Citations

8555 Background: Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of non-small cell lung cancer (NSCLC), with historically poor outcome. Excellent response of metastatic PSC to immunotherapy was previously reported, but its outcome compared with other NSCLCs is unknown in the immunotherapy era. Methods: NCDB was queried for stage IV NSCLC diagnosed from 2016 to 2020. Patients who were treated with chemotherapy only or immunotherapy only in the first course of treatment were included. Log-rank was used for survival analysis and adjusted by cox regression for age, gender, race, academic/integrated center, insurance, and comorbidity. Results: A total of 37,617 patients were identified, including 201 PSCs and 37,416 other NSCLCs. Pleomorphic (54%) was the most common PSC subtype. There was significant interaction between the survival effect of treatment and histology (interaction p = 0.024). When treated with immunotherapy alone, no significant difference was found between PSC and other NSCLCs (median survival 11.4 vs 12.4 months, logrank p = 0.56, HR 1.02, 95% CI 0.81 – 1.30). However, when treated with chemotherapy alone, PSC remained significantly associated with worse survival (median survival 4.5 vs. 8.5 months, logrank p <0.001, HR 0.67, 95% CI 0.54 – 0.83). Among PSC subtypes, spindle/giant cell PSCs were more likely to benefit from immunotherapy alone than pleomorphic PSCs (interaction p = 0.005), when compared with chemotherapy (Spindle/giant cell subtype: HR 0.24, 95% CI 0.14 – 0.42; Pleomorphic subtype: HR 0.60, 95% CI 0.37 – 0.99). Conclusions: Compared with other NSCLCs, PSC may not be associated with worse survival when treated with immunotherapy alone as it was when treated with chemotherapy. Distinct PSC subtypes may respond differently to immunotherapy and warrants further research. [Table: see text]

Liver fibrosis is characterized by the activation of perivascular hepatic stellate cells (HSCs), the release of fibrogenic nanosized extracellular vesicles (EVs), and increased HSC glycolysis. Nevertheless, how glycolysis in HSCs coordinates fibrosis amplification through tissue zone-specific pathways remains elusive. Here, we demonstrate that HSC-specific genetic inhibition of glycolysis reduced liver fibrosis. Moreover, spatial transcriptomics revealed a fibrosis-mediated up-regulation of EV-related pathways in the liver pericentral zone, which was abrogated by glycolysis genetic inhibition. Mechanistically, glycolysis in HSCs up-regulated the expression of EV-related genes such as Ras-related protein Rab-31 ( RAB31 ) by enhancing histone 3 lysine 9 acetylation on the promoter region, which increased EV release. Functionally, these glycolysis-dependent EVs increased fibrotic gene expression in recipient HSC. Furthermore, EVs derived from glycolysis-deficient mice abrogated liver fibrosis amplification in contrast to glycolysis-competent mouse EVs. In summary, glycolysis in HSCs amplifies liver fibrosis by promoting fibrogenic EV release in the hepatic pericentral zone, which represents a potential therapeutic target.

Abstract Aims Acute myocarditis, although a rare disease, can be associated with sudden cardiac death or the need for transplantation in both children and young adults. To date, there is no definitive evidence to support the routine use of immunosuppressive therapy or treatment targeting inflammation in patients with myocarditis. Animal models of cardiovascular (CV), as well as neurological diseases, have demonstrated that cannabidiol has significant anti-inflammatory properties and may represent a promising therapy in acute myocarditis. This efficacy has been shown in a murine model of autoimmune myocarditis as well as in in vitro and in vivo models of heart failure (HF). Methods and results We present the rationale and design of the ARCHER Trial, an international multicentre, double-blind, randomized, placebo-controlled, phase II study examining the safety and efficacy of a pharmaceutically produced cannabidiol formulation, in patients with mild to moderate acute myocarditis. Eligible patients are those with acute myocarditis, randomized within 10 days of the diagnostic cardiac MRI (CMR), which has met defined diagnostic criteria for myocarditis. Oral treatment (cannabidiol or placebo) is titrated from 2.5 mg/kg of body weight up to 10 mg/kg of body weight b.i.d. (or highest tolerated dose) and taken for 12 weeks in addition to standard of care therapy for HF. The primary endpoints are defined as changes in global longitudinal strain (GLS) and extra cellular volume (ECV), measured by CMR at 12 weeks. Assuming 80% power, a 5% alpha risk and 25% missing CMR follow-up data at Week 12, 100 patients are required to demonstrate the desired treatment effect of 18%. The change in left ventricular ejection fraction (LVEF) from baseline to Week 12 was selected as the secondary endpoint. Additional exploratory endpoints include changes in hs-troponin, NT-proBNP, markers of inflammation and endothelial function during the 12-week treatment period. The trial is ongoing but is now more than 50% recruited. As enrolment in the trial continues, no interim data are available for inclusion in this Design paper. Conclusions The ongoing ARCHER Trial is an international, multicentre, double-blind, randomized, placebo-controlled phase II study, designed to determine the effect of a pharmaceutically produced cannabidiol formulation on CMR parameters in patients presenting with acute myocarditis. Enrolment of 100 patients is expected to conclude in Q3 2024. Study results will be available in early 2025.

PURPOSE Long-term outcomes of patients with stage I human epidermal growth factor receptor 2 (HER2)–positive breast cancer receiving adjuvant trastuzumab emtansine (T-DM1) remain undefined, and prognostic predictors represent an unmet need. METHODS In the ATEMPT phase II trial, patients with stage I centrally confirmed HER2-positive breast cancer were randomly assigned 3:1 to adjuvant T-DM1 for 1 year or paclitaxel plus trastuzumab (TH). Coprimary objectives were to compare the incidence of clinically relevant toxicities between arms and to evaluate invasive disease-free survival (iDFS) with T-DM1. Correlative analyses included the HER2DX genomic tool, multiomic evaluations of HER2 heterogeneity, and predictors of thrombocytopenia. RESULTS After a median follow-up of 5.8 years, 11 iDFS events were observed in the T-DM1 arm, consistent with a 5-year iDFS of 97.0% (95% CI, 95.2 to 98.7). At 5 years, the recurrence-free interval (RFI) was 98.3% (95% CI, 97.0 to 99.7), the overall survival was 97.8% (95% CI, 96.3 to 99.3), and the breast cancer-specific survival was 99.4% (95% CI, 98.6 to 100). Comparable iDFS was observed with T-DM1 irrespective of tumor size, hormone receptor status, centrally determined HER2 immunohistochemical score, and receipt of T-DM1 for more or less than 6 months. Although ATEMPT was not powered for this end point, the 5-year iDFS in the TH arm was 91.1%. Among patients with sufficient tissue for HER2DX testing (n = 187), 5-year outcomes significantly differed according to HER2DX risk score, with better RFI (98.1% v 81.8%, hazard ratio [HR], 0.10, P = .01) and iDFS (96.3% v 81.8%, HR, 0.20, P = .047) among patients with HER2DX low-risk versus high-risk tumors, respectively. CONCLUSION Adjuvant T-DM1 for 1 year leads to outstanding long-term outcomes for patients with stage I HER2-positive breast cancer. A high HER2DX risk score predicted a higher risk of recurrence in ATEMPT.

Abstract Objectives The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs—a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care. Materials and Methods We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-class classification. We examined 3 traditional machine learning models, 9 BERT-based language models, 6 fusion models, and 2 ensemble models. Results The outcomes of our experimentation underscore the superior performance achieved by BERT-based models in comparison to traditional machine learning models. Remarkably, our fusion model emerges as the top-performing solution, delivering a notably improved accuracy score of 77.67 ± 2.74% and an F1 score of 74.37 ± 3.70% in macro-average. Discussion This study highlights the feasibility and effectiveness of multi-class classification for patient primary concern detection and the proposed fusion framework for enhancing primary concern detection. Conclusions The use of multi-class classification enhanced by a fusion of multiple pretrained LMs not only improves the accuracy and efficiency of patient primary concern identification in PPMs but also aids in managing the rising volume of PPMs in healthcare, ensuring critical patient communications are addressed promptly and accurately.

AbstractBackgroundIntensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency.PurposeThis study introduces an innovative Two‐Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies.MethodsOur approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three‐phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose‐Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods.ResultsThe proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high‐quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints.ConclusionsOur Two‐Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans.

Key Points Measuring blood potassium has always required access to blood. The surface electrocardiogram, analyzed using an artificial intelligence algorithm, can detect hyperkalemia bloodlessly. The artificial intelligence-analyzed electrocardiogram exhibited a high negative predictive value but substantially lower positive predictive value. Background Artificial intelligence (AI) electrocardiogram (ECG) analysis can enable detection of hyperkalemia. In this validation, we assessed the algorithm's performance in two high acuity settings. Methods An emergency department (ED) cohort (February to August 2021) and a mixed intensive care unit (ICU) cohort (August 2017 to February 2018) were identified and analyzed separately. For each group, pairs of laboratory-collected potassium and 12 lead ECGs obtained within 4 hours of each other were identified. The previously developed AI ECG algorithm was subsequently applied to leads 1 and 2 of the 12 lead ECGs to screen for hyperkalemia (potassium >6.0 mEq/L). Results The ED cohort ( N =40,128) had a mean age of 60 years, 48% were male, and 1% ( N =351) had hyperkalemia. The area under the curve (AUC) of the AI-enhanced ECG (AI-ECG) to detect hyperkalemia was 0.88, with sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive likelihood ratio (LR+) of 80%, 80%, 3%, 99.8%, and 4.0, respectively, in the ED cohort. Low-eGFR (<30 ml/min) subanalysis yielded AUC, sensitivity, specificity, PPV, NPV, and LR+ of 0.83, 86%, 60%, 15%, 98%, and 2.2, respectively, in the ED cohort. The ICU cohort ( N =2636) had a mean age of 65 years, 60% were male, and 3% ( N =87) had hyperkalemia. The AUC for the AI-ECG was 0.88 and yielded sensitivity, specificity, PPV, NPV, and LR+ of 82%, 82%, 14%, 99%, and 4.6, respectively in the ICU cohort. Low-eGFR subanalysis yielded AUC, sensitivity, specificity, PPV, NPV, and LR+ of 0.85, 88%, 67%, 29%, 97%, and 2.7, respectively in the ICU cohort. Conclusions The AI-ECG algorithm demonstrated a high NPV, suggesting that it is useful for ruling out hyperkalemia, but a low PPV, suggesting that it is insufficient for treating hyperkalemia.

Objectives: This study aims to identify COVID-19 breakthrough infections among people with HIV (PWH) across different phases of the pandemic and explore whether differential immune dysfunctions are associated with breakthrough infections. Design and methods: This retrospective population-based cohort study used data from an integrated electronic health record (EHR) database in South Carolina (SC). Breakthrough infection was defined as the first COVID-19 diagnosis documented in the state agency after the date an individual was fully vaccinated (ie, 2 doses of Pfizer/BNT162b2 or Moderna/mRNA-1273, or 1 dose of Janssen/Ad26.COV2.S) through June 14, 2022. We analyzed the risk and associated factors of the outcome using Cox proportional hazards models. Results: Among 7596 fully vaccinated PWH, the overall rate of breakthrough infections was 118.95 cases per 1000 person-years. When compared with the alpha-dominant period, the breakthrough infection rate was higher during both delta-dominant (HR: 1.50; 95% CI: 1.25 to 1.81) and omicron-dominant (HR: 2.86; 95% CI: 1.73 to 4.73) periods. Individuals who received a booster dose had a lower likelihood of breakthrough infections (HR: 0.19; 95% CI: 0.15 to 0.24). There was no association of breakthrough infections with degree of HIV viral suppression, but a higher CD4 count was significantly associated with fewer breakthroughs among PWH (>500 vs <200 cells/mm3: HR: 0.68; 95% CI: 0.49 to 0.94). Conclusions: In our PWH population, the incidence of breakthrough infections was high (during both delta-dominant and omicron-dominant periods) and mainly associated with the absence of a booster dose in patients older than 50 years, with comorbidities and low CD4 count.

Abstract BACKGROUND Treatment and clinical management decisions for children with NF1-OPGs remain challenging as most existing data are retrospective and have not included standardized visual outcomes. In this study, we prospectively enrolled newly diagnosed NF1-OPGs and performed standardized neuro-oncology and ophthalmology assessments in order to develop evidence-based guidelines for monitoring and treatment. METHODS Children with NF1-OPG on MRI who were evaluated by both a study ophthalmologist and neuro-oncologist/NF1 expert within 1 month of radiologic diagnosis were eligible for enrollment. All subjects attempted quantitative visual acuity using Teller acuity cards (TAC) as well as ATS-HOTV testing. The neuro-oncologist/NF1 expert provided reasons for obtaining the MRI as well as initiating treatment, if applicable. Descriptive statistics calculated the success rate of acquiring TAC and reasons to obtain the MRI. RESULTS Two-hundred fifty subjects from 22 institutions were enrolled and had at least one visit beyond baseline (Median age 3.1 years, range 0.1–16.8; 53% female). TAC was successfully acquired in both eyes (N=195, 78%) and at least one eye in (N=206, 82%). ATS-HOTV was successfully acquired in both eyes (N=97, 39%) and at least one eye in (N=98, 39%). The two most common reasons to obtain an MRI were screening due to a diagnosis of NF1 (N=99, 39%) and ophthalmologic concern (N=81, 32%). At enrollment, continued observation occurred in a majority of subjects (N=221, 88%) while treatment with chemotherapy was initiated in only 11% (N=29). Twenty-nine (11%) subjects initially observed transitioned to treatment after enrollment (range: 2.5–25 months) thus far. DISCUSSION We present a prospective multicenter study of children with newly diagnosed NF1-OPGs. The ability to acquire quantitative visual acuity was higher than anticipated. The frequency of NF1-OPGs requiring treatment is lower than previously reported. Regression models of clinical and MRI features that prompted immediate treatment with chemotherapy versus observation will be discussed.

Abstract BACKGROUND NF1-OPGs are amorphous tumors involving either single or multiple locations (optic nerve, chiasm, tract) along the anterior visual pathway (AVP). In this prospective study, we investigated how volumetric MRI measures of the AVP as well as other clinical variables are associated with treatment decisions in children with newly diagnosed NF1-OPGs. METHODS Children with newly diagnosed NF1-OPG whose MRI included a T1-weighted volumetric sequence without significant artifact at their enrollment visit were eligible for inclusion. All subjects underwent a quantitative ophthalmic exam to determine if visual acuity (VA) was normal. The neuro-oncologist/NF1 expert determined whether the subject would be observed or undergo treatment at that baseline visit. Volumetric MRI analysis was automatically performed using a deep learning network that measured AVP volume (mm3). Non-parametric group comparisons and multivariable logistic regression models evaluated the impact of age at enrollment, sex, NF1 inheritance type, AVP volume, and VA on the decision for immediate treatment with chemotherapy versus observation. RESULTS One-hundred twenty-three subjects met inclusion criteria. Subjects assigned to observation (N=112, 44% female) and subjects immediately treated with chemotherapy (N=11, 80% female) at enrollment were of similar age (2.7 and 2.8 years, respectively) and inheritance (p &gt; 0.05). Abnormal VA was present more often in the treatment group (46%) compared to the observation group (17%, p &lt;0.001). AVP volume was significantly greater in the treatment group (4,181.1mm3) compared to the observation group (1,819.8mm3, p &lt;0.001). AVP volume, sex, and VA reached significance in univariable regression, however, in the multivariable regression model only the AVP volume (p &lt; 0.001) was significantly associated with treatment initiation. DISCUSSION Children with greater NF1-OPG AVP volumes are treated more often compared with those with lower volumes. Volumetric measures of NF1-OPGs are a valuable metric in understanding treatment patterns and are positioned to help inform clinical decision making.