Citations

INTRODUCTION: Reliable biomarkers for the diagnosis of chronic pancreatitis (CP) and pancreatic fibrosis severity are lacking, hindering effective treatment and management. Histologic fibrosis is a hallmark of late-stage CP, but noninvasive methods to evaluate fibrosis progression are limited. We used urine proteomics to discover biomarkers that identify patients with CP and predict fibrosis severity. METHODS: We performed a cross-sectional study of 130 total subjects (CP n = 50) selected based on clinical criteria in a tertiary care setting. Urine proteomics samples were quantified using data-independent acquisition mass spectrometry. Differential biomarker candidates were identified with false discovery rate-corrected pairwise comparisons. These proteins were validated with an independent paired urine and plasma sample cohort (n = 36). Machine learning was used to develop a protein panel that predicted Ammann scores for patients with histologic fibrosis. RESULTS: We found 34 proteins consistently differentially expressed between CP and controls in pairwise false discovery rate-controlled tests. Of these, 25 urine proteins outperformed 19 previously suggested CP blood-based biomarkers in an independent validation cohort. Isocitrate dehydrogenase (IDH1), calcyphosin (CAPS), synuclein gamma (SNCG), and protein S100-P (S100P) all produced receiver operator curve area under the curve values >0.95, while the best plasma marker was interleukin 2 receptor subunit alpha (receiver operator curve area under the curve = 0.80). A 12-protein panel of identified markers predicted fibrosis severity with a linear correlation R 2 value of 0.61. DISCUSSION: We identified a panel of proteins that may diagnose CP in children and developed a model to predict pancreatic fibrosis severity, offering promising tools for improving diagnostics and patient care.

Abstract Background Computed tomography (CT) is an essential imaging modality for disease diagnosis, treatment efficacy, and image‐based guidance of various medical procedures. The locally deposited radiation dose in tissues, as estimated by the computed tomography dose index (CTDI), can vary considerably across exposures delivered by CT scanners from different vendors, even if the scans are performed using similar technique factors, such as tube potential and tube current. The volumetric CTDI (CTDI vol ) is a common dose metric that reports an average radiation dose (in mGy) delivered to a specific volume within a test phantom. The CTDI vol is important in dosimetry applications as the organ absorbed dose within the patient has been shown to scale in near‐linear proportion, creating a basis for comparing organ doses across different scan protocols and scanner models. Purpose To develop a database of tube current‐time product (mAs) normalized CTDI vol values for currently utilized CT scanner models for each of the four primary CT vendors for use in the MIRDct organ dosimetry software available at MIRDsoft.org. This data forms the basis of the MIRDct code, which reports organ doses across a range of computational phantoms based upon axial organ dose coefficient libraries generated through Monte Carlo radiation transport for a reference CT scanner. Organ doses delivered by alternate CT scanner vendors and models may then be reported using ratios of normalized CTDI vol values under similar technique factors. Methods Scanners were selected from four major CT manufacturers: Philips Healthcare, GE Healthcare, Canon Medical Systems, and Siemens Healthineers. Technique parameters were also selected for each scanner that closely matched values used in the generation of an equivalent CT source term (small to large bowtie filters; 80–140‐kVp tube voltage; and 10‐mm to 40‐mm beam collimation). For each scanner chosen, the appropriate technique factors and protocols were selected, and the console‐reported CTDI vol values were recorded and normalized to a set value of 100 mAs. The normalized CTDI vol data collected for use within the MIRDct code were analyzed for noticeable patterns, features, and trends, and were compared to similar normalized CTDI vol datasets used within the National Cancer Institute NCICT software and the Virtual Phantoms, Inc. VirtualDose software. Results For all given CT scanner and technique factor combinations, there was strong agreement in normalized CTDI vol values across all three codes: between 0% and 12% difference for the compared scanners. Ratios of CTDI vol values for various CT scanner vendors and models to the corresponding CTDI vol values for the MIRDct reference scanner (Cannon Aquilion One Genesis) were also compared on the basis of either the 16‐cm head PMMA phantom or the 32‐cm body PMMA phantom. The mean quotient of these normalized CTDI vol ratios (head ratios to body ratios) was found to be approximately 1.06, and thus either ratio may be applied in reporting patient organ dose by MIRDct. Conclusions A database of normalized CTDI vol (mGy/100 mAs) was created for 17 models of CT scanners from four manufacturers at varying tube potentials, collimations, x‐ray bowtie filters, and phantom sizes for use in the MIRDct software.

Abstract Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. Significance: Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.

This cohort study examines the clinical implementation of timely consolidation with antiresorptive therapy to preserve bone mineral density gains and reduce fracture risk.

Background: Sinonasal undifferentiated carcinoma (SNUC) is an extremely rare, high-grade, and aggressive tumor of the sinonasal tract. Due to the rarity of this malignancy, current treatment guidelines are based on small and often/mainly single-center retrospective datasets. In the absence of a universally accepted standard of care for SNUC, treatment approaches vary across countries and institutions, reflecting real-world clinical practice. The primary aim of this study was to describe real-world treatment and outcomes for patients with confirmed SNUC. Methods: This was an international, multi-center, retrospective, observational cohort study that pooled patients into the largest SNUC dataset to date. Fifteen centers were enrolled to contribute data, including seven from Europe, four from the United States, three from the United Kingdom, and one from Canada. In the absence of a universally accepted standard of care for SNUC, treatment approaches varied across countries and institutions, reflecting real-world clinical practice. Patients included were those with histologically confirmed SNUC who were treated between 1997 and 2021. Results: This study yielded 485 patients treated for SNUC. The median age at diagnosis was 55.6 years (IQR: 44.5–67.6), and 63.7% were male. Most cases presented at advanced stages, with 70.8% as T4a or T4b. Overall survival (OS) outcomes were available for 412 patients, with a median follow-up of 26.0 months. The 5- and 10-year OS were 47.2% (95% CI: 40.8–53.3%) and 39.6% (95% CI: 32.5–46.6%), respectively. Advanced age, dichotomized T-stage (T4a/b vs. T1–3), M-stage, and orbital involvement were significant poor prognostic factors on univariable analysis (p’s < 0.01). On multivariable analysis, orbital involvement (HR: 2.73, 95% CI: 1.42–5.27, p = 0.003) and distance metastasis stage (HR: 3.00, 95% CI: 1.25–7.21, p = 0.014) were both independently associated with worse OS. Conclusions: This observational study presents the largest multi-center cohort analysis of SNUC to date, providing new insights into prognostic factors for a rare cancer treated at global centers of excellence. Orbital involvement and the presence of metastases are candidate independent risk factors associated with poorer OS.

Abstract Background The Alzheimer's disease (AD) Braak staging is a key framework for classifying tau pathology progression in AD based on histopathological post‐mortem brain examinations. However, adapting it to PET imaging can be challenging due to differences in tracer uptake patterns and binding properties, which affect sensitivity, specificity, and regional staging. This study compares Braak staging across four tau PET tracers: Flortaucipir, MK6240, PI2620, and RO948. Methods We assessed 90 participants across the AD spectrum (46 CU, 31 MCI, 13 dementia; mean age 66.1 ± 7.8) using Aβ PET and four tau PET tracers: (Flortaucipir, MK6240, PI2620, and RO948). Braak positivity was defined based on Aβ− CU individuals (mean +2.5 SD, SUVR). To evaluate systematic bias and agreement between tracers, we computed pairwise differences at corresponding Braak stage estimates and applied the Bland‐Altman method to assess mean bias and limits of agreement. Additionally, Tau PET Braak region trajectories were modeled as functions of Aβ burden (Centiloid scale) using the Lowess method. Results Braak stage trajectories as a function of Aβ differ depending on the tracer and the sequential order of abnormality is highly variable. For instance, while for MK6240, RO948 and PI2620, Braak I is the first region to became abnormal, for Flortaucipir the earliest region to became abnormal is Braak IV (Figure 1). This variable pattern of abnormality impacts in the concordance of Braak staging between tracers with the highest Braak staging agreement resulting in concordance levels of approximately 70%. The highest levels of agreement between tracers usually happen at Braak 0 or Braak IV‐V, with intermediate stages showing very low concordance (Figure 2). The Bland‐Altman analysis identified wide limits of agreement, suggesting high variability and high tracer‐specific differences (Figure 3). On the other hand, it also identified that mean differences between tracers were small, indicating minimal systematic bias. Conclusion These preliminary findings reveal discrepancies in Braak staging when comparing Flortaucipir, MK6240, PI2620 and RO948. These findings suggest that while the tracers provide comparable stages on average, they may not be fully interchangeable in individual cases.

Background/Objectives: Postoperative opioid exposure after lumbar fusion remains a key clinical concern. Understanding which perioperative factors are associated with lower postoperative opioid use may help optimize recovery after minimally invasive (MIS) transforaminal lumbar interbody fusion (TLIF). This study aimed to determine if patients undergoing MIS-TLIF under spinal anesthesia (SA) showed lower postoperative opioid use compared to those undergoing MIS-TLIF under general anesthesia (GA). Methods: We retrospectively studied all adult patients (>18 years) undergoing 1- and contiguous 2-level MIS-TLIFs performed by a single surgeon. Patients undergoing the procedure under GA were compared to those undergoing the procedure under SA. Postoperative oral opioid use, up to 3 months post discharge, was collected. A 1:1 propensity score matching (PSM) protocol was implemented. Each outcome variable was initially assessed using univariate regression. Predictor variables with a p-value < 0.2 were included in the multivariate regression model. This was a retrospective, non-randomized study, and residual confounding cannot be excluded despite PSM. Results: The matched groups (n = 50 in each group) did not differ significantly depending on demographics or levels fused. Before regression, mean number of postoperative opioid prescriptions (p = 0.03), mean total operating room (OR) time in minutes (p < 0.01), and median length of stay (LOS) in days (p = 0.03) were significantly different. Multivariate regression showed that the GA group received 216.5 more total morphine milligram equivalents than the SA group (95% CI = 0.7–432.2, p = 0.049). The days of opioid use were higher in the GA group by 3.8 days (95% CI = 0.5 to 7.1, p = 0.025). On multivariate regression, LOS in hours was greater in the GA group by 14.1 h (p = 0.042). Conclusions: SA is an effective anesthetic modality for spinal surgery with the advantages of reduced postoperative opioid use, reduced OR time, and shorter LOS compared to GA.

Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH’s Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus, sustainability, technology) principles. Gold Standard Science supports open science by emphasizing transparency, reproducibility, and the use of best practices that enable others to verify and extend research. Pairing a research article’s cited data snapshot with a versioned, environment-specific code release, deposited in a companion code repository, ensures that, upon submission to a medical journal, readers and reviewers can directly verify results. An executable and updatable companion code repository complements, rather than replaces, established research data repositories. When code underlying medical research results is made openly available, then other scientists can inspect, run, and validate analyses. These activities enhance reproducibility, which is a core aim of GSS. Shared code also facilitates collaborative innovation by allowing researchers to extend the utility of the code to new datasets and applications. For researchers, code sharing can increase visibility, credibility, and citation impact. Demonstrating transparency through shared executable and updatable code builds trust with journal readers, peer reviewers, funders, and peers. Shared code in an open access repository signals adherence to high standards of scientific integrity and attracts opportunities for collaboration. A researcher who shares code receives recognition as a leader in reproducible, trustworthy research consistent with NIH’s GSS principles.

632 Background: Paltusotine is an oral, nonpeptide, selective somatostatin receptor 2 agonist. In a phase 2 study, treatment with once-daily paltusotine reduced the frequency and severity of carcinoid syndrome (CS) symptoms and was well tolerated. The effect of paltusotine on biomarkers of serotonin and 5-hydroxyindoleacetic acid (5-HIAA) was further explored. Methods: This exploratory study, without formal power calculations, included an 8-week randomized treatment phase (completed) and a 102-week open-label extension phase (currently ongoing). The purpose was to evaluate safety, pharmacokinetics, and exploratory efficacy endpoints, including changes in biomarkers of paltusotine treatment. Enrolled patients were adults with a stable, documented grade 1 or 2 neuroendocrine tumor (NET) and CS. These patients were actively symptomatic and either untreated with somatostatin receptor ligand (SRL) therapy (average of ≥4 bowel movements [BMs] per day or >2 flushing episodes per day in ≥2 days over a 2-week period) or washed out of SRL therapy (symptoms previously controlled on SRL), with demonstrated symptom worsening after washout. Patients were randomized to once-daily paltusotine 40 mg or 80 mg; one optional uptitration (from 40 mg to 80 mg or 80 mg to 120 mg) was permitted. Blood samples for assessment of biomarkers (serum serotonin and plasma 5-HIAA) were collected longitudinally from screening to end of treatment. Upper limit of normal was prespecified as 541 ng/mL for serotonin and 22 ng/mL for 5-HIAA. This analysis focuses on changes in biomarker from baseline to the end of 8-week randomized treatment phase and after approximately one year (48 weeks). Results: Thirty-six patients (n=9 untreated; n=27 SRL washout) were randomized. Mean age was 60.8 years (range 35-83), and 52.8% were female. Nineteen patients had grade 1 NETs, and 17 had grade 2 NETs. As reported previously, treatment with once-daily, oral paltusotine was well tolerated and reduced the frequency and severity of CS symptoms, justifying further clinical development of the 80 mg dose. Mean serum serotonin decreased from 1553.0 ng/mL at baseline to 643.9 ng/mL at Week 8, and mean plasma 5-HIAA decreased from 245.1 ng/mL to 159.7 ng/mL. There was a trend of untreated patients achieving a greater reduction in comparison to washout patients. At 48-week follow-up, mean serum serotonin was stabilized at 791.50 ng/mL (n=20), and mean plasma 5-HIAA was stabilized at 190.45 ng/mL (n=20). Conclusions: Paltusotine significantly reduced serotonin and 5-HIAA levels, with effects maintained at 48 weeks. Biomarker reductions paralleled reductions in BM and flushing frequency. These findings support further investigation in the ongoing phase 3 study (CAREFNDR, NCT07087054). Clinical trial information: NCT05361668 .