Citations

PURPOSE For patients with breast cancer undergoing breast conservation, escalating the dose (boost) of radiation to the lumpectomy cavity after whole-breast irradiation (WBI) reduces ipsilateral breast recurrence (IBR) but extends treatment duration. This phase III trial investigated whether boost delivery during WBI versus after WBI provides noninferior IBR and preserves cosmetic appearance. METHODS NRG/RTOG 1005 randomly assigned patients at higher risk for IBR after lumpectomy and axillary surgery to either a sequential boost of 12 Gy in six fractions(F) or 14 Gy in 7F after WBI of 50 Gy in 25F or 42.7 Gy in 16F (sequential arm) or a concurrent boost of 8 Gy in 15F of 0.53 Gy per day with WBI of 40 Gy in 15F (concurrent arm) using 3-dimensional conformal radiation therapy (RT) or intensity-modulated RT. Based on 1.59% 5-year IBR for the sequential arm, defining the noninferiority margin as a hazard ratio upper limit on the 90% CI of 2.12, 2,312 patients provide 80% power for noninferiority of IBR as first recurrence for the concurrent arm. Secondary end points included disease-free survival and overall survival, adverse events (AEs), and cosmetic outcomes. RESULTS Between May 24, 2011, and June 20, 2014, 2,354 patients were randomly assigned, with 2,255 eligible for analysis (sequential arm, n = 1,118; concurrent arm, n = 1,137). With median follow-up of 7.3 years, there were 56 IBR events; 5- and 7-year IBR were 2.1% and 2.2% on the sequential arm and 1.9% and 2.6% on the concurrent arm, respectively. The noninferiority criterion was met: HR (90% CI): 1.31 (0.84 to 2.04), P = .037. No differences were observed in AEs, cosmetic outcomes, or survival between arms. CONCLUSION Concurrent boost during WBI results in noninferior IBR compared with sequential boost without worsening toxicity or cosmetic outcomes and reduces overall treatment time.

Autoimmune diseases arise when B and T lymphocytes lose tolerance to self. Yet in most disorders, the underlying molecular determinants, including autoantibodies, epitopes and lymphocyte clones that drive tissue injury remain undefined. Rapid-onset obesity with hypothalamic dysfunction, hypoventilation and autonomic dysregulation (ROHHAD) is a rare and often fatal pediatric neuroendocrine syndrome with strong evidence of antigen-driven paraneoplastic autoimmunity, including association with the intracellular autoantigen ZSCAN1. However, the effector immune circuit and the epitope-level determinants operating within the hypothalamus and brainstem have remained unknown. To address this challenge in ROHHAD and more broadly in autoimmune disease, we developed the Autoimmune Epitope and immunoGlobulin/Immune-receptor identification System (AEGIS), an integrated framework that links immune repertoires to their cognate self-epitopes. AEGIS combines B cell and T cell receptor profiling from sites of tissue injury with high-resolution epitope mapping, direct sequencing of antigen-specific autoantibodies, in silico antibody-antigen folding, selection, and T cell antigen discovery. Applied to a deeply phenotyped child with ROHHAD, AEGIS revealed a compartmentalized, clonally restricted immune response in which brain-deposited IgG and expanded cerebrospinal fluid B cell and CD4 T cell clonotypes converged on shared ZSCAN1 epitopes, resolved to minimal determinants and peptide-MHC ligands. These findings provide a clone- and epitope-linked mechanistic map of ROHHAD autoimmunity and establish a generalizable framework for identifying candidate pathogenic clones and antigens across diverse autoimmune diseases.

Importance Current risk prediction guidelines for hypertrophic cardiomyopathy predict only sudden cardiac death and are imperfect, leading to avoidable deaths and unnecessary implantable cardioverter defibrillators. Objective To combine prospectively collected clinical history, imaging, genetic, and biomarker data to improve risk prediction of adverse events in hypertrophic cardiomyopathy. Design, Setting, and Participants A total of 2750 patients with hypertrophic cardiomyopathy were prospectively enrolled in the registry-based study from 44 sites in North America and Europe with expertise in hypertrophic cardiomyopathy and cardiac magnetic resonance (CMR) imaging. Participants were enrolled from April 1, 2014, to April 7, 2017. Exposures Patients underwent a health history questionnaire, blood sampling for biomarkers and genotyping, and contrast-enhanced CMR. Patients were followed up yearly by telephone and through records review regarding event documentation. Main Outcomes and Measures The predefined composite adjudicated primary end point was time to first event for hypertrophic cardiomyopathy–related deaths; nonfatal sustained ventricular arrhythmias (VAs) requiring cardioversion or defibrillation; and left ventricular (LV) assist device implant or heart transplant. A secondary end point was a composite of sudden cardiac death and nonfatal VA events. The elastic-net method identified the most important predictors. Cox proportional hazards regression assessed associations with time to the first end point. Results Of the 2750 prospectively enrolled patients, 2698 (98%) had analyzable data after 9 were excluded because they had hypertrophic cardiomyopathy phenocopies and 43 withdrew. Of these remaining patients, 1919 (71%) were male, mean age was 50 years (SD, 11 years), and 423 (16%) were from underrepresented racial and minority groups. The mean follow-up was 6.9 years (SD, 2.1 years). The primary event model in 104 patients included LV scar as a percentage of LV mass by late gadolinium enhancement (LGE%; hazard ratio [HR], 1.86; 95% CI, 1.58-2.20; P < .001), LV mass index (HR, 1.09; 95% CI, 1.01-1.17; P = .03), LV end-systolic volume index (HR, 1.28; 95% CI, 1.12-1.46; P < .001 ), all per 10-unit increase, history of heart failure at study entry (HR, 2.89; 95% CI, 1.75-4.77; P < .001), and log N-terminal pro–B-type natriuretic peptide (NT-proBNP; HR, 1.41; 95% CI, 1.17-1.70; P < .001) level per log unit, (C index for all, 0.77). An LGE percentage of the LV mass of 9% or higher substantially increased the primary composite event rate ( P = .001). The secondary sudden cardiac death and VA risk factor model (in 69 patients) included LGE%, LV mass index, LV ejection fraction, and log(NT-proBNP) (C index, 0.76). Conclusions and Relevance These results provide prospective evidence for incorporating cardiac magnetic resonance and NT-proBNP in the evaluation of patients with hypertrophic cardiomyopathy. Trial Registration ClinicalTrials.gov Identifier: NCT01915615

OBJECTIVE Protocols for intraoperative mapping during awake craniotomy vary widely. The aim of this study was to evaluate how the number and type of intraoperative neuropsychological paradigms administered via NeuroMapper, a tablet-based platform, during awake glioma surgery affect positive mapping rates, return to work (RTW), and oncological outcomes. Factors associated with the operative duration and early postoperative neurological deficits were of additional interest. METHODS This single-center retrospective study included patients with diffuse low- and high-grade gliomas who underwent awake craniotomy with NeuroMapper-guided mapping between 2018 and 2024. Primary outcomes were RTW, progression-free survival (PFS), and overall survival (OS); operative duration and early postoperative deficits were secondary outcomes. Covariate balancing propensity score (CBPS) analysis was used to address confounding by tumor grade, with all postweighting standardized mean differences < 0.10. A weighted logistic regression model assessed RTW, and CBPS-weighted Cox models assessed PFS and OS. Linear regression was used to analyze intraoperative variables, operative duration, and early postoperative deficits. RESULTS Of 189 patients included in the analysis, 65 had LGG (median age 39 years) and 124 had HGG (median age 56 years). Mapping complexity varied, with 1–6 tasks used (median 4). Weighted multivariate logistic regression analysis identified the following independent predictors of RTW: preoperative Karnofsky Performance Status score ≥ 80 (OR 1.37, p = 0.039), absence of recurrent disease (OR 0.30, p < 0.001), use of 5–6 paradigms (OR 1.54, p = 0.047), positive mapping (OR 2.41, p = 0.017), and subtotal resection (OR 4.43, p = 0.002). Intraoperative seizure, early postoperative deficit, and the resection technique were not significant. IDH mutation status was associated with improved PFS (HR 0.15, p < 0.001), while subtotal resection was associated with worsened PFS (HR 3.00, p < 0.001). Positive mapping was associated with better OS (HR 0.57, p = 0.04). The operative duration was unaffected by mapping variables but was longer in patients with obesity (β = 0.28, p = 0.038). CONCLUSIONS Positive NeuroMapper-guided mapping of more diverse linguistic functions was associated with RTW and longer OS. Additionally, mapping complexity did not prolong surgery times, supporting potential standardization.

Background: Gender-based reimbursement disparities in orthopedic surgery remain poorly understood, particularly when accounting for practice composition and setting. The purpose of this study was to compare and evaluate gender-based differences in Medicare reimbursement and practice patterns among female and male orthopedic surgeons. Methods: A cross sectional analysis of public Medicare data from 2013 to 2021 was performed. Outcomes included annual Medicare payments, submitted charges, total services, service categories, and beneficiaries treated by orthopedic surgeons who bill Medicare. Univariate and multivariable analyses quantified differences in payment, practice volume and composition, geographic adjustment, and Current Procedural Terminology (CPT)-matched reimbursements. Results: A total of 29,357 orthopedic surgeons (27,442 men and 1,919 women) billed Medicare fee-for-service during the study period. Female surgeons, on average, submitted 48.3% fewer total charges and received 44.1% lower annual Medicare payments per surgeon compared with male surgeons. These differences persisted after multivariable regression adjusted for practice metrics and excluded top and bottom earners. Female surgeons also billed fewer services, treated fewer beneficiaries, and submitted fewer unique CPT codes. However, payment disparities persisted even after matching surgeons by volume of services, beneficiaries, and years in practice. Male surgeons performed higher volumes of all 10 highest-paying orthopedic CPT codes. In CPT matched analyses, female surgeons received lower reimbursement per service than male surgeons performing identical procedures. Conclusion: These findings suggest that the observed gender-based disparities in orthopedic surgery Medicare reimbursement cannot be explained by differences in volume, procedural mix, or geographic practice cost. Instead, they likely reflect a combination of structural and behavioral mechanisms described in prior literature that may influence how access to clinical opportunities, referrals, and reimbursement practices unfold in surgical practices. Variations in coding practices may represent an important focus for future investigation and targeted educational initiatives. Level of Evidence: Level III , Retrospective Cohort Study. See Instructions for Authors for a complete description of levels of evidence.

Abstract Both the phase 3 MAIA and ALCYONE studies demonstrated significant survival benefit with the addition of daratumumab to standard-of-care Rd (Revlimid [lenalidomide] and dexamethasone; D-Rd) or to VMP (Velcade [bortezomib], melphalan, and prednisone; D-VMP), respectively, vs Rd or VMP alone in transplant-ineligible newly diagnosed multiple myeloma (NDMM). Patients with NDMM are highly susceptible to infection; therefore, gaining a greater understanding of infection incidence may help to mitigate future risk. We conducted a pooled analysis of infection incidence, timing, and management strategies from MAIA and ALCYONE. The median (range) age of the pooled population was 72 (40-93) years. Incidence was higher with D-Rd/D-VMP vs Rd/VMP for grade 3/4 (36.9% vs 22.4%) and grade 5 (3.0% vs 1.5%) infections; however, exposure-adjusted incidence rates were generally comparable between groups. Any-grade infections led to the discontinuation of study treatment in ∼2% of patients across treatment groups. Of the timing intervals explored, the highest incidence of grade 3/4 infection occurred within the first 6-month interval of study treatment initiation in both groups. Median time to the first onset of grade 3/4 infections (per Kaplan-Meier estimates) was 83.3 months and not estimable in the D-Rd/D-VMP and Rd/VMP groups, respectively. Although the rates of D-Rd/D-VMP treatment discontinuation due to infection remained low in MAIA and ALCYONE, clinicians should remain vigilant about infections throughout treatment and follow local guidelines and International Myeloma Working Group recommendations to minimize the risk of infection. These trials were registered at www.ClinicalTrials.gov as NCT02252172 (MAIA) and NCT02195479 (ALCYONE).

PURPOSE Most oncology trials define superiority according to dichotomized P value thresholds, which are frequently misinterpreted. Posterior probability, however, directly estimates the probability of the hypothesis at hand. Here, we reanalyze a large collection of modern phase III trials and benchmark posterior probability versus the standard trial interpretation based on statistical significance. METHODS Outcomes from 194,129 patients were manually reconstructed from the primary end points of 230 phase III, superiority-design oncology trials. Posterior probabilities of treatment effect were then calculated across multiple priors and several effect sizes of clinical relevance, including minimum clinically important difference (MCID) defined as hazard ratio (HR) < 0.8 per ASCO criteria or HR < 0.64 per European Society of Medical Oncology (ESMO) criteria. RESULTS All trials interpreted as superior using P value thresholds had probabilities >90% for achieving at least marginal benefits (HR < 1). However, only 62% of positive trials (74/120) had >90% probabilities of achieving the ASCO MCID (HR < 0.8), even under an enthusiastic prior, including 70% of trials (57/82) leading to regulatory approval. Only 30% of positive trials (36/120) had >90% probability of achieving the ESMO MCID (HR < 0.64). Conversely, 24% of trials (26/110) interpreted as not superior had >90% probability of achieving marginal benefits (HR < 1), even under a skeptical prior. CONCLUSION Bayesian models, although often in agreement with statistical significance thresholds, add considerable unique interpretative value for a subset of phase III oncology trials. Posterior probability may provide a solution for overcoming the discrepancies between refuting the null hypothesis and detecting clinically relevant effects.

Retrieval-augmented generation (RAG) is rapidly emerging as a transformative paradigm for large language models (LLMs), especially in high-stakes domains like oncology that demand precision, factual grounding, and up-to-date knowledge. By pairing LLMs with external knowledge repositories, RAG systems explicitly ground model outputs in relevant retrieved documents, helping to reduce hallucinations and ensure responses reflect current evidence. In oncology, where clinical knowledge evolves continually with new research and drug approvals, RAG offers a way to integrate the latest data (e.g., trial results, guidelines, genomic databases) into decision-making. This review synthesizes the technical foundations of RAG, including its architecture and key components, and examines current applications in oncology such as clinical decision support, patient education, radiology reporting, pathology analysis, and genomics-driven precision medicine. We highlight recent studies that demonstrate RAG’s potential—for instance, improving treatment recommendations by incorporating genetic profiles and literature, and enhancing diagnostic accuracy by integrating guidelines. We also discuss emerging developments like multimodal RAG (combining text with imaging or other data), ensemble model approaches, and new explainability tools that trace model outputs to sources. Finally, we critically analyze the limitations and challenges of deploying RAG in healthcare, including computational costs, retrieval errors, noise or conflicts in retrieved information, and ethical and regulatory considerations. While RAG-based systems show promise in augmenting oncologists’ expertise with timely knowledge, careful implementation, high-quality curation of knowledge bases, and human oversight will be crucial for safe and effective adoption in clinical practice.

Abstract Additive manufacturing (AM), commonly referred to as 3D printing, has been broadly used in the field of medical imaging and radiotherapy. In medical imaging applications, patient‐specific anatomic models have been used to aid in preoperative planning, patient communication, imaging technique assessment and optimization, and medical education. Within the field of radiation therapy, 3D printing finds significance in fabricating patient‐specific immobilization devices, custom bolus devices, anthropomorphic phantoms, brachytherapy devices, and electron therapy devices. Consistent with standard medical physics practices there is a need to establish quality assurance and quality control (QA/QC) protocols, tolerances, and testing frequencies. The diversity of 3D printing technologies and products poses challenges for medical adoption and thus requires guidelines in workflow standardization and establishment of testing procedures. This report is centered around providing comprehensive vendor‐neutral implementation guidelines and recommendations for QC and QA processes. The scope of this report encompasses diverse requirements within medical imaging and radiation therapy settings, serving both clinical and research purposes. Brief overview of 3D printing technology, common materials, and potential clinical applications is provided. QA team, infrastructure, measurement techniques and challenges are discussed. QA processes for each step in 3D printing are discussed in great detail and baseline and action limits are recommended. This report also touched on regulatory considerations. Key recommendations are summarized at the end of the report.

Background Failure of conventional imaging to detect pancreatic ductal adenocarcinoma (PDA) at its visually occult pre-diagnostic stage is a primary barrier to improving its otherwise poor rate of survival. Objective To develop and validate the Radiomics-based Early Detection MODel (REDMOD), an AI framework to identify subvisual radiomic signatures of pre-diagnostic PDA on standard-of-care CT. Designs REDMOD was trained on a multi-institutional cohort (n=969; 156 pre-diagnostic, 813 control) and tested on an independent set (n=493; 63 pre-diagnostic, 430 control), simulating a low prevalence (~1:6) early detection paradigm. The fully automated framework couples AI-driven segmentation with a heterogeneous ensemble architecture trained on a 40-feature radiomic signature derived from Synthetic Minority Over-sampling Technique (SMOTE)-balanced data. A tunable Youden Index-optimised classification threshold enables performance calibration without retraining. Validation included direct comparison with radiologists, longitudinal test–retest analysis and external specificity validation across two independent cohorts (n=539 and n=80). Results On an independent test set (n=493), REDMOD identified occult PDA (AUC 0.82; 73.0% sensitivity) at a median 475-day lead time. This represented nearly twofold higher sensitivity than radiologists (38.9%; p<0.001), which grew to nearly threefold (68.0% vs 23.0%) at >24 months lead time. REDMOD showed strong longitudinal stability (90–92% concordance) and generalisable specificity across multi-institutional (81.3%; n=539) and public (87.5%; n=80) datasets. Mechanistic analyses confirmed predictive power derived principally from multi-scale wavelet-filtered textural features (90% of selected signature), which outperformed unfiltered features (AUC 0.82 vs 0.74; p=0.007) in capturing subvisual architectural disruptions. Conclusions REDMOD is an automated, mechanistically grounded, longitudinally stable, externally validated AI that surpasses radiologists for PDA detection at its visually occult pre-diagnostic stage. These attributes position it for prospective validation in high-risk cohorts, a necessary step towards shifting the paradigm from late-stage symptomatic diagnosis to proactive pre-clinical interception.