Citations

Abstract Purpose: Circulating tumor fraction estimate (ctFE) is a machine learning–derived composite metric of circulating tumor DNA (ctDNA) burden. We hypothesized that pre-treatment and early on-treatment ctFE could robustly risk-stratify patients with locally advanced (LA) and oligometastatic non–small cell lung cancer (NSCLC) treated with radiotherapy (RT). Experimental Design: In a prospective phase II clinical trial (NCT03916419), 26 patients with unresectable stage IIB to IIIC NSCLC received magnetic resonance (MR)-guided hypofractionated chemoradiotherapy (chemoRT) followed by immunotherapy. Plasma ctDNA was profiled at baseline and mid-treatment (days 10–14) to derive ctFE and maximum variant allele frequency (Max VAF). A burden-based ctFE threshold derived from baseline samples was applied unchanged to mid-treatment samples and validated in two external cohorts: LA NSCLC treated with chemoRT (LA-RW; n = 94) and oligometastatic NSCLC treated with RT (OM-RW; n = 309). Results: Pre- and mid-treatment ctFE burden strongly stratified overall survival (OS) and progression-free survival (PFS), outperforming Max VAF and ctFE detectability. The baseline ctFE was prognostic for OS (HR 5.93, P = 0.005) and PFS (HR 11.08, P < 0.001) and remained significant at mid-treatment (OS: HR 7.08; PFS: HR 12.06; both P < 0.001). Early ctFE dynamics defined three molecular response groups with OS separation (median OS 60.8 vs. 13.0 vs. 2.9 months; P < 0.001). ctFE remained associated with survival in both validation cohorts. Conclusions: Early ctFE derived from a clinically available, tumor-naïve ctDNA assay enables noninvasive risk stratification in LA and oligometastatic NSCLC treated with RT, supporting its use as a practical biomarker for precision treatment adaptation.

Introduction: Abnormal sleep has been linked to increased dementia risk, but the pathophysiological processes driving this connection are unclear. To provide insight into the biological pathways underlying the relationship between sleep and brain health, we tested the hypothesis that increased obstructive sleep apnea (OSA) severity and shorter habitual sleep duration are associated with a higher burden of Alzheimer’s disease (AD) pathology, neurodegeneration, and neuroinflammation measured through plasma biomarkers. Methods: ARIC participants who took part in the Sleep Heart Health Study at Visit 4 (1996-98) with stored plasma samples at Visit 3 (1993-95) and Visit 5 (2011-13) were examined (n=261; mean age 61.3 years; 43.3% male). OSA severity, categorized based on the number of apneas and hypopneas per hour of sleep (<5 events/hour [Normal], 5 to <15 events/hour [Mild OSA], or ≥15 events/hour [Moderate/Severe OSA]) was assessed via in-home polysomnography, and average habitual sleep duration (<7 hours, 7 to <8 hours, or ≥8 hours) was self-reported. Plasma biomarkers of amyloid beta (Aβ) 42 and 40, phosphorylated Tau 181 (p-Tau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured using Quanterix Simoa immunoassays. Covariate-adjusted linear regression models estimated associations of sleep indices in 1996-98 with standardized plasma biomarker measurements in 1993-95 (3 years earlier) and in 2011-13 (15 years later). Covariate-adjusted linear mixed effects models quantified associations of sleep measures with the 5-year rates of change in standardized biomarker levels (1993-2013). Results: Compared to a habitual sleep duration of 8 hours or more, sleeping less than 7 hours per night was associated with higher NfL, a biomarker of neurodegeneration, 15 years later (β = 0.252; 95% confidence interval [CI]: 0.003, 0.501). Sleep indices were not associated with biomarker levels 3 years earlier. Counter to our hypothesis, Moderate/Severe OSA was associated with slower increases in p-Tau181 (β = -0.102; 95% CI: -0.198, -0.006), a biomarker of AD pathology, over a median of 17.9 years. Conclusions: Short habitual sleep duration may impact dementia outcomes through neurodegenerative and other processes rather than through pathways specific to AD pathology or neuroinflammation. Longitudinal studies with sleep measurements in larger, more diverse samples are needed to further distinguish the pathways linking sleep to dementia.

Abstract Purpose: Familial adenomatous polyposis (FAP) confers a significant risk of colorectal/duodenal cancer. Encapsulated rapamycin (eRapa) has demonstrated promise as FAP chemoprevention in early clinical studies. Patients and Methods: Thirty patients with FAP enrolled to three dosing regimens of eRapa (0.5 mg): cohort 1—every other day, cohort 2—daily every other week, or cohort 3—daily. The primary endpoints were safety/tolerability, pharmacokinetics, and percentage change from baseline (PCFB) in colorectal polyp burden (CPB) at 6 months. Secondary endpoints included PCFB total (TPB) and duodenal (DPB) polyp burden and change in International Society for Gastrointestinal Hereditary Tumors stage and Spigelman score at 6 and 12 months. Results: Twenty nine of thirty patients (97%) completed the 12-month study with predictable bioavailability. Low-grade adverse events were frequent but most pronounced in daily dosing. Two patients discontinued treatment related to toxicity. Cohort 1 had the largest decrease median PCFB CPB, DPB, and TPB at 6 months: −39.4 % (IQR, 108.9; P = 0.28), −33.33 % (IQR, 90; P = 0.04), and −38.6 % (IQR, 88.5; P = 0.26), respectively. At 12 months, cohort 2 had the largest decrease median PCFB CPB and TPB: −29.3 % (IQR, 67.6; P = 0.37) and −26.3 % (IQR, 49.5; P = 0.29), respectively. Intermittent dosing cohorts (1 and 2) reduced DPB at 6 months (P = 0.04) and improved TPB at 12 months (P = 0.05) compared with daily dosing. Conclusions: eRapa was safe, tolerable, and showed preliminary efficacy for FAP chemoprevention. The 0.5 mg daily every-other-week schedule will be evaluated in an upcoming phase III trial.

Importance Seizure-induced brain injury is central to the treatment urgency of new-onset refractory status epilepticus (NORSE). Identifying biomarkers that reflect ongoing neuronal damage could inform therapeutic timing and improve outcomes. Objective To quantify acute brain injury in patients with cryptogenic NORSE (cNORSE), etiology-defined status epilepticus (eSE), and chronic epilepsy. Design, Setting, and Participants This was an international cross-sectional study conducted between 2013 and 2025. Patients were enrolled at 36 hospitals in the US, 2 in Canada, and 1 in Italy, France, and Belgium. Patients with cNORSE and eSE for which biological samples were obtained during ongoing seizure activity were enrolled in the study. Comparison groups without status epilepticus comprised individuals with chronic epilepsy and healthy participants. None were excluded. Exposures Neurofilament light chain (NfL) and S100-beta (S100B) protein concentrations in serum and cerebrospinal fluid (CSF). Main Outcomes and Measures Degree of neuronal and glial damage, indexed by NfL and S100B levels, and their association with short-term functional outcomes. Results A total of 78 patients with cNORSE (mean [95% CI] age, 37 [30-41] years; 44 female [56%]) and 2 independent cohorts of 211 patients (mean [95% CI] age, 69 [66-71] years; 128 female [61%]) and 73 patients (mean [95% CI] age, 56 [45-65] years; 39 male [53%]) with eSE were included. NfL concentrations were markedly elevated in cNORSE—approximately 10-fold higher in CSF and 4-fold higher in serum—compared with the eSE cohorts (CSF: median [IQR], 6408 [1503-22 963] pg/mL compared with 694 [219-2389] pg/mL; serum: median [IQR], 231 [99-855] pg/mL compared with 55 [20-135] pg/mL; P &amp;lt;.001). Serum NfL levels were nearly 20-fold higher in cNORSE than in the cohort with epilepsy and in healthy controls (median [IQR], 11 [7-19 ] and 7 [5-14 ] pg/mL, respectively). Serum and CSF NfL levels were strongly correlated (Spearman ρ = 0.75; P &amp;lt; .001) and rose sharply between week 1 (median [IQR], 101 [51-137] pg/mL), week 2 (median [IQR], 197 [117-324] pg/mL), and week 3 (median [IQR], 598 [163-1000] pg/mL) after onset ( P &amp;lt; .001). In contrast, S100B concentrations did not differ between groups and showed no consistent temporal pattern. NfL discriminated cNORSE from eSE (area under the receiver operating characteristic curve [AUROC], 0.79; 95% CI, 0.68-0.90) and from cohorts without status epilepticus (AUROC, 0.99; 95% CI, 0.78-1.00). Higher serum NfL was independently associated with poor functional outcome at discharge (Glasgow Outcome Scale extended score, 1-4; odds ratio, 1.01; 95% CI, 1.00-1.03; P = .03). Conclusions and Relevance Results of this cross-sectional study suggest that acute neuroaxonal injury, as reflected by elevated NfL levels, was substantially greater in cNORSE than in the cohorts with eSE and in controls without status epilepticus. The rapid early rise in NfL highlights a narrow therapeutic window, emphasizing the need for prompt, effective, and potentially neuroprotective interventions in cNORSE.

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast

Importance Accurate prediction of patient mortality after kidney transplant is an unmet need. Objective To develop and validate an integrative prediction model that predicts short- and long-term patient mortality for kidney recipients. Design, Setting, and Participants This international cohort study included patients who underwent transplants between 2004 and 2023 from 14 academic medical centers from Europe and the US. The derivation cohort consisted of 1566 consecutive adult kidney recipients in a deeply phenotyped cohort prospectively recruited in 1 French center between 2004 and 2014. External validation cohorts consisted of 10 951 kidney recipients from 7 centers in France, 3 centers in Europe, and 3 centers in North America who underwent kidney transplants between 2006 and 2023. Data were analyzed from January 2023 to June 2025. Main Outcome and Measures All-cause mortality was assessed, and 121 candidate prognostic factors, comprising demographics and clinical, biological, imaging, and immunological parameters, were collected. Results Among 12 517 kidney transplant recipients, including 1566 in the derivation cohort (mean [SD] age, 50.05 [14.31] years; 942 male [60.15%]) and 10 951 in validation cohorts (mean [SD] age, 53.32 [13.97] years; 6766 male [61.78%]), 2486 patients (19.9%) died after a median (IQR) follow-up of 5.08 (2.97-7.00) years. Fourteen prognostic factors (including clinical, biological, and imaging risk factors) were independently associated with patient death (eg, patient age: hazard ratio per 1-year increase in age, 1.07 [95% CI, 1.06-1.08]; P &amp;lt; .001) and were combined into a risk prediction model (mBox). The model exhibited accurate calibration and discrimination in the derivation cohort, with C statistics of 0.82 (95% CI, 0.77-0.87) and 0.80 (95% CI, 0.78-0.82) at 1 and 10 years, respectively, after the transplant. Abbreviated models were developed and validated to ensure model generalizability. Performance of abbreviated models was confirmed in external validation cohorts from France (C statistic, 0.76 [95% CI, 0.73-0.78]), Europe (C statistic, 0.74 [95% CI, 0.72-0.76]), the US (C statistic, 0.74 [95% CI, 0.70-0.78]), the Greater Paris University Hospital database (C statistic, 0.79 [95% CI, 0.77-0.81]), and the University of California at San Francisco database (C statistic, 0.70 [95% CI, 0.65-0.74]). The model was also validated in a series of subpopulations (eg, women vs men: C statistic, 0.81 [95% CI, 0.77-0.84] vs 0.79 [95% CI, 0.77-0.82]) and clinical scenarios (eg, before COVID-19 era: C statistic, 0.79 [95% CI, 0.77-0.81]) with good and stable performance. Conclusions and Relevance In this study, an accurate prediction model for mortality among kidney recipients, computable at the time of transplant, was developed and externally validated. Results suggest that this model may help stratify patient risk of death, allowing for improved medical decisions.

ABSTRACT Background Retrospective evaluations of multidisciplinary team (MDT) review of pancreatic cystic lesions (PCL) demonstrate improved PCL management. Endoscopic ultrasound (EUS) evaluates PCL for worrisome features; however, its influence on MDT is unclear and may be attenuated by anchoring/confirmation bias. We aimed to evaluate the impact of EUS and the overall performance of MDT evaluation of PCL. Methods Four mock MDT sessions at two institutions were presented imaging from 40 consecutive PCL cases (20 “high‐risk” with advanced neoplasia, 20 “low‐risk” with pathologic low‐grade dysplasia or ≥ 3 years of non‐progression on surveillance), with and without upfront EUS/FNA (cytology, CEA, Amylase), in a randomized, crossover design. Group 1 adjudicated without EUS, Group 2 adjudicated with EUS, and Group 3 adjudicated with EUS after initially adjudicating without it. Results The cohort included branch‐duct ( n = 20), mixed type ( n = 6), and main duct ( n = 4) IPMN, MCN ( n = 5), and non‐mucinous PCL ( n = 5). Group 2 (EUS) correctly identified mucinous PCL with 97% sensitivity and 70% specificity, significantly higher than Group 1 (No EUS) (Sensitivity 91%, Specificity 20%; p = 0.04). Group 3 (Unblinded to EUS) performed significantly worse in mucinous PCL identification compared with Group 2, indicating cognitive bias (Sensitivity 97%, Specificity 10% ( p = 0.0003)). Group 2 correctly identified high‐risk PCL that required surgical intervention with 85% sensitivity and 85% specificity, significantly higher than Group 1 (Sensitivity 60%, Specificity 75%; p = 0.0016) and Group 3 (Sensitivity 73%, Specificity 80%, p = 0.0485). Conclusion While susceptible to cognitive bias, EUS significantly improves MDT assessment of PCL. MDT establishes a high bar for iterative additions of biomarkers to PCL analysis.