Citations

Study Design: Analysis of prospectively collected data. Objective: To assess if systemic illness severity affects cervical spondylotic myelopathy (CSM) surgery outcomes. Summary of Background Data: It remains unclear if CSM patients with poor physical status/severe systemic illness benefit as much from surgery as those in good condition. Methods: Using the Quality Outcomes Database CSM cohort and the American Association of Anesthesiology (ASA) grade as a surrogate for illness burden, we compared patients with (ASA 3–4) and without (ASA 1–2) severe systemic illness, including rates of readmission and 24-month minimal clinically important differences (MCID) achievement for patient-reported outcomes (PROs)—numerical rating score (NRS) arm and neck pain, neck pain-related disability (NDI), and quality of life (EQ-5D). Results: Of 1141 CSM patients, 1062 had ASA grades recorded. Of these 1062 patients, 70.2% had a 2-year follow-up for mJOA, and 81%–84% had a follow-up for NRS arm and neck, NDI, and EQ-5D. Five hundred twenty-one patients (49.1%) had mild (ASA 1–2) and 541 (50.9%) had severe systemic illness (ASA 3–4). The severe disease cohort was older (63.3±11.0 vs. 57.4±11.7), had higher BMI (31.4±7.0 vs. 28.9±5.6), had more comorbidities (diabetes, coronary artery disease, depression), and had less independent ambulation (71.3% vs. 90.6%) ( P <0.05). At baseline, severe disease patients had worse NRS arm (5.2±3.5 vs. 4.7±3.4) and neck (5.5±3.2 vs. 5.1±3.3) pain, NDI (40.5±20.1 vs. 36.8±21.0), and EQ-5D (0.53±0.22 vs. 0.59±0.22) scores ( P <0.05). Perioperatively, the severe disease cohort had longer hospitalizations (2.4±2.6 vs. 1.7±2.0 days) and increased nonhome discharges (17% vs. 5%) ( P <0.05). The severe disease cohort had higher 90-day readmissions (7.6% vs. 2.5%), including surgery-related (3.7% vs. 1.5%) and non–surgery-related reasons (3.9% vs. 1.0%) ( P <0.05). On multivariate analysis, increased ASA grade was significantly associated with 90-day readmissions (OR: 2.55 per 1-grade increase, 95% CI: 1.38–4.83). However, both severe and mild disease cohorts had similarly high rates of achieving 2-year MCID for mJOA (67.5% vs. 66.0%), NRS arm (72.0% vs. 74.1%), neck (69.5% vs. 69.4%) pain, NDI (63.1% vs. 68.1%), and EQ-5D (67.9% vs. 66.9%) ( P >0.05). Conclusion: Patients with severe systemic illness (higher ASA) have worse baseline PROs and higher 90-day readmissions. However, they achieve similar MCID rates for mJOA and all measured PROs 2 years postoperatively.

Abstract Deep learning has advanced digital pathology and multi-omics data analysis. However, there is still a critical need to integrate these modalities to better understand complex diseases. Deep learning models, such as Prov-Gigapath, a state-of-the-art pathology foundation model, have been developed for analyzing whole-slide images (WSI). Our previously published deep-learning framework, OmicsFootPrint (OFP), transforms high-dimensional multi-omics data into intuitive genomically-arranged circular images and utilizes transfer learning to overcome the challenges of high-dimensional, low-sample-size data. In this study, we aimed to combine WSI and multi-omics data to develop a framework capable of distinguishing between invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC), which is clinically significant as it may help explain differential responses to therapies, such as tamoxifen versus letrozole. We enhanced the performance of our OFP model by dividing each multi-omics circular image (1024x1024x3 pixels) into 16 equal-sized patches (256x256x3 pixels). Each patch was trained using a separate EfficientNetV2 architecture with pre-trained ImageNet weights. The probability outcomes from these 16 models were subsequently combined through a meta-learner model using the AutoGluon framework. Concurrently, WSI images corresponding to the same patients were independently trained, maintaining consistent train/validation/test splits. The Prov-Gigapath model, which was trained using a dataset from the Providence Health System, was employed to extract patch-level embeddings from the WSI data. These embeddings were fine-tuned using a LongNet-based masked autoencoder to predict outcomes. Finally, predictions from the OFP model and the WSI-based Prov-Gigapath model were integrated through a meta-learner, preserving the original train/validation/test split. Model performances (AUC) were evaluated using the held-out test set. The gold standard used for the analysis was histological identification of IDC versus ILC, against which the performance of omics data alone, WSI data alone, and the multi-modal integration approach were compared. We evaluated our integrated model as a proof-of-concept using The Cancer Genome Atlas (TCGA) breast cancer cohort, comprising 92 ILC and 391 IDC samples. Multi-omics data, including gene expression, microRNA, copy number variation, and RPPA, were analyzed using the OFP framework, while WSI data were processed using the Prov-Gigapath method. The results demonstrated that the multi-modal integration approach significantly outperformed individual modalities, achieving an AUC of 0.98 compared to 0.87 for OFP (original), 0.95 for OFP (16-patches), and 0.92 for WSI. Integrating WSI and multi-omics data improves predictive accuracy, significantly improving the classification of breast cancer subtypes over histology alone. Citation Format: Naresh Prodduturi, Xiaojia Tang, Hamid R. Tizhoosh, Kevin J. Thompson, Richard Weinshilboum, Karthik V. Giridhar, Judy C. Boughey, Eric W. Klee, Liewei Wang, Matthew P. Goetz, Vera Suman, Krishna R. Kalari. A multi-modal learning framework to integrate digital pathology image and multi-omics data in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2429.

ABSTRACT HLA‐B*38:125 differs from HLA‐B*38:02:01:01 by one nucleotide substitution in codon 248 (GTG>ATG) in exon 4.

Gastric point-of-care ultrasound (POCUS) may offer clinical value in assessing aspiration risk among medically complex patients undergoing regional anesthesia and pain procedures. While the American Society of Anesthesiologists (ASA) preoperative fasting guidelines primarily apply to healthy individuals, medically complex populations often present with differing gastric emptying and aspiration risk. This narrative review, conducted by the American Society of Regional Anesthesia and Pain Medicine (ASRA-PM), adhered to PRISMA guidelines and was registered with PROSPERO. It focused on seven medically complex patient groups: those who are pregnant, obese, diabetic, have gastroesophageal reflux disease (GERD), are receiving emergency care, are enterally fed, or are taking GLP-1 receptor agonists (GLP-1RA). Study quality was assessed using the Mixed Methods Appraisal Tool (MMAT). Practice recommendations were developed using an iterative expert consensus process, with final recommendations based on evidence strength, clinical relevance, and expert agreement. Findings support the use of gastric POCUS in patients in active labor, those undergoing urgent cesarean sections, and those with diabetes. Conditional support is given for obesity, emergency care, enteral feeding, and GLP-1RA use. Routine use is not recommended in non-laboring pregnancies, elective cesarean delivery, or GERD. While gastric POCUS may aid with aspiration risk evaluation, its use should complement clinical judgment. Implementation may be limited by practical and training constraints, requiring individualized decision-making. These recommendations serve as a foundation for future research and potential clinical guideline development. PROSPERO registration number: CRD42023445927.

Abstract Richter transformation (RT) is defined as an aggressive lymphoma emerging in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). Despite novel therapeutics developed in CLL, RT is associated with poor outcomes. In light of recent progress regarding the diagnostic procedures and therapeutic concepts of RT, an international group of experts, under the coordination of the European Research Initiative on CLL, has developed consensus recommendations for clinical procedures and future research on this disease. Patients with RT typically present with a rapid clinical decline, worsening B-symptoms, elevated lactate dehydrogenase, and/or rapidly enlarging lymphadenopathy. Workup should include a positron emission tomography–computed tomography scan for patients with suspected RT. An excisional biopsy should be taken from an accessible lesion, preferably with the highest fluorodeoxyglucose avidity, and analyzed for the presence of aggressive lymphoma. The molecular relationship to the original CLL clone(s) should be defined. Because no effective standard treatment for RT exists, patients should be treated in a clinical trial. Response of both RT and CLL should be assessed at an early time point, and survival end points should be prioritized in trial design. We hope that these recommendations can help to harmonize clinical and translational research and improve outcomes for patients with RT.

Abstract Rationale Increased risk of coronavirus disease (COVID-19) hospitalization and death has been reported among patients with clinical lung disease. Objectives To test the association of objective measures of prepandemic lung function and structure with COVID-19 outcomes in U.S. adults. Methods Prepandemic obstruction (FEV1/FVC &lt; 0.70) and restriction (FEV1/FVC ⩾ 0.7, FVC &lt; 80%) were defined based on the most recent spirometry exam conducted in 11 prospective U.S. general population–based cohorts. Severe obstruction was classified by FEV1 &lt; 50%. Percentage emphysema, percentage high-attenuation areas, and interstitial lung abnormalities were defined on computed tomography in a subset. Incident COVID-19 was ascertained via questionnaires, serosurvey, and medical records from 2020 to 2023 and classified as severe (hospitalized or fatal) or nonsevere. Cause-specific hazard models were adjusted for sociodemographics, anthropometry, smoking, comorbidities, and COVID-19 vaccination status. Measurements and Main Results Among 29,323 participants (mean age, 67 yr), there were 748 severe incident COVID-19 cases over median follow-up of 17.3 months from March 1, 2020. Greater hazards of severe COVID-19 were associated with severe obstruction (vs. normal; adjusted hazard ratio [aHR], 2.11; 95% confidence interval [CI], 1.02–1.27), restriction (vs. normal; aHR, 1.40; 95% CI, 1.12–1.76), and percentage emphysema (highest vs. lowest quartile; aHR, 1.64; 95% CI, 1.03–2.61), but not greater high-attenuation areas or interstitial lung abnormalities. COVID-19 vaccination provided greater absolute risk reduction in these groups. Results were similar in participants without smoking, obesity, or clinical cardiopulmonary disease. Conclusions Prepandemic severe spirometric obstruction, spirometric restriction, and greater percentage emphysema lung on computed tomography were associated with risk of severe COVID-19. These findings support enhanced COVID-19 risk mitigation for individuals with impaired lung health and warrant further mechanistic studies on interactions of lung function, structure, and vulnerability to acute respiratory illnesses.

Abstract INTRODUCTION Biomarkers play a crucial role in understanding Alzheimer's disease (AD) pathogenesis and treatment effects. However, comparing biomarker measures without standardization and appreciating their magnitude relative to the disease can be challenging. METHODS To address this issue, we propose the CentiMarker approach, similar to Centiloid, which provides a standardized scale between normal (0) and nearly maximum abnormal AD (100) ranges. We applied this scale to cerebrospinal fluid (CSF) biomarkers in dominantly inherited AD and sporadic AD cohorts. RESULTS CentiMarkers facilitated the interpretation of disease abnormality, demonstrating comparable changes and distributions of AD biomarkers across disease stages. CentiMarkers make the treatment effect more comparable than their original scales across various biomarkers. DISCUSSION The versatility of CentiMarkers makes it a valuable tool for standardized biomarker comparison in AD research, enabling informed cross‐study comparisons and contributing to accelerated therapeutic development. Adoption of the CentiMarker scale could enhance biomarker reporting and advance our understanding of AD. Highlights Comparing fluid biomarkers without appreciating their magnitude relative to the disease can be challenging. We propose a CentiMarker metric to standardize biomarker measures from normal (0) and nearly maximum abnormal AD (100) ranges. CentiMarkers make the treatment effect more comparable across various biomarkers than when using the original scales.

Background Neoadjuvant treatment has become standard for patients with high-risk operable stage III melanoma, but the optimal regimen is unknown. Targeted therapy approaches yield high pathological response rates, while immunotherapy regimens show favorable recurrence-free survival (RFS). NeoACTIVATE was designed to address whether a neoadjuvant combination of both targeted therapy and immunotherapy might leverage the benefits of each. Methods We tested neoadjuvant treatment with 12 weeks of vemurafenib, cobimetinib, and atezolizumab for patients with BRAF-mutated (BRAFm) melanoma (cohort A) and cobimetinib and atezolizumab for patients with BRAF-wild-type (BRAFwt) melanoma (cohort B), regimens which we have shown generate a substantial major pathological response. After therapeutic lymph node dissection, patients received 24 weeks of adjuvant atezolizumab. Here, we report survival outcomes and their association with biomarkers assayed among the gut microbiome and peripheral blood immune subsets. Results With 49 months median follow-up, the median RFS was not reached for cohort A and was 40.8 months for cohort B. At 24 months after operation, 2 of 14 cohort A patients and 4 of 13 cohort B patients had experienced distant relapse. Key findings from correlative analyses included diversity, taxonomic and functional metagenomic gut microbiome signals associated with distant metastasis-free survival at 2 years. Notably, we observed a strong correlation between low microbial arginine biosynthesis (required for T-cell activation and effector function) and early distant recurrence (p=0.0005), which correlated with taxonomic differential abundance findings. Peripheral blood immune monitoring revealed increased double-positive (CD4+CD8+) T cells in patients with early recurrence. Conclusions Neoadjuvant treatment with cobimetinib and atezolizumab±vemurafenib was associated with a low rate of distant metastasis in patients with high-risk stage III melanoma. Freedom from early distant metastasis was highly associated with taxonomic differences in gut microbiome structure and with functional pathway alterations known to modulate T cell immunity. Identification of predictive biomarkers will permit optimization of neoadjuvant therapy regimens for individual patients. Trial registration number NCT03554083.

ABSTRACTObjectiveWhile endoscopic laser wedge excision (LWE) for iSGS demonstrated lower surgical recurrence rates compared to endoscopic dilation (ED), ED remains the primary technique employed. Additionally, serial intralesional steroid injections (SILSIs) also demonstrate benefits in controlling disease. We aimed to compare surgical recurrence rates following ED, ED + SILSI, and LWE following a patient's first operation.MethodsThis was a two‐center retrospective analysis of iSGS patients who underwent either ED, ED + SILSI, or LWE. Patients were followed to their last follow‐up date or reoperation. Kaplan–Meier analysis and Cox proportional hazards were used to evaluate the recurrence times across the different surgical groups with additional stratification by age, compliance to medical adjuvant therapy, and percentage of stenosis rated at reoperation.ResultsA total of 126 patients from Institution 1 underwent LWE, while at Institution 2, ED and ED + SILSI were performed on 32 and 23 patients, respectively. One‐year recurrence estimates were 9%, 53%, and 0% for LWE, ED, and ED + SILSI, respectively, while 5‐year recurrence estimates were 45%, 90%, and 19%, respectively. Adjusted Cox‐proportional hazard ratios demonstrated a greater risk of surgical recurrence with ED compared to LWE (2.25; 95% confidence interval [CI]: 1.31–3.88) and no difference between ED + SILSI and LWE (0.84; 95% CI: 0.32–2.25).ConclusionLWE demonstrates reduced recurrence times compared to ED when controlling for surgery number, age, triple therapy compliance, and percentage of stenosis at reoperation. The application of postoperative SILSI appears to similarly reduce recurrence rates comparable to LWE and warrants further investigation.

Abstract Purpose To report historical patterns of pharmaceutical expenditures, to identify factors that may influence future spending, and to predict growth in drug spending in 2025 in the United States, with a focus on the nonfederal hospital and clinic sectors. Methods Historical patterns were assessed by examining data on drug purchases from manufacturers using the IQVIA National Sales Perspectives database. Factors that may influence drug spending in hospitals and clinics in 2025 were reviewed—including new drug approvals, patent expirations, and potential new policies or legislation. Focused analyses were conducted for biosimilars, cancer drugs, endocrine drugs, generics, specialty drugs and vaccines. For nonfederal hospitals, clinics, and overall (all sectors), estimates of growth of pharmaceutical expenditures in 2024 were made based on a combination of quantitative analyses and expert opinion. Results In 2024, overall pharmaceutical expenditures in the US grew 10.2% compared to 2023, for a total of $805.9 billion. Utilization (a 7.9% increase) and new drugs (a 2.5% increase) drove this increase, while prices remained flat (a 0.2% decrease). Semaglutide was the top drug in 2024, followed by tirzepatide and adalimumab. Drug expenditures were $39.0 billion (a 4.9% increase) and $158.2 billion (a 14.4% increase) in nonfederal hospitals and clinics, respectively. In clinics, increased utilization drove growth, with a small contribution from new products, while prices remained flat. In nonfederal hospitals, new products, price, and new volume each contributed modestly to growth in spend. Several new drugs that will influence spending are expected to be approved in 2025. Specialty, endocrine, and cancer drugs will continue to drive expenditures. Conclusion For 2025, we expect overall prescription drug spending to rise by 9.0 to 11.0%, whereas in clinics and hospitals we anticipate an 11.0% to 13.0% increase and a 2.0% to 4.0% increase, respectively, compared to 2024. These national estimates of future pharmaceutical expenditure growth may not be representative of any health system because of the myriad of local factors that influence actual spending.