Citations

Abstract Nonmyeloablative-related haploidentical allogeneic stem cell transplantation (NMAC-HID allo-HSCT) has emerged as an additional treatment to achieve durable remission in sickle cell disease (SCD), a prevalent blood disorder characterized by painful vaso-occlusive crises and chronic anemia. The standard of care (SOC) for SCD includes hydroxyurea, pain management, and blood transfusion, but patients with SCD still lose several decades of life expectancy. Gene therapy (GT) for SCD is the other treatment for lifelong disease amelioration in SCD, with accessibility limited by cost and manufacturing capacity in the United States and globally. Two recent prospective studies that evaluated NMAC-HID allo-HSCT validated haploidentical allotransplantation as an efficacious and accessible treatment option in the era of GT. Given the ongoing price negotiation across jurisdictions for GT implementation and the absence of cost-effectiveness data comparing NMAC-HID allo-HSCT and GT, we conducted a cost-effectiveness analysis of NMAC-HID allo-HSCT vs GT vs SOC for adults and children living with SCD. The primary outcomes were the incremental cost-effectiveness ratio and the net monetary benefits across these 3 strategies. The secondary outcome was the maximum cost-effective threshold price for GT compared with NMAC-HID allo-HSCT. Treatment with SOC, NMAC-HID allo-HSCT, and GT accrued 14.3, 20.1, and 22.1 quality-adjusted life-years at costs of $1.22 million, $1.15 million, and $2.75 million, respectively. NMAC-HID allo-HSCT was the cost-effective strategy compared with GT in 100% of 10 000 Monte Carlo iterations across the base case and all scenario analyses. The maximum cost-effective thresholds for GT vs SOC were $1.4 million in the United States and $4200 to $22 000 across India, Nigeria, and Tanzania, depending on willingness-to-pay thresholds.

As machine learning (ML)-based decision support tools proliferate in clinical practice, understanding how clinicians integrate personalized ML predictions alongside randomized controlled trial (RCT) evidence is critical. We designed a web-based clinical decision support system (CDSS) presenting survival and adverse event data from a simulated RCT and ML model across 12 synthetic multiple myeloma scenarios. In a within-subjects study with 32 physicians, we evaluated how clinicians synthesize competing evidence sources to make treatment decisions. When ML and RCT outputs were concordant, physicians reported greater confidence than with RCT data alone. When results were discordant, most physicians shifted toward the ML-supported treatment, often before reviewing any information about model training or validation, suggesting a tendency toward automation bias rather than algorithm avoidance. Despite reporting higher perceived reliability after viewing model quality disclosures, physicians were largely unable to describe the validation procedures they had reviewed. Taken together, these findings reveal that clinicians may over-rely on ML recommendations even when equipped with tools designed to support critical appraisal. We discuss implications for CDSS design, clinician training, and the institutional safeguards needed before ML-based systems are deployed in high-stakes oncology settings.

Among the transcriptional dependencies that sustain leukemic identity in acute myeloid leukemia (AML), the menin–KMT2A chromatin complex has emerged as a central regulatory node. The scaffold protein menin, encoded by MEN1, facilitates transcriptional activation of HOX and MEIS family genes during normal hematopoietic development. In AML, this physiologic and developmentally regulated role is co-opted to sustain constitutive HOX/MEIS-driven programs that block differentiation and maintain leukemic potential. Although dependency on menin is most clearly established in KMT2A-rearranged and NPM1-mutated AML, this vulnerability appears to arise from a shared transcriptional state characterized by persistent HOX activation rather than from any single genetic alteration. Pharmacologic disruption of the menin-KMT2A interaction collapses stemness-associated transcriptional networks, promotes myeloid differentiation, and attenuates leukemic self-renewal. Clinical activity observed with menin inhibitors provides translational validation of this dependency and establishes menin inhibition as a differentiation-based therapeutic strategy. In this review, we examine the molecular basis of menin-dependent transcriptional regulation in AML and its implications for therapeutic targeting with menin inhibitors and resistance to therapy.

ABSTRACT Objective Odontogenic sinusitis (ODS) ranges from isolated maxillary disease to pansinusitis. We compared patient characteristics, microbial and histopathological features, and symptom outcomes following endoscopic sinus surgery (ESS) between low and high radiographic burden ODS patients. Methods ODS patients undergoing ESS between 01/2013 and 08/2024 were reviewed. Preoperative CT scans were used to classify patients into high radiographic burden [with ostiomeatal complex (OMC) opacification] and low radiographic burden ODS [clear OMC]. Demographic, microbiological, and histopathological data were analyzed. Symptom improvement was assessed using pre‐ and post‐operative SNOT‐22 scores. Results Eighty‐seven patients were identified (high CT burden: 70; low CT burden: 17). High CT burden ODS was associated with older age ( p = 0.014), higher overall degree of inflammation ( p = 0.002), hyperplastic/papillary epithelial changes ( p = 0.034), and neutrophil infiltration ( p = 0.003). Culture of classic ODS bacteria ( Fusobacterium spp., Prevotella spp., mixed anaerobes, Streptococcus anginosus group) did not correlate with CT disease burden ( p = 0.110). No independent predictors of radiographic high‐burden disease were identified. Post‐ESS, significant reduction in total and rhinologic SNOT‐22 scores was only observed in the radiographic high‐burden ODS group ( n = 39; median reductions: 23 and 12 respectively; p < 0.001). Conclusion High radiographic burden was associated with older patients and with tissue inflammation level. Classic ODS bacterial profile did not associate with increased CT burden. While these findings remain exploratory, the observed differences in inflammatory and symptomatic profiles between groups suggest that radiographic burden warrants further study as a potential factor in ODS clinical decision‐making. Level of Evidence 3.

Ziftomenib - a potent, selective, oral menin inhibitor - is approved as monotherapy for adults with relapsed/refractory (R/R) NPM1-mutated acute myeloid leukemia (NPM1-m AML). The KOMET-007 phase 1 trial investigated clinical activity and tolerability of ziftomenib in combination with standard therapies for R/R and newly diagnosed AML. Here, we report outcomes of adults with R/R NPM1-m AML treated with ziftomenib plus venetoclax/azacitidine. In phase 1a, patients received ziftomenib 200, 400, or 600 mg once daily with standard doses of venetoclax/azacitidine. In phase 1b, ziftomenib 600 mg was selected for expansion. Sixty-seven patients were treated (27 phase 1a; 40 phase 1b). Median age was 66 years, and 55% were men. Median number of prior therapies was 1 (range 1-8); 55% received prior venetoclax and 22% had prior transplantation. Most common (≥20%) grade ≥3 treatment-emergent adverse events were leukopenia (34%), thrombocytopenia (28%), febrile neutropenia and neutropenia (25% each). Six patients developed QTc prolongation (1 ziftomenib-related; grade 1), and 2 experienced differentiation syndrome (grade 3); all events were successfully managed. In patients receiving ziftomenib 600 mg, composite complete remission (CRc) rate was 46% (22/48), with 67% (12/18) achieving central measurable residual disease (MRD) negativity (&lt;0.01% threshold). In venetoclax-naïve and -exposed patients, CRc rates were 70% (16/23) and 24% (6/25), with MRD-negativity rates of 75% (9/12) and 50% (3/6), respectively. Median duration of response was 8.6 months, and median overall survival was not reached. The combination of ziftomenib 600 mg with venetoclax/azacitidine was well tolerated with deep and durable clinical activity in R/R NPM1-m AML. This trial was registered at www.ClinicalTrials.gov as #NCT05735184.

Abstract Isolated cardiac sarcoidosis (iCS), defined by granulomatous inflammation limited to the myocardium, represents the most diagnostically challenging and prognostically adverse form of sarcoidosis. As it is fundamentally a diagnosis of exclusion, iCS diagnosis relies on the absence of extracardiac sarcoid and the integration of multimodality imaging, endomyocardial biopsy, and molecular testing, each with inherent limitations. Cardiac magnetic resonance and positron emission tomography provide complementary assessment of inflammation, fibrosis, and ventricular function, enhancing diagnostic confidence. Electroanatomic mapping-guided biopsy may improve histologic yield, whereas genetic testing helps exclude phenocopies such as arrhythmogenic, hypertrophic, or dilated cardiomyopathies. Circulating biomarkers remain non-specific but may complement imaging-based algorithms. Future research should focus on harmonized imaging protocols, non-FDG radiotracers, and molecular tissue profiling to refine activity assessment and guide therapy. Multimodal, probability-based frameworks represent the most promising approach for earlier, more accurate diagnosis and risk stratification in iCS.

Background: The current guidelines recommend that women at elevated risk for breast cancer (BC), defined as lifetime BC risk ≥ 20%, undergo annual screening with breast magnetic resonance imaging (MRI) and mammogram. However, limited evidence exists in the literature to guide the optimal timing of the MRI relative to the mammogram. Our study evaluated women undergoing high-risk BC screenings to determine the impact of timing for supplemental MRI on BC detection. Methods: Patients who completed high-risk screening MRI at a single institution from January 2019 through June 2022 were included. Baseline characteristics and clinical outcomes were collected through retrospective chart review. MRI exams were divided into two groups based on timing of MRI: concurrent (<90 days from mammogram) and staggered (≥90 days from mammogram). Results: Of 1115 patients initially identified, 770 met inclusion criteria, with a total of 3707 screening exams performed (2073 mammograms and 1634 MRIs). The final analysis included 1355 MRI exams for 712 patients, where a prior mammogram and MRI were available. Of the MRIs included, 784 (57.9%) were concurrent and 571 (42.1%) were staggered. Additional imaging was performed for 12.5% (98/784) of concurrent MRIs and 9.6% (55/571) of staggered MRIs. Biopsy rates were 9.8% (77/784) for concurrent and 7.0% (40/571) for staggered MRIs. In this high-risk population, there were surprisingly low BC detection rates, with a BC incremental detection rate of 0.5% in both the concurrent and staggered groups (p = 1.0), with the median size of detected invasive BCs equaling 5 mm in the concurrent group and 4 mm in the staggered group (p = 0.72). Conclusions: When comparing concurrent and staggered MRI regimens, there were no significant differences in incremental cancer detection rate, tumor size, rates of additional imaging, or negative biopsies. Further investigation with prospective analysis is needed to validate these findings.

Background: The integration of artificial intelligence (AI) in dental and maxillofacial radiology is revolutionizing diagnostic accuracy and clinical decision-making. This bibliometric analysis investigates the research landscape, emerging trends, and scholarly impact of AI applications in this specialized field. Methods: A comprehensive search was conducted on 25 December 2024 using the Web of Science Core Collection database. Data analysis tools, including VOSviewer, CiteSpace, and Biblioshiny, were employed to examine publication trends, global contributions, collaborative networks, and keyword dynamics. Results: The analysis revealed a marked increase in AI-related publications in dental and maxillofacial radiology, particularly from 2016 onward. The number of studies rose steadily, reaching 218 publications in 2024. The United States led in research output, followed closely by China and South Korea, with KU Leuven emerging as the top-contributing institution. Reinhilde Jacobs was identified as the most prolific author, while Medical Physics was the most cited journal. Co-citation analysis highlighted influential works by authors such as J.H. Lee and F. Schwendicke . Keywords including “artificial intelligence,” “deep learning,” “CBCT,” and “classification” dominated research discussions, reflecting the field’s evolving focus. Recent research trends emphasize advanced applications in segmentation, accuracy enhancement, and predictive modeling. Conclusion: AI has become integral to the advancement of dental and maxillofacial radiology, offering significant improvements in diagnostic precision and treatment planning. This study underscores the importance of staying abreast of AI innovations to enhance patient care and foster future research opportunities. Researchers and clinicians are encouraged to adopt AI-driven approaches to maximize clinical efficiency and outcomes.