Next-generation sequencing (NGS) has improved diagnostic accuracy for myeloid neoplasms, but its clinical utility in assessing unexplained cytopenias remains uncertain. This study aimed to develop an evidence-based tool to guide the optimal and cost-effective use of NGS testing in patients with unexplained cytopenia. In this retrospective study, 524 patients with unexplained cytopenias were evaluated and divided into a clonal group with detected clonal mutations (CCUS and MDS, n = 212) and a non-clonal group without detected clonal mutations (n = 312). Demographic, clinical, laboratory, and bone marrow data were analyzed using regression models to predict NGS-based clonal detection, and the model was validated in an independent cohort of 105 patients. Age > 61.4 years, male sex, mean corpuscular volume > 108.8 fL, absolute neutrophil count < 0.95 × 109/L, and bone marrow hypercellularity were all identified as significant predictors of NGS positivity in this multivariate model. The model achieved a sensitivity of 92.9%, specificity of 41.5%, negative predictive value of 89.6%, and a positive predictive value of 52%. Performance in the validation cohort remained robust, with 90.5% sensitivity and 42.5% specificity, confirming the model's reproducibility. This study presents a predictive model that estimates an individual's risk of harboring detectable clonal mutations, supporting clinical decision-making and helping optimize the use of NGS testing, with the potential to contribute to cost savings.

BackgroundIbrutinib exposure is strongly affected by cytochrome P450 3A4 (CYP3A4) activity. Drug-drug interactions (DDIs) can substantially increase ibrutinib plasma concentrations, requiring major dose reductions in DDI management. This study aimed to assess whether splitting ibrutinib 140 mg tablets is a practical and feasible strategy to adjust ibrutinib dosing in case of DDIs.MethodsIbrutinib 140 mg tablets were split into quarters using a tablet splitter aiming at 35 mg dose units. The obtained quarters were evaluated according to the European Pharmacopoeia requirements for Uniformity of Dosage Units. In addition, Uniformity of Mass, Uniformity of Content, loss of mass, stability of quartered tablets, reproducibility of splitting, usability of the splitting device, and patient instructions were assessed. The expected effects of tablet splitting on ibrutinib exposure were calculated.ResultsA strong correlation between tablet mass and ibrutinib content was observed (r = 0.896; p < 0.0001), indicating uniform distribution of ibrutinib throughout the tablets. Loss of mass was <3% for all tablets, indicating that quartering did not lead to substantial material loss. The mean ibrutinib content was 34.4 mg (range 28.2-40.3 mg). Uniformity of Dosage Units of ibrutinib quarters complied with the European Pharmacopoeia requirements, with an acceptance value of 7.5% against a requirement of ≤15%. Split tablets were stable for at least two weeks under outpatient storage conditions. Patient instructions were considered sufficient and the splitting device was rated user-friendly. The impact of splitting variation on exposure is within the range of interindividual variation in ibrutinib exposure.ConclusionSplitting ibrutinib 140 mg tablets may provide a practical, clinically feasible and patient-friendly strategy to obtain 35 or 70 mg doses of ibrutinib when dose reduction is required in the management of DDIs. The expected exposure variation due to dose variations introduced by tablet splitting is unlikely to be of clinical relevance.

Patients with hereditary hemorrhagic telangiectasia (HHT) experience recurrent epistaxis. Doxycycline has been proposed as a possible treatment, although its efficacy remains controversial. Whether the most common genotypes (activin receptor-like kinase 1, endoglin, and SMAD4) contribute to a differential response has not been investigated. In this study, we evaluate the effectiveness of doxycycline among the different HHT genotypes. A retrospective cohort study was conducted at the University of Florida's Hereditary Hemorrhagic Telangiectasia Center. Forty-one adult patients (aged ≥18 years) with HHT, diagnosed by Curacao criteria and genetic testing, were classified as responders and nonresponders based on the minimal clinically important change between pre- and posttreatment epistaxis severity scores (ESS). Hemoglobin and hematocrit values were also collected to assess treatment response. Overall, the cohort was 61% female and 90.2% White, with a mean age of 58.1 years; 26 responders had a decrease (P < .0001) in ESS from a baseline median of 4.6 (interquartile range [IQR], 3.3) to posttreatment ESS of 2.4 (IQR, 1.9). The median baseline ESS for the total cohort was 4.4 (IQR, 3.3), and after a mean follow-up of 4.1 months, it significantly (P < .0001) decreased to an ESS of 3.3 (IQR, 3.2). The mean hemoglobin and hematocrit values did not exhibit significant changes. The relationship between genotype and doxycycline response was not statistically significant. Patients with HHT treated with doxycycline showed an overall reduction in epistaxis severity, which did not appear to be associated with genotype. Doxycycline may be a safe, effective, and accessible treatment option for epistaxis in HHT.

Continuous intravenous heparin infusion is widely used for deep vein thrombosis (DVT) in the intensive care unit (ICU), but accurate prediction of activated partial thromboplastin time (APTT) remains challenging due to patient heterogeneity and complex drug responses. A deep learning model was developed using heparin administration data, laboratory tests, and patient history to predict future APTT values in ICU patients with DVT. Data from 796 patients receiving continuous heparin infusion were collected, including demographics, comorbidities, treatment, and laboratory information, with external validation performed on 514 patients from the Medical Information Mart for Intensive Care (MIMIC) database. A 2-layer Long Short-Term Memory model with dropout was trained and evaluated. Optimal performance was achieved with the [t - 12, t - 2] window, yielding a mean absolute error of 1.885, root mean square error of 4.732, R [2] of 0.945, and mean absolute percentage error of 4.433. Subgroup analyses demonstrated robust accuracy across critical APTT zones and therapeutic categories (subtherapeutic, therapeutic, supratherapeutic), with area under the curve values of 0.92, 0.81, and 0.92. The model predicted abnormal APTT values a mean of 6 hours in advance and could improve guidance over physician-led management in approximately 70% of cases. External validation confirmed good generalizability. Feature importance identified the difference between 45 s and APTT, cumulative heparin dose, and infusion rate as the leading predictors. Collectively, this deep learning model accurately forecasts future APTT values in critically ill patients with DVT receiving intravenous heparin, supporting a shift from reactive to proactive, data-driven heparin management in the ICU with potential benefits for patient safety and treatment efficacy.

IntroductionAntibody-drug conjugates (ADCs) are now widely used in breast cancer across multiple disease subtypes. With increasing clinical use, treatment-related toxicities have become an important factor in therapeutic decision-making. However, comparative safety data among ADCs are limited because direct head-to-head trials are lacking.MethodsWe conducted a systematic review and Bayesian network meta-analysis of randomized controlled trials evaluating ADCs in breast cancer, with the literature search updated through March 31, 2025. Treatment-related adverse events (TRAEs) and serious adverse events (SAEs) were classified according to the Common Terminology Criteria for Adverse Events. A Bayesian random-effects network meta-analysis was used to compare toxicity risks across regimens. Odds ratios (ORs) with 95% credible intervals (CrIs) were estimated, and surface under the cumulative ranking curve (SUCRA) values were used as descriptive ranking summaries interpreted alongside the corresponding comparative estimates. The protocol was registered in PROSPERO (CRD42024606194).ResultsSeventeen randomized trials including 8,946 patients and five ADCs-trastuzumab emtansine (T-DM1), sacituzumab govitecan (SG), trastuzumab deruxtecan (T-DXd), datopotamab deruxtecan (Dato-DXd), and ARX788-were analyzed. SG and T-DXd showed the least favorable hematologic safety profiles, with SUCRA values for anemia/neutropenia of 22.6%/17.4% and 12.0%/27.0%, respectively. T-DM1-based regimens had the highest risk of thrombocytopenia. For gastrointestinal toxicities, SG ranked worst for diarrhea (SUCRA 6.0%), whereas T-DXd was associated with higher risks of nausea (2.2%), vomiting (7.9%), and decreased appetite (8.6%). In analyses of SAEs, SG had the highest rates of anemia (11.7%) and neutropenia (8.5%), while gastrointestinal SAEs occurred more frequently with T-DXd.ConclusionsThis network meta-analysis highlights clinically meaningful differences in ADC safety profiles and may help guide individualized toxicity management in breast cancer.

Diabetes mellitus is characterized by persistent hyperglycemia accompanied by dyslipidemia, oxidative stress, and progressive hepatic, renal, and hematological disturbances. This study evaluated the compositional, antioxidant, and preclinical antidiabetic potential of Trigonella foenum-graecum (fenugreek) and Nigella sativa (black seed) powders, administered individually or combined, in alloxan-induced diabetic rats. Fenugreek powder contained high crude fiber (22.1%) and moderate protein (20.5%), whereas black seed powder showed high crude fat (38.9%) and appreciable protein (20.9%). Total phenolic content was substantially higher in black seed powder (185.3 mg ± 7.6 mg GAE/g) than in fenugreek powder (47.1 mg ± 2.0 mg GAE/g), although both exhibited comparable DPPH radical scavenging activity (63.8%-63.9%). Diabetic rats received fenugreek, black seed, or their combination (100 mg/kg body weight) for 28 days alongside healthy and untreated diabetic controls. All treatments improved glycemic status, with the combined treatment producing the greatest HbA1c reduction (8.9% to 5.1%) compared with fenugreek (6.4%), black seed (6.2%), and untreated diabetic rats (8.1%). Treatments also improved dyslipidemia, hematological indices, and hepatic and renal biomarkers, with the combined treatment consistently showing superior efficacy. These findings support fenugreek and black seed powders as bioactive-rich functional ingredients with complementary glucose-lowering and organ-protective effects, highlighting their promise as a multi-target dietary adjunct against diabetes. PRACTICAL APPLICATIONS: This study demonstrates that the combined use of Trigonella foenum-graecum (fenugreek) and Nigella sativa (black seed) powders has potential as a functional food ingredient or nutraceutical formulation for dietary management of diabetes. Their complementary bioactive composition improved glycemic control, lipid metabolism, and liver and kidney function in a preclinical model, supporting their application in developing value-added functional foods, health supplements, and plant-based therapeutic diets aimed at reducing diabetes-associated metabolic complications.