Citations

ABSTRACT Approximately 30% of patients with acute graft-versus-host disease (GVHD) develop steroid-refractory disease and have very poor outcomes. Ruxolitinib has become the standard of care for steroid-refractory acute GVHD, but it is unclear which patients derive benefit. The MAGIC Composite Score (MCS), an algorithm that combines clinical symptoms and biomarkers, has been validated to predict outcomes at the start of primary GVHD treatment. Here, we evaluated its performance at the initiation of second-line treatment in 278 patients. MCS stratified patients into three risk groups (MCS1-3), with the majority (88%) classified as intermediate or high risk. Increasing MCS score was associated with progressively higher 1-year non-relapse mortality (NRM) rates (16%, 41%, and 73%; p<0.001), lower 1-year survival (77%, 56%, and 24%; p<0.001), and lower complete response (CR) rates at day 28 (47%, 38%, and 20%, respectively; p<0.01). The area under the receiver operating characteristic curve (AUROC) for 1-year NRM was significantly higher with MCS compared to clinical symptoms alone (0.70 vs. 0.63; p=0.023). Among patients treated with ruxolitinib, higher MCS similarly predicted higher NRM and lower survival and CR rates. Patients classified as MCS2/3 had poor outcomes despite ruxolitinib, underscoring the need for novel therapies in this patient population. In conclusion the MCS is an accurate predictor of outcomes for patients who require second-line treatment and may be of use as an eligibility criterion for future clinical trials in this high-risk population. Key Points MAGIC Composite Scores that integrate clinical symptoms and biomarker scores predict outcomes of second-line therapy for acute GVHD more accurately than clinical symptoms alone. MCS identifies patients with high NRM despite treatment with ruxolitinib.

ABSTRACT Background Diagnostic interpretation of kidney allograft biopsies using the Banff classification remains variable, but the determinants of this variability are not fully defined. We performed a global, fully digital multi-reader study to identify the principal drivers of disagreement in Banff-based assessment. Methods Thirty-six kidney transplant biopsies were independently scored by 67 renal pathologists on a standardized digital platform. Readers assessed Banff lesions on hematoxylin and eosin, periodic acid–Schiff, and Jones’ silver stains; final diagnostic categories were assigned using prespecified Banff-based decision rules. Interobserver agreement was quantified with Gwet’s agreement coefficient (AC) statistics. Determinants of diagnostic agreement were evaluated using pairwise mixed-effects logistic regression, and reader similarity was examined by principal component analysis (PCA) with post hoc molecular annotation. Results Agreement for final diagnostic categories was moderate (Gwet’s AC1, 0.55; 95% CI, 0.47–0.63). Lesion-level agreement varied substantially, with lowest agreement for selected threshold-dependent inflammatory or semi-quantitative lesions, including interstitial inflammation in areas of IFTA, peritubular capillaritis and arteriolar hyalinosis. Diagnostic concordance differed markedly across biopsies, indicating strong case-level heterogeneity. In pairwise models, differences in active inflammatory and vascular lesion scoring were the strongest correlates of diagnostic disagreement; reader experience and geography contributed minimally. Principal component analysis showed reader variation was organized along two dominant axes: a rejection-calling threshold axis linked mainly to tubulointerstitial inflammatory injury, and a T cell-mediated (TCMR/TI) and antibody-mediated/microvascular (AMR/MVI) inflammation-oriented phenotypic classification axis. Conclusion Interobserver variation in Banff-based kidney transplant biopsy assessment is structured rather than random and driven mainly by how readers threshold and integrate key inflammatory lesion compartments rather than experience or geographic location.

Importance In vivo biomarkers for detecting neuropathologies from repetitive head impacts (RHI), including chronic traumatic encephalopathy (CTE), are needed. Objective To evaluate the utility of plasma phosphorylated tau 217 (p-tau217), assess its performance as a beta-amyloid (Aβ) biomarker in participants with RHI exposure at risk for CTE, and explore concordance with CTE neuropathology in a postmortem subsample. Design, Setting, and Participants This longitudinal, multicenter, case-control study used data from the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of CTE (DIAGNOSE CTE) Research Project, collected from September 2016 to October 2023. Participants were former American football players (case participants) and asymptomatic men unexposed to RHI (control participants). A subsample had available neuropathologic data. Exposures RHI, traumatic encephalopathy syndrome (TES) diagnoses, and levels of CTE certainty. Main Outcomes and Measures Plasma p-tau217 (classified as positive [≥0.63 pg/mL], intermediate [0.40-0.62 pg/mL], and negative [&amp;lt;0.40 pg/mL]), Aβ–positron emission tomography (PET; 18 F-florbetapir; with Aβ-positive defined as a standardized uptake value ratio [SUVR] ≥1.10), and tau-PET ( 18 F-flortaucipir). TES diagnoses were assigned by multidisciplinary consensus conference. Analyses of postmortem brains controlled for age, race, and APOE ε4 status. Results Among 231 participants (mean [SD] age, 57.75 [8.25] years), 177 were former football players (117 professional and 60 college) and 54 were unexposed participants. Former football players had higher baseline mean (SD) p-tau217 concentrations than unexposed participants (0.35 [0.26] pg/mL vs 0.27 [0.14] pg/mL; P = .008), although this was driven by a higher proportion of Aβ-PET–positive participants among former players. Plasma p-tau217 increased over time across the sample (B = 0.207 [95% CI, 0.117-0.298]; P &amp;lt; .001), with no significant time × exposure group interactions. Among football players, p-tau217 showed no time × group interactions with TES diagnosis, TES-CTE certainty, or RHI metrics. Higher p-tau217 concentration correlated with higher global Aβ-PET SUVR (B = 0.058 [95% CI, 0.053-3.501; P = .01), with a few discordant cases (5 participants were p-tau217–negative and Aβ-PET–positive; 7 participants were p-tau217–positive and Aβ-PET–negative). P-tau217 had similar areas under the curve for projecting Aβ-PET positivity as cerebrospinal fluid (CSF) p-tau181/Aβ42 and CSF Aβ40/42 measures (p-tau217: AUC, 0.88 [95% CI, 0.80-0.96]; CSF p-tau181/Aβ42: AUC, 0.89 [95% CI, 0.79-1.00]; CSF Aβ40/42: AUC, 0.85 [95% CI, 0.72-0.98]). Among 9 brain donors, 6 had CTE (stages II-IV; none with Alzheimer disease). Seven had negative or intermediate p-tau217, concordant with Aβ-PET. Two p-tau217 outliers with stage III CTE had normal concentrations upon additional testing. Conclusions and Relevance The findings of this study suggest that plasma p-tau217 concentration is unlikely to be useful for the detection of CTE, but it does show utility for ruling out Aβ pathology in participants at risk for CTE.

Abstract Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia, pathologically defined by the presence of Lewy bodies. Peripheral and central inflammation are increasingly recognized in DLB in clinical, post-mortem and animal studies. Finding clinically relevant biomarkers of inflammation in DLB will support the identification of novel pathways for disease-modifying therapies or use in clinical trials of immunomodulatory agents. Whilst there are cross-sectional studies of inflammation markers in DLB, there is limited evidence on the association between these markers and cognitive decline over time. Twenty participants with DLB underwent blood sampling for serum inflammatory markers, paired with PET imaging of the translocator protein (TSPO) and up to 4 years of longitudinal cognitive testing. Thirty participants with Alzheimer’s disease—comprising both Alzheimer’s dementia and/or mild cognitive impairment with biomarker evidence of amyloid pathology (AD/MCI+)—and 28 controls were also recruited for group comparisons. Data from 42 baseline cytokine immunoassays and TSPO PET were used as predictors of longitudinal cognitive scores in linear mixed-effects models. Partial least squares regression was used to test the association between peripheral and central inflammation. Using peripheral inflammatory markers as single predictors, we identified 14 associated with either a slower or faster rate of cognitive decline in DLB, whilst no single marker was predictive of decline in AD/MCI+. As many inflammatory markers were highly correlated, we used principal component analysis to identify a cytokine component associated with reduced cognitive decline in both DLB and AD/MCI+, that overlapped with the single markers identified in the previous analysis. A separate component was associated with cognitive decline in AD/MCI+ or DLB with Alzheimer’s dementia co-pathology (ascertained by amyloid PET). Widespread TSPO binding was associated with reduced cognitive decline in DLB, whilst a fronto-temporal pattern was associated with more rapid cognitive decline in both DLB and AD/MCI+. There were associations between peripheral cytokines and TSPO PET in AD/MCI+, but these were not significant in DLB. Overall, peripheral and central inflammation predicted cognitive decline in DLB. Specific patterns associated with both faster and slower rates of decline were identified. These profiles had both overlapping and contrasting associations when compared to AD/MCI+. Collectively, these data add to a body of evidence suggesting clinically relevant levels of inflammation in DLB. Future studies in larger, multi-site cohorts with multiple biomarker sampling points are required to understand the impact and dynamics of inflammation across all stages of the disease.

ABSTRACT Ischemic events after contemporary percutaneous coronary intervention (PCI) are uncommon but carry high morbidity/mortality. Identifying patients at highest risk is critical to guide dual antiplatelet therapy (DAPT) intensity while minimizing bleeding. Current machine learning (ML) model‐developed risk scores do not incorporate pharmacogenetic data. To develop and externally validate ML models that integrate clinical, demographic, and CYP2C19 genetic information to predict 1‐year ischemic outcomes post‐PCI to refine clinical decision making. We analyzed 8317 patients from TAILOR‐PCI trial ( n = 4572) and the Precision PCI registry ( n = 3745). The outcome was a composite of cardiovascular death, myocardial infarction, stroke, and stent thrombosis at 1 year. Boruta feature selection identified 11 predictors. Multiple ML algorithms were trained in TAILOR‐PCI and validated in Precision PCI using cross‐validation and synthetic minority oversampling (SMOTE). Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The best external performance was achieved with a support vector machine (SVM, polynomial kernel) (AUC 0.667; sensitivity 0.871; specificity 0.282), while XGBoost provided a more balanced profile (AUC 0.619; sensitivity 0.442; specificity 0.688). Variable importance for the SVM polynomial model demonstrated that all 11 included Boruta feature selected predictors had relatively high importance (> 75). ML models trained on large clinical trial and real‐world registry datasets can help identify the small subset of patients at high ischemic risk after PCI. This distinction is of relevance because ischemic events are rare, and most patients may safely de‐escalate DAPT to reduce bleeding risk while maintaining ischemic protection through a multimodal approach to risk stratification. Trial Registration: TAILOR‐PCI URL: https://clinicaltrials.gov/ct2/show/NCT01742117

Abstract Burke, AA, Saine, ND, King, EL, Fields, JB, Jagim, AR, Miller, AD, Green, BC, and Jones, MT. Longitudinal modeling of pitching workload and countermovement jump performance as determinants of fastball velocity and consistency in collegiate baseball pitchers. J Strength Cond Res XX(X): 000–000, 2026—Maintenance of four-seam fastball (FSFB) velocity across the baseball season is critical, yet the extent to which workload and neuromuscular status relate to velocity is unclear. Thus, aims of the current study were to assess the relationship between external pitching workload metrics and FSFB velocity; quantify within-season FSFB velocity; and examine how countermovement jump (CMJ) performance predicts FSFB velocity. Collegiate pitchers ( n = 8) completed weekly CMJ testing during a 15-week, 53-game season. Countermovement jump metrics included jump height (JH), reactive strength index–modified (RSImod), peak braking force, and peak propulsive force normalized to body mass. Workload variables (innings, total pitches, FSFB pitches) and FSFB velocity were evaluated via repeated measures correlation (RMCORR). A longitudinal heat map visualized velocity trends, and a hierarchical location–scale model assessed predictors of mean velocity and variance. Repeated measures correlation showed weak negative associations between FSFB velocity and innings ( r = −0.15, p = 0.11), total pitches ( r = −0.18, p = 0.05), and FSFB pitches ( r = −0.18, p = 0.05). Heat map analysis identified 3 distinct velocity clusters. Location model results indicated no predictors of mean velocity. The scale model showed JH ( γ = −0.060, p = 0.001) predicted reduced velocity variance, and RSImod ( γ = 3.800, p < 0.001) predicted increased variance. Findings suggest that velocity patterns varied across athletes, where greater workloads were negatively associated with FSFB pitch velocity. Further, CMJ performance related to velocity stability rather than mean velocity. Routine longitudinal monitoring and continued strength-power training are recommended to support FSFB velocity.

Importance There is no consensus on staging and surveillance imaging for cutaneous squamous cell carcinoma (CSCC). Although imaging has been shown to affect management, broad recommendations from the National Comprehensive Cancer Network have led to variability in clinical practice. Objective To develop multidisciplinary consensus recommendations on the use of staging and surveillance imaging of localized CSCC. Evidence Review A multidisciplinary expert panel across academic and clinical practice settings convened a Delphi consensus, with 3 iterative survey rounds from January to June 2025. Data were analyzed from February 2025 to January 2026. Eligibility defined by at least 1 to 2 CSCC publications during the previous 5 years, involvement in a relevant clinical trial, experience treating at least 3 patients monthly with CSCC, and/or 5 years or longer of clinical practice. Fifty-four experts were invited and 45 (83%) completed all 3 rounds and were included in the final analysis. Structured Delphi surveys evaluated clinical scenarios, imaging modalities, and surveillance strategies for CSCC. Consensus and near-consensus recommendations were generated, defined as 80% or greater and 70% to 79% agreement, respectively. Findings The 45 participants (21 female individuals [47%] and 24 male individuals [53%]; 14 Asian individuals [31%], 1 multiracial individual [2%], and 30 White individuals [67%]) consisted of dermatology (15 [33%]), medical oncology (7 [16%]), radiation oncology (9 [20%]), radiology (9 [20%]), surgery (3 [7%]), and otolaryngology specialists (2 [4%]). The Delphi panel recommended staging and surveillance for CSCCs with at least a 15% risk of metastasis. Consensus or near consensus was reached to recommend staging and surveillance imaging for tumors with a concern for metastasis, bone invasion, invasion beyond subcutaneous fat, large-caliber nerve invasion, or a diameter of 4 cm or larger or the combination of tumors with poorly differentiated histology and any of the following: diameter of 2 cm or larger, lymphovascular invasion and subcutaneous fat invasion, or lymphovascular invasion and small-caliber perineural invasion. Computed tomography imaging was the preferred modality for nodal staging (38 [84%]) and surveillance (35 [78%]). For surveillance duration, consensus was reached to provide imaging for at least 2 years, and near consensus was reached for at least 3 years. Conclusions and Relevance This study provides an expert consensus–based framework to standardize imaging in localized CSCC that may inform future guidelines.

Abstract Hemorrhagic shock is a common emergency that accounts for more than 10% of global mortality and up to 40% of trauma-related mortality. The Advanced Trauma Life Support (ATLS) guidelines outline resuscitation strategies in patients with massive hemorrhage based on clinical trial and observational data. Early intervention with fluids and/or blood products is recommended during resuscitation as key to maintaining vascular patency, stabilizing a patient’s blood pressure, maintaining tissue oxygenation, and limiting shock. From a transfusion perspective, there is wide heterogeneity in the quality of blood products due to donor and manufacturing variation. The optimal transfusion strategy for massive hemorrhage remains unclear. In silico models of resuscitation may offer a means to evaluate the effectiveness and safety of various resuscitation protocols. Here we describe a stochastic multicompartment model of fluid balance and resuscitation that includes (i) cardiovascular hemodynamics, (ii) body fluid compartments and capillary solute exchange, (iii) the ability to alter hemorrhage, resuscitation, and hemostasis parameters, and (iv) tissue oxygenation and capillary-alveolar gas exchange. Building upon deterministic frameworks, this stochastic model more faithfully reflects the clinical heterogeneity of bleeding patients at a level I trauma center. This allows for a proof of concept in silico trial comparing crystalloids, conventional component therapy (CCT), i.e. red cell, platelet and plasma components, to cold-stored low titer group O whole blood (LTOWB). In an in silico cohort of ATLS class III (>30% and ≤40% blood volume lost) hemorrhage, LTOWB resuscitation reduced the time spent in the critical hemostatic window (platelet count <50x109/L, INR≥2, hemoglobin (Hgb) <8 g/dL and fibrinogen <150 mg/dL) compared with CCT (90.59 vs. 147.62 minutes; p=0.04), with no difference in predicted event-free survival (t = 240 minutes; cardiac < 1.5, fluid overload > 10% or SBP > 150% of the starting SBP, or Hgb < 3.0 g/dL). In a separate cohort of ATLS class IV (>40% blood volume lost) hemorrhage, LTOWB yielded a higher predicted event-free survival (74%) versus the CCT arm (69%, p < 0.01). We demonstrate how this in silico platform can function as a digital twin for hemorrhagic trauma enabling precision transfusion strategies, and in parallel, an operational twin to support blood banks to forecast blood product demand and inform massive transfusion protocols and clinical trial design.

PURPOSE Social determinants of health (SDOH) shape cancer treatment access, adherence, and outcomes, yet their collection and use within National Clinical Trials Network (NCTN) studies remain poorly defined. This study examined how demographic and SDOH-related variables were historically collected and published to identify gaps that constrain the study of social context within NCTN trials. METHODS Participant-level data from completed phase III trials for gastrointestinal (GI) cancers conducted by the Alliance for Clinical Trials in Oncology (Alliance) or its legacy groups from 1999 to 2018 were pooled. Thirteen measures were assessed: four demographic and nine SDOH-related. The proportion of individual participants with data collected for each measure was evaluated. Data utilization was evaluated for all primary articles and via targeted review of related publications using the number either reporting subgroups or publishing analyses for each measure. RESULTS A total of 12,701 participants across 11 trials were included. All trials collected demographic measures (<2% of patients missing), insurance status (1% missing), and ZIP code (3% missing). Education level was collected in two trials (28% missing) with marital and employment status collected in one trial (41% missing for both). No trials collected data on other SDOH-related measures. Education level was the only SDOH-related measure reported in primary articles, and none reported analysis of SDOH-related measures. Of the 149 related publications, <2% reported or analyzed any SDOH-related measure. CONCLUSION Across Alliance and NCTN legacy group phase III trials for GI cancers, demographic variables have been consistently collected and frequently reported or analyzed, whereas SDOH-related measures are inconsistently collected and rarely published in the literature. These findings demonstrate a historical absence of routine SDOH data capture and utilization within NCTN trials.

Black race and Hispanic ethnicity are associated with higher mortality in severe combined immunodeficiency (SCID) following hematopoietic cell transplantation (HCT), though mechanisms remain unclear. We evaluated 796 children with SCID who received nonsibling HCT between 1982 and 2020 using data from the Primary Immune Deficiency Treatment Consortium. Overall survival for Black (aHR 2.47, 95%CI 1.64, 3.71) and Asian/Pacific Islander patients (aHR 1.82, 95%CI 1.00, 3.30) was significantly lower compared with non-Hispanic White patients, while Hispanic patients had lower event-free survival (aHR 1.83, 95%CI 1.27, 2.63) compared with non-Hispanic White patients. Even after adjusting for age and infection, Black patients with SCID had more than twofold hazard of death compared with non-Hispanic White patients. NBS was associated with earlier diagnosis, reduced infection at HCT, and elimination of survival disparities between Black and non-Hispanic White patients. These findings suggest that universal, system-level interventions such as NBS can mitigate disparities in outcomes for children with SCID.