Citations

ABSTRACT Background and Objectives Among patient with early‐stage breast cancer, breast conservation surgery (BCS) is the most performed surgery, utilized in approximately two‐thirds of patients. While 5‐year overall‐survival rates are strong—typically above 90%—additional re‐excisions can occur in up to 25% of patients who undergo index BCS and some patients will require subsequent surgery for new breast cancer or recurrences. As such, these additional procedures can complicate patients’ pathway to survivorship, negatively impact quality of life, and lead to excess healthcare costs. Methods This retrospective cohort study used linked claims and an electronic healthcare record database to (1) characterize patients at higher risk for additional breast oncologic surgery (aBOS) following BCS, and (2) quantify the long‐term financial impact of aBOS after BCS. In total, 87,190 patients with breast cancer, who had an index BCS between January 1, 2012, to March 31, 2023, were followed for up to 5‐years post‐operatively. Patients with and without aBOS were analyzed, comparing demographics, tumor characteristics, healthcare utilization, and per‐person‐per‐month (PPPM) costs. Results Twenty‐three percent ( n = 20,212) of patients underwent aBOS. These patients were younger, had higher tumor grades and larger tumor sizes, and incurred greater healthcare costs compared to patients who did not undergo a secondary surgery. Conclusion This study highlights significant factors influencing BCS outcomes and healthcare utilization, underscoring the need for tailored therapeutic strategies for patients with breast cancer.

Importance Recent case reports suggest that B antigen–containing blood products may be associated with anaphylactic transfusion reactions in recipients with preformed immunoglobulin E to galactose- α -1,3-galactose (alpha-gal). Objective To test the association of local alpha-gal syndrome (AGS) prevalence and allergic transfusion reaction (ATR) in patients with blood type O. Design, Setting, and Participants In this international, multicenter, retrospective cohort study at academic medical centers, sites were assigned to AGS high- or low-prevalence clusters based on the known geographic distribution of AGS. Data were collected on platelet or plasma transfusions and ATRs during 2020 to 2024. Consecutive patients receiving platelet or plasma transfusions were included. Exposures Patients with blood type O who received B or AB units and patients with blood type O who received O units (reference group) in AGS high- and low-prevalence clusters were compared. Main Outcomes and Measures Before data collection, the hypothesis was that if transfusion-related alpha-gal syndrome (TRAGS) is a true clinical entity, excess ATRs to group B or AB units would be detected in AGS high-prevalence regions exclusively. The main measure was the overall risk ratio (RR) for ATRs to B or AB plasma or platelets in AGS high- vs low-prevalence clusters. Results In total, 558 823 platelet and plasma transfusions at 40 sites in 5 countries were analyzed, of which ATRs occurred in 1744 transfusions (0.3%). In the US AGS high-prevalence cluster (9 sites), significantly more ATRs of any severity occurred among patients with blood type O who received B or AB units vs patients with blood type O who received O units (overall RR, 3.93; 95% CI, 2.96-5.21; P < .001). In contrast, in the primary analysis of the AGS low-prevalence cluster (15 sites), excess ATRs to B or AB units were not detected. In subgroup analyses among patients with blood type O receiving B units, the RR for moderate to severe ATRs was 9.14 (95% CI, 5.39-15.52; P < .001) in the AGS high-prevalence cluster vs 2.15 (95% CI, 1.34-3.47; P = .002) in the AGS low-prevalence cluster. Outside the US, a signal consistent with TRAGS was not detected. Conclusions and Relevance This cohort study provides provocative epidemiologic evidence that TRAGS may be a unique manifestation of AGS and a previously unrecognized risk associated with transfusion. In AGS high-prevalence regions, blood collectors and hospital transfusion services should consider approaches to preventing severe ATRs from B or AB plasma or platelet units.

Background: Several breast cancer (BC) risk prediction models have been developed to provide personal risk assessments. Though individually validated, their performance has not been systematically evaluated across a wide range of populations or ages. Methods: We harmonized individual-level baseline questionnaire data and incident BC diagnoses from 21 cohorts from North America, Europe, and Australia participating in the Breast Cancer Risk Prediction Project. Five-year absolute risk of invasive BC was estimated for five established risk prediction models using classical risk factors only. Discrimination was evaluated by area under the curve (AUC). Calibration was assessed using average and risk-decile specific expected to observed (E/O) ratios. Performance metrics were meta-analyzed across cohorts and models. Metaregression tested associations between cohort characteristics and performance metrics. Results: This analysis included 1,595,977 women aged 20-75 years, enrolled in studies between 1976-2015, with 19,062 (1.2%) invasive BC cases ascertained within 5 years from exposure assessment. Age-adjusted AUCs were similar across models and cohorts (pooled AUCs by model: 0.57-0.58), while E/O ratios varied substantially (pooled E/O ratios by model: 0.83-1.25). Overestimation was common among predicted high-risk individuals (>3%). No appreciable differences in model performance by cohort age, birth year, race, and variable missingness emerged. Calibration improved after assigning race-specific incidence rates. Conclusion: Existing BC risk prediction models provided similar risk discrimination across multiple cohorts, although there was overestimation of risk for high-risk individuals. Performance variation across cohorts was not driven by specific characteristics, which supports development of a unified risk model for diverse populations that leverages appropriate incidence rates.

Myeloproliferative neoplasm (MPN) patients are at risk of splanchnic vein thromboses (SVT). Prior studies have failed to demonstrate a benefit of hydroxyurea therapy in preventing recurrent thrombosis after SVT, but are limited by small sample sizes and inability to account for starting, stopping, or switching of cytoreductive therapies. To better assess the impact of cytoreductive therapy on thrombosis recurrence, we performed a retrospective cohort study of MPN-SVT patients from the international GASTRO-MPN Consortium, treating cytoreductive therapy as a time-dependent covariate. We identified 757 patients, of which 43% were treated with cytoreductive therapy. During a median follow-up of 7.4 years, 256 patients (34%) had thrombosis recurrence; 145 (19%) had SVT extension/recurrence/TIPS thrombosis, 138 (18%) an thrombosis recurrence outside the splanchnic bed (74% were venous). Additionally, 262 patients (35%) experienced clinically relevant bleeding and 170 (22%) died. After adjusting for age, sex, prior thrombosis, timing of MPN diagnosis relative to SVT, anticoagulation initiation within 30 days of SVT diagnosis, MPN type, JAK2 status, other cancers and cirrhosis, cytoreductive therapy was associated with a decreased risk of recurrent thrombosis (HR 0.67 95%CI 0.50-0.89, p=0.01). This was driven by a lower risk of SVT extension/recurrence (HR 0.62 95%CI 0.42-0.90, p=0.01) but not by extra-splanchnic thrombosis recurrence (HR 0.97 95%CI 0.72-1.30, p=0.82). In a subgroup of patients without erythrocytosis/thrombocytosis at initial SVT (n=275), cytoreductive therapy was associated with a HR 0.65 (95%CI 0.40-1.07, p=0.09) for recurrent thrombosis. These data support the use of cytoreductive therapy in MPN-SVT patients to prevent recurrent thrombosis, particularly SVT extension/recurrence.

MOGAD is a rare autoimmune encephalomyelitis that shares similar clinical manifestations with other central nervous system demyelinating diseases. However, they must be distinguished due to their distinct pathogenesis and treatment methods. Currently, the clinical diagnosis of MOGAD primarily relies on patients’ clinical manifestations and imaging features, with biomarker application being relatively limited. Meanwhile, research on MOGAD biomarkers has advanced rapidly, with findings mainly focusing on imaging features, antibody titers, nerve cell markers, cytokines, and inflammatory cell ratios. These biomarkers can distinguish among various autoimmune with similar clinical manifestations and exhibit certain specificity. If these biomarker findings are applied to the clinical diagnosis of MOGAD, they could enhance diagnostic accuracy and support earlier and more accurate diagnosis, while providing a scientific basis for evaluating disease progression and prognosis. We discuss the biomarkers and emerging biomarkers of MOGAD, emphasizing the specific changes and aspects that may be applicable to clinical diagnosis and treatment.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Background: Noninvasive tests are well validated in metabolic dysfunction–associated steatotic liver disease, but evidence in metabolic dysfunction and alcohol-associated liver disease (MetALD) and alcohol-associated liver disease (ALD) is limited. We evaluated noninvasive test–based clinical care pathways for fibrosis risk stratification in MetALD and ALD. Methods: This is a multinational, multicenter, cross-sectional study across 35 centers in 16 countries (2013–2025), including adults with MetALD or ALD. Fibrosis was assessed by liver biopsy and/or vibration-controlled transient elastography (VCTE). In biopsy-proven participants, we analyzed the sequential pathway (Fibrosis-4 [FIB-4] first, followed by VCTE for indeterminate FIB-4) to identify advanced fibrosis (≥F3). Diagnostic accuracy was assessed using the AUC. Results: Among 893 participants (41.3% MetALD and 58.7% ALD), the median age was 52 [43.0–61.0] years, and 79.4% were male. The estimated prevalence of advanced fibrosis was 45% (32.2% in MetALD and 54.0% in ALD). Participants with MetALD had a more dysmetabolic profile but lower fibrosis stages than ALD. Among biopsy-proven participants, FIB-4 AUC was 0.720, and VCTE AUC was 0.833. FIB-4 performed better in MetALD than ALD (AUC 0.773 vs. 0.540), while VCTE accuracy was similar across groups. In the sequential pathways, the false-negative rate for advanced fibrosis (misclassified as low risk) was 6.8% (4.9% MetALD and 11.3% ALD). Conclusions: In biopsy-proven patients, FIB-4 performance was acceptable in MetALD but substantially weaker in ALD. The standard 2-step pathway performed adequately in MetALD but missed a clinically meaningful proportion of advanced fibrosis in ALD.

Abstract Introduction Microglia are the resident immune cells of the central nervous system, classically studied for neuroinflammation. A specialized subset, vessel-associated microglia (VAM), whose somata directly contact capillaries, constitutes ∼30% of microglia in the naïve brain. Only recently have VAM been recognized as regulators of brain circulation, influencing blood—brain barrier (BBB) integrity and cerebral blood flow, yet their role in pathological vascular remodeling remains unclear. To address this gap, we used glioma models in which peritumoral capillaries undergo extensive vascular remodeling and BBB dysfunction, providing an in vivo platform to probe capillary vulnerability and vascular stability. Methods We combined pharmacological microglial ablation via CSF1R inhibitors with longitudinal in vivo two-photon imaging to visualize microglia—capillary interactions. Behavioral testing, survival analysis, T2-weighted MRI, and immunostaining were performed in parallel. Results Over half of the microglia-depleted mice developed acute, lethal paralysis by 15 days, whereas control tumor-bearing mice remained asymptomatic and survived 30 days. MRI revealed large intracranial hemorrhages and severe edema, and two-photon imaging showed nodular, abnormal vasculature at paralysis onset. The peritumoral region contained dense capillary networks with a marked increase in VAMs (>60%). Genetic lineage tracing confirmed these cells were microglia, exhibiting elongated, vessel-wrapping morphology, also observed following single-vessel photothrombosis and consistent with a response to capillary injury. Conclusion Our findings identify VAMs as critical neurovascular stabilizers that preserve peritumoral capillary integrity and prevent lethal hemorrhage in glioma, highlighting an essential immune role in brain vascular homeostasis. Notably, intracranial hemorrhage has repeatedly emerged across clinical trials of CSF1R inhibitors, raising important safety considerations for CSF1R-targeted therapies in the diseased brain. Funding Source AHA postdoc fellowship (26POST1560008) (J.Z.) Topic Categories Neuroimmunology (NEUR)

Abstract Immune checkpoint inhibitors (ICIs) can produce durable tumor control, yet many patients experience primary or acquired resistance, mixed lesion-level responses, or immune-related adverse events. Tissue and blood biomarkers provide biologically informative but spatially incomplete views of a heterogeneous and time-varying tumor–host system. Radiologic imaging complements these assays by repeatedly measuring whole-body tumor burden, organ-specific disease patterns, lesion-level heterogeneity, and treatment-related change. This critical narrative review evaluates imaging-centered artificial intelligence (AI) for precision cancer immunotherapy, including baseline and serial CT, MRI, and PET; radiomics and learned image representations; lesion-level and whole-body heterogeneity; toxicity assessment; and integration with pathology, genomics, circulating tumor DNA, laboratory measurements, and electronic health records. Representative cohorts range from early radiogenomic studies of approximately 100–200 patients to externally validated and longitudinal models involving hundreds or thousands of patients. Rather than treating all reported performance estimates as equally actionable, we appraise the clinical question, cohort design, endpoint, validation strategy, calibration, and intended clinical action. Current evidence supports noninvasive immune phenotyping, risk stratification, longitudinal monitoring, and multimodal biomarker integration. However, most models predict outcomes among patients already receiving ICIs and therefore remain prognostic under treatment rather than predictive of differential treatment benefit. Radiotherapy (RT) combined with ICI serves as a focused imaging use case because lesion identity, dose distribution, fractionation, sequence, and thoracic and normal-tissue exposure must be linked to defined actions. Existing patient-level AI studies estimate efficacy or toxicity after treatment selection; none has prospectively shown that an AI-selected RT strategy improves patient outcomes. Translation will require patient-level leakage control, calibration, geographic and temporal validation, robustness to missing modalities, and prospective evaluation of prespecified model-guided decisions.