HDAC6 is a biomarker of leukaemic dissemination and relapse in B-ALL - British Journal of Cancer

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Povorcitinib for hidradenitis suppurativa: the randomized, double-blind, placebo-controlled STOP-HS1 and STOP-HS2 phase 3 trials - Nature Medicine

In a pair of pivotal phase 3, placebo-controlled, randomized clinical trials, the oral JAK1 inhibitor povorcitinib significantly reduced abscesses and inflammatory nodules in patients with moderate to severe hidradenitis suppurativa.

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FcRH5×CD3 bispecific antibody cevostamab in relapsed or refractory multiple myeloma: a phase 1 trial - Nature Medicine

In a phase 1 trial, the maximum tolerated dose for an FcRH5-containing bispecific T cell engager was not reached, and there was an encouraging response rate in patients with relapsed or refractory multiple myeloma.

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Individualized antisense oligonucleotides for SCN2A-related developmental epileptic encephalopathy - Nature Medicine

In two patients with SCN2A epileptic encephalopathy, treatment with personalized allele-selective antisense oligonucleotides led to a decrease in seizure frequency with a positive safety profile.

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Global breast cancer survival estimates in 2017–2021 to advance the WHO Global Breast Cancer Initiative - Nature Medicine

Benchmark estimates from 2017–2021 provide an updated assessment of progress toward the WHO Global Breast Cancer Initiative survival targets across all 194 Member States.

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Efficacy of higher-dose versus lower-dose corticosteroids in community-acquired pneumonia: a systematic review and network meta-analysis - Critical Care

Background Adjunctive corticosteroids improve outcomes in hospitalized patients with community-acquired pneumonia (CAP), but whether higher-dose regimens provide additional benefit over lower-dose regimens remains uncertain. Methods We searched PubMed, Embase, and Cochrane databases for randomized controlled trials (RCTs) up to January 25, 2026. Interventions were standardized to protocol-assigned dexamethasone-equivalent doses: high (≥ 7.5 mg/d) and low (< 7.5 mg/d). A frequentist network meta-analysis was performed. The primary outcome was short-term all-cause mortality. Confidence in network meta-analysis estimates was assessed using the Confidence in Network Meta-Analysis (CINeMA) framework. Results 32 RCTs involving 9,746 participants were included. Compared with placebo or usual care, higher-dose corticosteroids were associated with lower short-term mortality (Risk Ratio [RR], 0.83; 95% Confidence Interval [CI], 0.74–0.92), as were lower-dose corticosteroids (RR, 0.84; 95% CI, 0.75–0.95). The indirect comparison showed no clear difference between higher- and lower-dose regimens (RR, 0.98; 95% CI, 0.83–1.16). In severe patients with CAP, the corresponding indirect estimate was RR 1.01 (95% CI, 0.77–1.33). Most secondary active-dose comparisons were imprecise and showed no consistent advantage of either strategy. Conclusion Compared with placebo or usual care, lower-dose corticosteroids (moderate confidence) and higher-dose corticosteroids (low confidence) were both associated with lower short-term mortality. The indirect higher-versus-lower dose comparison showed no clear mortality difference between dose categories; confidence in this comparison was low. Future research should prioritize large, head-to-head RCTs designed to evaluate whether selected inflammatory phenotypes benefit from higher-dose corticosteroids.

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The Practices of Pancreatic Neck Margin Testing and Their Outcomes after Pancreatoduodenectomy for Pancreatic Ductal Adenocarcinoma - Annals of Surgical Oncology

Background The role of checking the pancreatic neck margin with frozen section (PNM-FS) during pancreatoduodenectomy (PD) for pancreatic ductal adenocarcinoma (PDAC) to secure R0 resection and its impact on long-term outcomes remains an area of debate. Patients and Methods Patients with PD for PDAC between 2018 and 2023 were included. The primary outcome was pancreatic neck recurrence-free survival (PN-RFS). Secondary outcomes were locoregional recurrence-free survival (LR-RFS), distant recurrence-free survival (D-RFS), and overall survival (OS). Results There were 403 patients who met inclusion criteria. PNM-FS was checked in 361 patients (89.6.2%) and returned negative at first attempt in 285 (78.9%). A total of 76 patients had positive PNM-FS; 71 were revised and clearance achieved on repeat sampling in 49 (69.0%). Median PN-RFS in patients with PNM-FS cleared with revision was significantly shorter compared with those with negative PNM-FS at first attempt (16.9 versus 23.1 months; p = 0.048) but was not different from patients with PNM-FS not cleared (16.9 versus 16.0 months; p = 0.961). LR-RFS and D-RFS were not different between the groups. OS was marginally longer in patients with negative PNM-FS at first attempt (23.9 versus 19.4 versus 16.0 months; p = 0.049). Six patients underwent completion total pancreatectomy (TP) for margin clearance, four developed distant recurrence, one locoregional recurrence and two died without disease at 1 and 11 months postoperatively. Conclusions PNM-FS is only a prognostic marker. Pursuing PNM-FS clearance does not improve PN-RFS, LR-RFS, D-RFS, or OS. Furthermore, pursuing a completion TP may be associated with shorter OS either from disease progression or surgical morbidity.

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Clinical decision support in hematological malignancies using a case-grounded AI agent - Nature Medicine

A locally deployable, case-grounded large language model agent achieved high concordance with hematology tumor board decisions across retrospective, external and prospective evaluations.

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Metabolic determinants of cancer immunotherapy outcomes identified by plasma profiling - Nature Medicine

Mass-spectrometry-based metabolomic analysis of plasma samples from multiple cohorts of patients treated with immunotherapy across five distinct tumor types, followed by machine learning enabled identification of metabolic signatures, as well as functional exploration, reveals association of increased plasma histidine levels with prolonged survival and its potential for therapeutic intervention.

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Fate induction through asymmetric T cell division is modulated by chimeric antigen receptor costimulatory domains - Nature Immunology

Asymmetric cell division is thought to affect chimeric antigen receptor (CAR) T cell efficacy owing to distinct CAR T daughter cell effector and memory T cell fates. Here the authors show how the costimulatory domain of the CAR T cell can affect this process.

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Contribution of resting pulse rate to fall risk prediction in patients with glaucoma: a nationwide retrospective study based on an XGBoost model - BMC Ophthalmology

Background Falls are among the most common safety concerns in people with visual impairment and can lead to serious consequences, including fractures, prolonged hospitalization, and even death. Patients with glaucoma are at increased risk of falls due to visual field loss, impaired motor coordination, and declines in cognitive function compared with the general population. Resting pulse rate is an easily obtainable measure in routine clinical practice; however, its contribution to fall risk prediction in patients with glaucoma has not been sufficiently investigated. To address this knowledge gap, we developed and compared multiple predictive approaches by incorporating a broad range of fall-related variables into prediction models, and we used explainable machine learning to quantify the contribution of resting pulse rate to fall risk prediction in glaucoma. In doing so, we aimed to explore the potential contribution of resting pulse rate as one of the model features in fall risk estimation, rather than as a standalone glaucoma-specific ophthalmic indicator. Methods Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). We included 249 participants with self-reported physician-diagnosed glaucoma who had no history of falls at the 2015 baseline survey and completed follow-up in 2018. The outcome was the occurrence of any fall between 2015 and 2018. To further characterize baseline differences, we also included 12,297 participants without glaucoma and without a history of falls at the 2015 baseline survey for comparative analyses.Candidate predictors comprised demographic characteristics, clinical comorbidities, medication use, self-reported vision status, and relevant laboratory measures. Self-reported near and distance vision were treated as limited visual functional information available in the database and were not considered equivalent to objective glaucoma-specific ophthalmic indicators. To compare machine learning models with a conventional statistical approach, we developed a logistic regression (LR) baseline model and trained six machine learning models: random forest, XGBoost, gradient boosting decision tree (GBDT), support vector machine (SVM), k-nearest neighbors (KNN), and AdaBoost. Feature selection was performed in the training set using recursive feature elimination with 5-fold cross-validation; within each fold, feature selection was conducted using only the fold-specific training subset and evaluated on the corresponding validation subset to reduce the risk of information leakage and overly optimistic performance estimates. After determining the final feature subset, hyperparameters were tuned and models were fitted using cross-validation within the training set. Model stability was assessed using 1,000 bootstrap resamples of the training set, and we reported the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals, accuracy, and F1 score. Calibration curves and decision curve analysis were used to evaluate calibration and clinical net benefit. Finally, SHAP was applied to interpret the best-performing XGBoost model. Results A total of 249 eligible participants with glaucoma were included. During follow-up, 36 participants reported at least one fall, yielding a fall incidence of 14.46%. In contrast, among the 12,297 non-glaucoma participants included for baseline comparison, 873 reported at least one fall (7.1%; P < 0.001).In model development, the conventional logistic regression model showed the lowest discriminative performance, with an AUC of 0.676 (95% CI, 0.628–0.724). The XGBoost model achieved the best performance, with an AUC of 0.851 (95% CI, 0.812–0.886). Decision curve analysis indicated that, within a threshold probability range of 51.5% to 67.5%, the XGBoost model provided greater net benefit than the other machine learning models. SHAP-based feature importance further identified key predictors of falls in patients with glaucoma, with resting pulse rate ranking among the top contributing features in the XGBoost model. Conclusion In this study, the XGBoost model demonstrated the best performance for estimating fall risk among participants with self-reported glaucoma. SHAP analyses indicated that resting pulse rate, creatinine, age, blood urea nitrogen, frailty status, and height made relatively large contributions within the final model. Given the absence of objective ophthalmic parameters, these findings should be regarded as exploratory and interpreted cautiously. Resting pulse rate may provide supplementary information within model-based fall risk estimation, but it should not be interpreted as a standalone glaucoma-specific indicator or as evidence of causality.

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