ChatGPT 4.0 (updated, paid subscription), Gemini, and OpenEvidence. OpenEvidence was used only for clinician-based questions. Responses were evaluated by three expert reviewers blinded to the LLM used who rated them as accurate and complete, accurate but incomplete, or inaccurate. A fourth reviewer resolved discordant scores. Readability for patient-level questions was assessed using the Flesch Reading Ease Score (FRES) and word count. Lower FRES scores indicate more difficult reading. Accuracy and completeness were compared using odds ratios (95% CI) with ChatGPT 3.5 as the reference model, and differences in readability were analyzed using Friedman’s test. Results LLM performance varied across question types. For patient-level questions, ChatGPT 4.0 achieved the highest accuracy (9 of 11; 82%), followed by ChatGPT 3.5 and Gemini (each 8 of 11; 73%), with no statistically significant differences. Among clinician-level questions, OpenEvidence demonstrated perfect accuracy (15 of 15; 100%), compared with 93% for and 80% for ChatGPT 4.0 and Gemini. Completeness followed similar patterns, with OpenEvidence providing the most complete clinician responses (93%) and ChatGPT 4.0 the most complete patient-level responses (89%). Readability differed significantly among models ( p = 0.012), with Gemini producing the most readable patient-level content (median FRES 43.5 [IQR 36.8–53.4]) compared with ChatGPT 3.5 (30.6 [16.8–48.4]) and ChatGPT 4.0 (28.8 [22.1–37.6]). Word counts did not differ significantly ( p = 0.39). Discussion LLMs demonstrated good overall performance in answering FHA-related questions but often provided incorrect or incomplete information. Fine tuning field-specific data, engineered prompts, and obtaining human-in-the-loop feedback may help improve the accuracy of these models.

Objective To evaluate the effects of mepolizumab therapy on the blood transcriptome in patients with severe eosinophilic asthma (SEA) and to determine whether changes in gene expression predict responsiveness to mepolizumab treatment. Methods Fourteen consecutive patients diagnosed with SEA were prospectively enrolled. Each patient had sequential blood samples obtained pre-initiation and at 4, 8, and 12 weeks post-initiation of mepolizumab. Peripheral blood mononuclear cells (PBMCs) were isolated from blood samples for bulk RNA sequencing. Paired differential expression (DE) gene analysis was performed comparing baseline gene expression versus all timepoints. Changes in gene expression were also compared between responders versus nonresponders to mepolizumab treatment. Finally, gene set enrichment analysis was evaluated across timepoints and its interaction with the response to mepolizumab treatment. Results Principal component analysis of all genes demonstrated a homogeneous distribution, which did not separate into distinct groups based on either timepoint or therapeutic response. At week 12, 149 genes had significant DE (FDR &lt; 0.05) compared to baseline. When performing all-way timepoint comparisons, 74 genes (63 protein-coding) were found to be downregulated at weeks 4, 8 and 12 compared to baseline, but no differences were observed between post baseline timepoints. Twenty-eight genes (16 protein-coding) did change with progression of time and were associated with response to therapy, and 56 protein-coding genes distinguished responders and nonresponders. At week 12, nonresponders had a high enrichment of genes involved with signaling pathways, including cytokines, growth factors, cell differentiation markers, and protein kinases. Conclusion In this exploratory study, mepolizumab use was associated with limited global transcriptomic separation with some preliminary differential-expression and enrichment findings. No definitive mechanistic or predictive response signatures were identified due to the study limitations. Future studies, including larger cohorts followed for longer durations with interrogation of specific immune subsets, may offer additional insight into the pathophysiology of severe eosinophilic asthma and into predicting response to mepolizumab treatment.