Citations

Abstract Categorical variants, or sets of genomic alterations constrained by shared properties, are pervasive across clinical, regulatory, and research domains in the biomedical ecosystem, yet their inconsistent and non-computable representation hinders data interoperability and clinical interpretation. We surveyed genomic knowledgebases spanning regulatory approvals and the biomedical literature and found that categorical variants underpin a substantial proportion of clinical genomics knowledge, but are largely described using incompatible bespoke models. To address this, we developed the GA4GH Categorical Variation Representation Specification (Cat-VRS), a constraint-based framework that provides a unified computable representation for both precise and intentionally broad categories across molecular and systemic variant domains. Cat-VRS enables harmonization of genomic knowledgebases, computable category-based search, and automated matching between assayed variants and categorical entities in clinical and research contexts. By providing a principled, extensible model for categorical variation, Cat-VRS enables computable reasoning over genomic variant categories and establishes a foundation for the standardized representation and exchange of genomic knowledge.

Abstract This publication represents the first part of an update to the clinical practice guideline on the diagnosis and management of group A streptococcal (GAS) pharyngitis, developed by the Infectious Diseases Society of America (IDSA). Diagnosis of GAS pharyngitis by clinician judgment alone is unreliable, and universal testing incurs cost and inconvenience for individuals at low risk of having GAS infection. Clinical scoring systems have been used to quantify the probability of a positive GAS throat culture based on standardized criteria such as the presence of fever, tonsillar enlargement or exudate, tender and enlarged anterior cervical lymph nodes, and the absence of cough. The goal of this manuscript is to review the evidence and provide a recommendation as to whether a scoring system should be used to decide which patients should have a GAS diagnostic test (ie, rapid antigen test [RADT], molecular method, and/or throat culture) performed. We performed a systematic review of randomized and nonrandomized studies that compared the use of a clinical scoring system to clinician judgment alone in predicting the result of a throat culture. Evidence from studies in children and adults suggests the diagnostic accuracy is comparable or slightly higher using a scoring system compared to clinician judgment alone. Although the studies are limited due to small size, lack of uniformity in outcome measures, and incomplete data, the consensus of the panel is that the balance of benefits and harms favors incorporation of a clinical scoring system as part of the evaluation of patients with sore throat and suspected GAS pharyngitis.

Abstract Patients at risk for progression from myeloid precursor states (idiopathic cytopenia of undetermined significance [ICUS] and clonal cytopenia of undetermined significance [CCUS]) to myelodysplastic syndrome (MDS) are not well defined. Epidemiologic risk factors, clonal changes for MDS development, and evolution from one MDS state to another were available in the MDS Natural History Study (NHS), a prospective cohort enrolled at diverse US sites. Extensive clinical data and biospecimens were collected at baseline and follow-up. A total of 1177 (56%) individuals with MDS or MDS-related precursor conditions (ICUS/idiopathic dysplasia of undetermined significance [IDUS], CCUS, and MDS/myeloproliferative neoplasm overlap) were enrolled and diagnosed in the MDS NHS. The median age was 74 years, with 89% aged ≥60 years, and most were male patients. Median follow-up time was 1.6 years and was similar among ICUS/IDUS, CCUS, and MDS. During follow-up period, 68% of participants terminated the study, 35% died, and 38% had disease progression. Using a refined clinical definition of progression, the greatest proportion of progression was observed among higher-risk-MDS (116 [73%]), followed by lower-risk-MDS (170 [52%]); fewer progression events were observed among participants with CCUS (65 [22%]) and ICUS/IDUS (46 [17%]). Predictors of progression are delineated, including female sex, higher quantity of mutations, the presence of TP53 mutation, and poor/very poor cytogenetic score. Based on these prospective data, guidelines for clinical management including monitoring and surveillance are outlined. The MDS NHS provides real-world data to illustrate how clinical and genotypic differences inform the classification, disease course, and approach to therapy, with informed monitoring guidelines for patients. This trial was registered at www.ClinicalTrials.gov as NCT02775383.

Background Measles remains a public health threat in the United States with over 50,000 cases being reported from 1989 through 1991 with continued smaller outbreaks. Measles vaccine failure is in part to blame for these large-scale outbreaks. The human leukocyte antigen (HLA) genes are important determinants of immune response to measles virus and vaccine. To examine the influence that HLA polymorphisms may have on measles vaccine antibody response, we compared the distribution of HLA-DRB1 alleles between measles vaccine nonresponders and hyper-responders. Methods We determined the seroprevalence of measles antibody in 881 school children immunized with measles-mumps-rubella-II at age 15 months using a whole virus IgG EIA. We performed class II HLA-DR typing by PCR with sequence specific primers (PCR-SSP) on 81 nonresponders (IgG seronegative) and 65 hyper-responders (from the upper 10th percentile of IgG levels of all subjects). We then compared the distribution of alleles between nonresponders and hyper-responders. Results The distribution of HLA-DRB1 alleles among nonresponders compared to hyper-responders was significantly different ( p = 0.014). Nonresponders were significantly less likely to carry the HLA-DRB1*13 alleles than were hyper-responders (7.4% vs 16.2%; p = 0.02). Nonresponders also had an excess of HLA-DRB1*07 alleles (15.4% vs 6.2%; p = 0.015). Conclusions The absence of HLA-DRB1*13 alleles is associated with measles vaccine nonresponse. The absence of this allele has also been associated with susceptibility to other infectious diseases. The role of this gene in the immunogenetic response to infectious diseases requires further study.

BACKGROUND AND OBJECTIVES: En bloc spondylectomies are essential for controlling malignant spinal tumors, but existing classification systems are often complex and impractical. This study introduces the Column, Line-of-Sight, Margins, Ring (CLiMR) framework, a novel system simplifying and standardizing en bloc spondylectomy planning and classification. METHODS: A retrospective review of patients who underwent single- or multistage en bloc spinal tumor resections was conducted at a single academic center (October 2019-December 2024). The CLiMR framework assigns scores to 4 components: Column (osteotomies/diskectomies for tumor release), Line-of-Sight (approach for circumferential access), Margin (adjacent structures sacrificed), and Ring (size of the vertebral ring window for safe delivery of neural tissue). Scores were applied using operative notes and imaging. RESULTS: Column scores ranged from 0.5 to 4.5. Of the patients included, 40.9% underwent sagittal split osteotomies, 22.7% radical diskectomies, 18.2% horizontal osteotomies, and the remaining 18.2% combinations of previous osteotomies . A posterior-only approach (Line-of-Sight score = 1) was used in 45.4% of cases, whereas 45.4% required a multistage approach (score = 2). Margin scores reflected increasing morbidity: 31.8% (n = 7) involving chest wall/pleura resection (grade 3), 40.9% (n = 9) requiring eloquent nerve sacrifice (grade 6), and 9.1% (n = 2) necessitating limb sacrifice (grade 7). The majority (86.4%, n = 19) of ring scores were grade 1, requiring laminectomies/facetectomies. The mean CLiMR score was 9.36 ± 2.43, with higher scores correlating with longer hospital stays (R = 0.64, P = .0012), longer case durations (R = 0.61, P = .0023), and increased blood loss (R = 0.40, P = .067). Patients with local recurrence, positive margins, or complications trended toward greater CLiMR scores. CONCLUSION: The CLiMR framework provides a novel, user-friendly method for planning and communicating en bloc spondylectomies. By addressing technical complexities and morbidity, CLiMR enables standardized assessment, facilitates surgical decision-making, and supports future research. This study demonstrates feasibility and lays the foundation for future validation studies.

Abstract Purpose SARS-CoV-2 infection continues to impact global health, particularly among high-risk vulnerable individuals. With the loss of federal funding for SARS-CoV-2 management, hospitals will need to budget appropriately for antivirals like remdesivir, which has demonstrated effectiveness in reducing mortality. We evaluated the economic impact realized by hospitals for patients hospitalized for SARS-CoV-2 infection and initiated on remdesivir therapy. Methods We conducted a retrospective analysis using data compiled in the Premier Healthcare Database from January 2023 to February 2024. Propensity score matching was used to compare remdesivir-treated (RDV) and untreated (No RDV) groups. The mortality rate, hazard ratios associated with remdesivir use, and hospitalization costs were assessed overall and among the elderly (age ≥65 years). We also conducted a cost-effectiveness analysis to assess the economic value of remdesivir treatment. Results Among 25,498 hospitalized patients, the mortality rate in the RDV group was lower than in the No RDV group (6.2% versus 8.1%), with a greater reduction in the elderly (6.9% versus 9.0%). Remdesivir significantly reduced mortality risk by approximately 25% overall and among the elderly. Each life saved was realized at a minimal increase in average hospitalization costs ($18,329 in the RDV group versus $14,845 in the No RDV group). Remdesivir was a cost-effective treatment option at a willingness-to-pay threshold of $25,000 overall and among the elderly. Conclusions Our evaluation provides contemporaneous evidence of benefits and costs associated with management of individuals hospitalized for SARS-CoV-2 infection. Initiation of remdesivir was associated with minimal incremental hospitalization costs for lives saved as compared to not initiating remdesivir. Hospital pharmacy leadership can utilize this real-world evidence to appropriately budget for remdesivir treatment.

Abstract Sinonasal squamous cell carcinoma (SNSCC) is an aggressive head and neck cancer of the sinonasal cavity which has not benefitted from therapeutic advances over decades 1 . Though historically attributed to inhaled carcinogens such as hardwood dust and tobacco smoking 2 , SNSCC is incidentally associated with human papillomavirus (HPV) 3,4 . Importantly, HPV is the primary oncogenic driver of >80% of anatomically adjacent oropharyngeal cancers 5 . While viral status drives clinical staging and treatment guidelines in these malignancies 6,7 , the potentially oncogenic consequences and prognostic value of host–virus interactions in SNSCC remain incompletely defined. Here, through paired host and viral whole-genome sequencing (WGS), we map the genomic footprint of HPV in SNSCC. Strikingly, lesser studied strains such as HPV45, 51, and 39 constitute driver infections in this rare but clinically credentialed cancer, where extrachromosomal DNA (ecDNA)-associated viral integration and APOBEC mutagenesis are shown to underpin somatic tumor evolution. Statement of Significance Paired host viral and whole-genome sequencing of SNSCC nominates HPV as a primary oncogenic driver of SNSCC. HPV–human ecDNA amplicons harboring noncanonical strains such as HPV45, 51 mediate viral carcinogenesis. Routine clinical diagnostic HPV panels should be expanded to capture the activity of lesser studied strains.

Background: Aggressive non-Hodgkin lymphoma (aNHL) commonly occurs in older adults. However, geriatric assessments (GAs), which are associated with both survival and treatment-related toxicity, are infrequently performed due to logistical constraints. In this study, we examined how the brief, self-reported Vulnerable Elders Survey-13 (VES-13) screening tool and a comprehensive GA relate to clinical outcomes in this population. Methods: We conducted a longitudinal study of 105 adults aged ≥65 years who were initiating upfront chemoimmunotherapy for aNHL at 2 academic medical centers and their community affiliates between September 2020 and January 2023. Baseline frailty was evaluated using the Fondazione Italiana Linfomi (FIL) GA, which classifies patients as fit, unfit, or frail. The VES-13 was assessed both continuously and by categorizing patients as vulnerable (score ≥3). Using logistic regression controlling for covariates, we examined the association of VES-13 with grade ≥3 nonhematologic toxicity (toxicity), unplanned hospitalization within 6 months of treatment initiation, decline in quality of life (QoL) 1 year after therapy initiation, and death within 1 year of treatment initiation. In addition, we calculated the sensitivity and specificity of both the VES-13 and the FIL GA in identifying patients at risk for these outcomes. Results: The median patient age was 73 years (range, 64–99 years), with 42% aged ≥75 years. GA classified 40% of patients as fit, 10% as unfit, and 51% as frail, while 46% of patients had a VES-13 score ≥3, indicating vulnerability. VES-13 score was significantly associated with toxicity (odds ratio [OR], 1.18; P =.026), unplanned hospitalization (OR, 1.16; P =.043), QoL decline at 1 year (OR, 1.22; P =.027), and death within 1 year (OR, 1.49; P =.010). Using the VES-13 to define vulnerability (score ≥3), sensitivity and specificity were 59% and 61% for predicting toxicity, and 100% and 59% for predicting death within 1 year, respectively. FIL GA frailty had a sensitivity of 63% and specificity of 56% for predicting toxicity, and 100% sensitivity and 54% specificity for predicting death within 1 year. Conclusions: We found that VES-13 score was associated with survival, toxicity, health care utilization, and QoL decline, demonstrating similar sensitivity and specificity to the FIL GA. These findings underscore the potential utility of VES-13 as a screening instrument to identify older patients with aNHL at risk for adverse clinical outcomes.

Abstract Generative artificial intelligence (AI) is rapidly populating medical records with synthetic or partially AI-generated content, creating a feedback loop where future models are increasingly at risk of training on uncurated AI-generated data. However, the clinical consequences of this AI-generated data contamination remain unexplored. Here, we show that in the absence of mandatory human verification, this self-referential cycle drives a rapid erosion of pathological variability and diagnostic reliability of medical data at population scale. By analysing more than 800,000 synthetic data points across clinical text generation, vision–language reporting, and medical image synthesis, we find that models progressively converge toward generic phenotypes regardless of the model architectures. Specifically, rare but critical findings, including pneumothorax and effusions, vanish from the synthetic content generated by AI models, while demographic representations skew heavily toward middle-aged male phenotypes. Crucially, this degradation is masked by false diagnostic confidence. Models continue to issue reassuring reports while failing to detect life-threatening pathology, with false reassurance rates tripling to 40%. Blinded physician evaluation confirms that this decoupling of confidence and accuracy renders AI-generated documentation clinically useless after just two generations. We systematically evaluate three mitigation strategies that can be easily integrated into existing clinical workflows, finding that while synthetic volume scaling fails to prevent collapse, mixing real data with quality-aware filtering effectively preserves diversity. Ultimately, our results suggest that without policy-mandated human oversight, the deployment of generative AI threatens to degrade the very healthcare data ecosystems it relies upon.