Citations

Context.— The US Food and Drug Administration (FDA) Emergency Use Authorization (EUA) for SARS-CoV-2 assays encompassed both in vitro diagnostic and laboratory-developed tests. Related testing data and documents from EUAs were published on the FDA website as PDF files, constituting a rich data resource. Objective.— To highlight the value of structured descriptive and validation data and provide recommendations on improving the quality, accessibility, and shareability of the FDA’s digital resources. Design.— SARS-CoV-2 diagnostics EUAs and related files were acquired from the FDA, and data were extracted through an iterative manual or automated process with quality assurance in accordance with a set of data entry definitions to generate a data product (ie, data analysis and presentation of data into tables, graphs, and reports, optionally including different data sets) that could be disseminated. Results.— Four challenges limited the usability of FDA EUA data, including (1) distinguishing EUA tests owing to similar names or inconsistent naming conventions; (2) document location and tracking owing to inconsistent EUA document identifiers, resource locators, and versioning; (3) data location and retrieval owing to heterogeneous structure and data formatting within EUA documentation; and (4) maintenance of existing data owing to lack of clear and traceable communication around EUA amendments. Conclusions.— Converging efforts from disparate groups to extract and synthesize FDA test data reveal an unaddressed need for better organization and communication. Existing FDA data reporting systems must be improved and adapted for the demands of the connected data science era.

Abstract Over 50% of older adults in the US take ≥5 medications, with prevalence reaching 76.8% in the emergency department (ED) setting. However, little is known about their medication self-efficacy (the ability to understand and follow medication regimens), which may influence adherence and adverse drug events when new prescriptions are added during ED visits. Our objective was to determine whether polypharmacy and potentially inappropriate medication (PIM) are associated with self-efficacy. We performed a logistic regression analysis using 5-site multicenter ED survey data linked to electronic health records from patients aged ≥65 years with baseline ED visits during 2019-2021. The predictors were polypharmacy (≥5 medications) and PIM use (≥1 high-risk medication, GEMRx criteria) of prescriptions taken within 1 year of the ED visit. The outcome was low medication self-efficacy (< 11 points MUSE-taking score) assessed at the ED visit. Covariates included insurance, education, marital status, race/ethnicity, caregiver support, dementia status, and frailty. Among 921 patients, 249 (27.0%) had polypharmacy and 66 (7.2%) had PIM use. Low medication self-efficacy was reported by 76 (37.8%) with polypharmacy and 26 (12.9%) with PIM use versus 125 (62.2%) and 40 (5.6%) without. Both polypharmacy (aOR 6.12, 95% CI 2.05-18.22, p = 0.001) and PIM use (aOR 33.65, 95% CI 5.81-214.35, p < 0.001) were associated with greater adjusted odds of low medication self-efficacy. Frailty modified this association, with weaker effects in more frail patients (OR 5.51, 95% CI 2.57-11.8, p = 0.003). These findings suggest that the ED is an important setting to identify older adults who may struggle with medication use.

This economic evaluation estimates the implementation costs and cost per additional patient receiving the vaccine associated with each of the intervention strategies for increasing rates of human papillomavirus (HPV) vaccination in primary care practices.

Importance Primary mitral regurgitation (MR) is a prevalent valvular lesion. Current American College of Cardiology/American Heart Association guidelines include class I recommendations for intervention for severe primary MR at the onset of symptoms, significant left ventricular (LV) enlargement (end-systolic dimension ≥40 mm), or dysfunction (ejection fraction ≤60%), with a class IIA recommendation for mitral valve repair when performed at an experienced surgical center. Recent data suggest a survival penalty when waiting for class I surgical guideline indications, and novel markers of decompensation are under investigation. Observations Comprehensive assessment of MR severity using echocardiography is critical, and when warranted, cardiac magnetic resonance (CMR) is complementary. Assessment of LV size and function, as well as serial changes in both, is crucial for determining timing of surgery. New-onset atrial fibrillation, left atrial enlargement, pulmonary hypertension, and exercise-induced changes in LV function should also be considered in borderline scenarios. The roles of LV volumes, global longitudinal strain, CMR-derived measures of myocardial dysfunction, and cardiac biomarkers are worthy of further investigation regarding consideration for early surgical intervention. Conclusions and Relevance A more refined approach incorporating assessment of extravalvular cardiac injury, novel imaging markers, and biomarkers is needed to optimize surgical timing in primary MR. Further research is warranted to validate these emerging parameters and refine guidelines to improve patient outcomes.

Abstract Background To determine if dose escalation improves outcomes for chondrosarcomas (CHS) of the base of the skull (BOS) and the cervical spine (CS). Methods A prospective, randomized, dose-escalation trial was designed for patients with CHS of the BOS and CS. Patients were randomly assigned to 70 Gy (RBE) or 76 Gy (RBE). The primary endpoint was local failure (LF). Secondary endpoints included overall survival (OS), cancer-specific survival (CSS), progression-free survival (PFS), and treatment-related toxicities. Results Between 1987 and 2007, 105 patients were randomized, median follow-up was 29.2 years (IQR, 26.7-32.4). Forty-six patients were assigned to 70 Gy (RBE) and 59 were assigned to 76 Gy (RBE). LF at 5-, 10-, and 20 years were 7%, 9%, and 11% for 70 Gy (RBE), and 10%, 15%, and 19% for 76 Gy (RBE) (P = .16). Like LF rates, there was no benefit in dose escalation for OS (P = .28) and CSS (P = .22). Progression-free survival at 5-, 10-, and 20 years was 93%, 89%, and 77% for the low-dose group and 83%, 71%, and 59% for the high-dose group (P = .069). Late RT injury ≥ grade 3 was reported in a total of 19 (18%) patients across both dose levels, with 11% in the low-dose group and 24% in the high-dose group (P = .13). Conclusions This is the first and largest trial of patients with grade I/II BOS and CS CHS evaluating dose escalation for tumor control. Proton-based RT is effective and safe for these tumors, but there is no apparent benefit in dose escalation. Clinical Trial Information NCT00592748.

Abstract Valvular heart disease represents a significant global health burden, with an estimated prevalence of 2.5% in high-income countries and projected increases due to population ageing. Randomized controlled trials in valvular heart disease have undergone substantial evolution, shifting from mortality-focused endpoints toward comprehensive assessments integrating imaging parameters and patient-centered outcomes. Cardiovascular imaging modalities, including echocardiography, cardiac computed tomography, and cardiac magnetic resonance, have become pivotal in trial design, patient selection, and endpoint definition. Recent landmark trials in aortic stenosis, including EARLY-TAVR and EVOLVED, have challenged traditional symptom-based intervention thresholds by incorporating imaging biomarkers of subclinical myocardial dysfunction and cardiac damage staging. In aortic regurgitation, the paucity of randomized controlled trials evidence contrasts with emerging transcatheter technologies, highlighting critical knowledge gaps. Mitral regurgitation trials have demonstrated the importance of patient phenotyping, with divergent outcomes between COAPT and MITRA-FR emphasizing the role of imaging in optimal patient selection. The recent TRILUMINATE and TRISCEND trials have transformed tricuspid regurgitation management through transcatheter interventions, prioritizing quality-of-life improvements alongside traditional clinical endpoints. Future directions include standardization of imaging protocols across modalities, development of artificial intelligence-enhanced analysis, and integration of multiparametric biomarkers for personalized risk stratification. The paradigm shift toward imaging-guided, patient-centered trial design represents a fundamental reimagining of therapeutic success in valvular heart disease, moving beyond procedural outcomes toward comprehensive assessment of clinical benefit and improved patient care.

Abstract Background: TP53-mutated myeloid neoplasms (MNs) represent one of the most lethal subgroups of blood cancers. The World Health Organization (WHO-5) recognize TP53-mutated (TP53mut) myelodysplastic syndrome (MDS) and International Consensus Classification (ICC) recognize TP53mut MDS and acute myeloid leukaemia (AML) as distinct disease entities, acknowledging their dismal prognosis and the urgent need for novel therapeutic strategies. However, key discrepancies exist between the classifications, creating uncertainty in diagnosis, influencing therapeutic decisions, and complicating clinical trial enrolment for patients with uniformly poor survival. Importantly, neither classifications included TP53-mutated myelofibrosis (MF), other myeloproliferative neoplasms (MPN), and MDS/MPN overlap syndromes, despite growing evidence that these cases carry similar adverse outcomes. To address these critical gaps, we conducted a comprehensive analysis across the full spectrum of TP53-mutated MN. Methods: We included TP53mut cases with variant allele frequency (VAF ≥2%) of AML, MDS, MDS/MPN overlap, myelofibrosis and other MPN managed at the Mayo clinic (Rochester, USA) and Local Health Network in South Australia (Australia). Cases were classified according to the revised 4th edition WHO classification (WHO-4R). Biallelic TP53 loss was defined as: (i) ≥2 mutations with VAF ≥2%; (ii) single TP53mut with VAF ≥2% plus 17p loss on karyotype, FISH, or SNP array; or (iii) single TP53mut with VAF ≥50% with or without 17p loss. Monoallelic loss was defined as a single TP53mut with VAF <50% without 17p loss or copy neutral loss of heterozygosity. The primary endpoint was overall survival (OS) from diagnosis, censored at allogeneic transplantation. Conditional inference tree analysis was performed to define the effect of individual predictors on OS. Results: We identified 853 TP53mutMN cases including WHO-4R-defined AML (BM/PB blasts ≥20%, n=314; 36.8%), MDS with excess blasts-2 (EB-2; BM 10–19% or PB 5–19%, n=129; 15.1%), MDS-EB-1 (BM 5–9% or PB 2–4%, n=100; 11.7%), and MDS with low blasts (LB; BM <5% and PB <1%, n=228; 26.7%). MF included chronic phase (MF-CP, n=48; 5.6%), accelerated phase (MF-AP, n=7; 0.8%), and blast phase (MF-BP, n=17; 2.0%). Additional cases comprised other MPN-chronic phase (n=3, 0.4%) and MDS/MPN overlap syndromes (n=7, 0.8%). Of 848 evaluable TP53mut MN, 616 (72.6%) harbored biallelic TP53 loss and 232 (27.4%) had monoallelic loss, with 42.4% (n=98) of monoallelic cases harboring a complex karyotype (CK). Biallelic loss was highly prevalent in AML (83.1%), MDS (70.4%), and MDS/MPN overlap (71.4%), but was less frequent in cases with MPN (33.3%) and MF-chronic phase (25.0%). Across the spectrum, the frequency of biallelic loss increased stepwise with disease progression, rising from MDS-LB (62.8%) to MDS-EB1 (76.0%), MDS-EB2 (79.5%), AML (83.1%), and MF-AP/BP (79.2%) (P<0.0001). In multivariable analysis, WHO-4R category, TP53mut VAF, biallelic loss and CK were independent predictors of poor survival in TP53mut MN. Conditional inference tree analysis stratified the cohort into seven prognostic groups with distinct median OS: (1) AML, MF-BP/AP, and MDS/MPN overlap regardless of mono/biallelic and CK status (n=335, 39.7%; median OS 4.0 months); (2) MDS-EB1/EB2 with biallelic loss or monoallelic plus CK (n=212, 25.1%; 7.2 months); (3) MDS-LB, MF-CP and MPN with CK (n=156, 18.5%, OS 10.2 months); (4) biallelic MDS-LB (n=28, 3.3%; OS 15.6 months), (5) monoallelic MDS-EB1/EB2 without CK (n=20, 2.4%; OS 26.2 months), (6) monoallelic MDS-LB without CK (n=57, 6.7%; OS 33.4 months), and (7) MF-CP and other MPN without CK (n=36, 4.3%; OS 37.0 months). This analysis defines a clear stepwise risk gradient, identifying subsets with extremely poor prognosis versus a relatively indolent disease. Conclusions: This is the first study to evaluate the prognostic impact of TP53mut MN across the entire MN spectrum, providing a framework for future refinement of TP53-driven disease classification. Key findings include: (i) MF-AP/BP and MDS/MPN overlap exhibit survival outcomes as dismal as AML, irrespective of the TP53 allele status; and (ii) complex karyotype is a surrogate for “biallelic equivalent”, refining risk interpretation in monoallelic cases. Overall, our study defines seven prognostic subgroups spanning all TP53mut MN, offering a foundation for risk-adapted clinical trial design and future classification updates.

Abstract Introduction The 2022 WHO/ICC classifications of myeloid neoplasms (MNs) incorporated genomics into the existing clinicopathologic framework, defining new (mono)genetic entities. However, this iterative approach resulted in a mix of pathologically and genomically-defined entities, reliant on arbitrary thresholds and historically-derived boundaries between entities. We hypothesised that integrating genomics with other features, de novo from first principles, might better incorporate modern molecular knowledge to define the biological continuum, evolutionary links and overlapping features across MN. Methods The discovery cohort comprised 6484 thoroughly annotated pts. Contemporary diagnoses included 1817 AML, 1695 MDS, 737 MPN, and 1101 MDS/MPN. Non-malignant pts (AA/CHIP/CCUS/ICUS) were included to explore beyond current neoplastic boundaries. 1407 pts had ≥1 follow-up sample/s. Validation was performed in an independent international cohort (n=2012). An unsupervised random forest algorithm was used to integrate status (and VAF) for 28 mutations, karyotypes, CBC features, sex and age (total parameters 144). Features were selected for potential to be independent of BM sampling. Proximity-based multidimensional scaling/PCA were used to visualize latent structure and identify variance-driving features. Results The model projected pts onto a continuous 3-dimensional space. We first applied clustering seeking 1st-order structure, revealing 4 major clusters (C1–C4). These were further subdivided into 58 distinct subclusters (SCs) by an unsupervised iterative clustering approach. All SCs were enriched for distinctive features, with diverse associations linking genomics to clinicopathological/outcome features. Notably, contemporary diagnoses were distributed widely throughout this landscape, with 9/58 SCs containing cases spanning multiple WHO/ICC MN categories. C1 displayed the most internal heterogeneity, with admixed AML, MDS and MDS/MPN pts. It naturally subdivided down to 4th-order subclustering. Ten SCs were dominated by splicing factor mutations. For example, SF3B1MT segregated into 3 SCs, alone or with high-VAF TET2/ASXL1 or DNMT3A mutations. A separate TET2/SRSF2 SC associated with elevated monocyte%, reflecting a discrete CMML-phenotype genomic entity. NPM1MT formed a distinct SC with FLT3-ITD, distinguished further by VAFs of FLT3, TET2, and NRAS. Current genomically-defined AML subtypes separated in the 4th subclustering. C2 encompassed classical MPN driver mutations across 6 SCs, including a distinct CALRMT group and others defined by variable JAK2 VAFs, co-mutation patterns and other CBC features: eg high-VAF SF3B1MT correlated with PB blast%, and concurrent TET2MT with higher Hb/monocyte counts. C3 was characterized by TP53 alterations, with 5 SCs differing by TP53MT burden, 17p lesions, karyotypic complexity and age. Two SCs, one marked by high TP53 VAF+complex karyotype, the other by ch17 lesions, were associated with the worst OS in the whole cohort. C4 contained most known non-malignant pts, dividing into 4 SCs: 2 largely comprising CCUS and AA, while 2 reflect overlaps/convergence between AA and MDS and MPN, respectively. Repurposing single-cell pseudotime analysis suggested multiple disease origins, with various progression trajectories converging on C3. Projecting them onto the model longitudinal samples moved along these derived paths, consistent with their known progression/remission changes, validating the model's biological relevance and predictive utility. Remarkably, the 58 SCs displayed distinct risks of clonal progression and survival. To maximize potential clinical utility we created a pan-MN prognostic score integrating these features. It performed robustly (c-index 0.84), matching/exceeding existing prognostic tools and validated in an independent dataset. Conclusion Integrating clinicopathologic and genomic data we developed ab initio a continuum model of MNs that transcends historical diagnostic boundaries, captures disease evolution and stratifies clinical outcomes. It may better reflect the core biology and natural histories of specific cases, placing more rational boundaries between discrete entities. Potential advantages extend to treatment selection/trial design (in the era of molecularly-targeted therapies) and personalised prognostication throughout each disease course. Expanded validation is needed to resolve complexity in some areas (notably in C2/C4) and validate/refine this prototype framework.