Enhanced predictive validity of integrative models for refractory hyperthyroidism considering baseline and early therapy characteristics: a prospective cohort study.

BACKGROUND: A subset of Graves' disease (GD) patients develops refractory hyperthyroidism, posing challenges in treatment decisions. The predictive value of baseline characteristics and early therapy indicators in identifying high risk individuals is an area worth exploration. METHODS: A prospective cohort study (2018-2022) involved 597 newly diagnosed adult GD patients undergoing methimazole (MMI) treatment. Baseline characteristics and 3-month therapy parameters were utilized to develop predictive models for refractory GD, considering antithyroid drug (ATD) dosage regimens. RESULTS: Among 346 patients analyzed, 49.7% developed ATD-refractory GD, marked by recurrence and sustained Thyrotropin Receptor Antibody (TRAb) positivity. Key baseline factors, including younger age, Graves' ophthalmopathy (GO), larger goiter size, and higher initial free triiodothyronine (fT3), free thyroxine (fT4), and TRAb levels, were all significantly associated with an increased risk of refractory GD, forming the baseline predictive model (Model A). Subsequent analysis based on MMI cumulative dosage at 3 months resulted in two subgroups: a high cumulative dosage group (average ≥ 20 mg/day) and a medium-low cumulative dosage group (average < 20 mg/day). Absolute values, percentage changes, and cumulative values of thyroid function and autoantibodies at 3 months were analyzed. Two combined predictive models, Model B (high cumulative dosage) and Model C (medium-low cumulative dosage), were developed based on stepwise regression and multivariate analysis, incorporating additional 3-month parameters beyond the baseline. In both groups, these combined models outperformed the baseline model in terms of discriminative ability (measured by AUC), concordance with actual outcomes (66.2% comprehensive improvement), and risk classification accuracy (especially for Class I and II patients with baseline predictive risk < 71%). The reliability of the above models was confirmed through additional analysis using random forests. This study also explored ATD dosage regimens, revealing differences in refractory outcomes between predicted risk groups. However, adjusting MMI dosage after early risk assessment did not conclusively improve the prognosis of refractory GD. CONCLUSION: Integrating baseline and early therapy characteristics enhances the predictive capability for refractory GD outcomes. The study provides valuable insights into refining risk assessment and guiding personalized treatment decisions for GD patients.

Real-world effectiveness of dupilumab in patients with asthma: Findings from the US ADVANTAGE study.

BACKGROUND: Dupilumab is approved as an add-on maintenance therapy for patients (≥6 years) with moderate-to-severe asthma. Better understanding of real-world effectiveness is needed. OBJECTIVE: To characterize the real-world effectiveness of dupilumab in asthma management. METHODS: This retrospective study included patients (≥12 years of age) diagnosed with asthma, initiating dupilumab between November 2018 and September 2020. The study used a US electronic medical record database (TriNetX Dataworks, Cambridge, Massachusetts). Asthma exacerbation rates before and after the initiation of dupilumab were analyzed using generalized estimating equations models with Poisson probabilistic link to estimate incidence rate ratios (IRRs). Sensitivity analyses were conducted based on previous exacerbation data, eosinophil levels, history of atopic dermatitis or chronic rhinosinusitis with nasal polyps, previous use of biologics, and presence of SARS-CoV-2 (COVID-19). RESULTS: A total of 2400 patients initiating dupilumab met all study criteria. After initiation of dupilumab, risk of asthma exacerbation was reduced by 44% (IRR, 0.56; 95% CI, 0.47-0.57; P = <0.0001) and systemic corticosteroid prescriptions by 48% (IRR, 0.52; 95% CI, 0.48, 0.56; P = <0.0001) compared with those before initiation of dupilumab. Adjustment for COVID-19 showed a greater reduction in asthma exacerbations (IRR, 0.50; 95% CI, 0.45-0.55; P = <0.0001). CONCLUSION: Current real-world efficacy evidence indicates that dupilumab reduces asthma exacerbations and total systemic corticosteroid prescriptions in clinical practice. The effectiveness of dupilumab was observed independent of exacerbation history, eosinophil levels, or COVID-19 impact.

Real-world effectiveness of dupilumab versus benralizumab and mepolizumab.

INTRODUCTION: In the United States, this real-world study compared the effectiveness of dupilumab, benralizumab, andmepolizumab in reducing exacerbations and systemic corticosteroid (SCS) prescriptions among patients with asthma. METHODS: Patients (12 years old) who initiated dupilumab, benralizumab, or mepolizumab (index) between November 2018 and September 2020 were identified by using electronic medical record data. Subjects were included if they had greater than or equal to 12 months of data before and after the index date and two or more severe asthma-related exacerbations before the index date. Differences in baseline characteristics were addressed by using inverse probability treatment weighting (IPTW). Pairwisecomparisons between dupilumab and benralizumab, or mepolizumab were conducted by using negative binomial regression, adjusting for baseline rates and unbalance characteristics (greater than or equal to 10% standardized differences) after IPTW. RESULTS: Overall, a total of 1737 subjects met all criteria: 825 dupilumab, 461 benralizumab, and 451 mepolizumab initiators.In the postindex period, dupilumab was associated with a 24% and 28% significant reduction in the risk of severe asthmaexacerbations versus benralizumab (incidence rate ratio [IRR] 0.76 [95% confidence interval {CI}, 0.67-0.86)] and mepolizumab(IRR 0.72 [95% CI, 0.63-0.82]), respectively. In addition, dupilumab treatment significantly reduced SCS prescriptionsby 16% and 25% versus benralizumab and mepolizumab, respectively (p < 0.05). CONCLUSION: This study represents one of the largest real-world comparisons of biologics (dupilumab, benralizumab, and mepolizumab) for asthma in the United States to date. This analysis shows that the use of dupilumab was associated with a significantly greater reduction in both severe asthma exacerbations and SCS prescriptions compared with benralizumab and mepolizumab.

Dupilumab in children aged 6 months to younger than 6 years with uncontrolled atopic dermatitis: a randomised, double-blind, placebo-controlled, phase 3 trial.

BACKGROUND: Current systemic treatments for children younger than 6 years with moderate-to-severe atopic dermatitis that is uncontrolled with topical therapies might have suboptimal efficacy and safety. Dupilumab is approved for older children and adults with atopic dermatitis and for other type 2 inflammatory conditions. We aimed to evaluate efficacy and safety of dupilumab with concomitant low-potency topical corticosteroids in children aged 6 months to younger than 6 years with moderate-to-severe atopic dermatitis. METHODS: This randomised, double-blind, placebo-controlled, parallel-group, phase 3 trial was conducted in 31 hospitals, clinics, and academic institutions in Europe and North America. Eligible patients were aged 6 months to younger than 6 years, with moderate-to-severe atopic dermatitis (Investigator's Global Assessment [IGA] score 3-4) diagnosed according to consensus criteria of the American Academy of Dermatology, and an inadequate response to topical corticosteroids. Patients were randomly assigned (1:1) to subcutaneous placebo or dupilumab (bodyweight ≥5 kg to <15 kg: 200 mg; bodyweight ≥15 kg to <30 kg: 300 mg) every 4 weeks plus low-potency topical corticosteroids (hydrocortisone acetate 1% cream) for 16 weeks. Randomisation was stratified by age, baseline bodyweight, and region. Patient allocation was done via a central interactive web response system, and treatment allocation was masked. The primary endpoint at week 16 was the proportion of patients with IGA score 0-1 (clear or almost clear skin). The key secondary endpoint (coprimary endpoint for the EU and EU reference market) at week 16 was the proportion of patients with at least a 75% improvement from baseline in Eczema Area and Severity Index (EASI-75). Primary analyses were done in the full analysis set (ie, all randomly assigned patients, as randomly assigned) and safety analyses were done in all patients who received any study drug. This study was registered with ClinicalTrials.gov, NCT03346434. FINDINGS: Between June 30, 2020, and Feb 12, 2021, 197 patients were screened for eligibility, 162 of whom were randomly assigned to receive dupilumab (n=83) or placebo (n=79) plus topical corticosteroids. At week 16, significantly more patients in the dupilumab group than in the placebo group had IGA 0-1 (23 [28%] vs three [4%], difference 24% [95% CI 13-34]; p<0·0001) and EASI-75 (44 [53%] vs eight [11%], difference 42% [95% CI 29-55]; p<0·0001). Overall prevalence of adverse events was similar in the dupilumab group (53 [64%] of 83 patients) and placebo group (58 [74%] of 78 patients). Conjunctivitis incidence was higher in the dupilumab group (four [5%]) than the placebo group (none). No dupilumab-related adverse events were serious or led to treatment discontinuation. INTERPRETATION: Dupilumab significantly improved atopic dermatitis signs and symptoms versus placebo in children younger than 6 years. Dupilumab was well tolerated and showed an acceptable safety profile, similar to results in older children and adults. FUNDING: Sanofi and Regeneron Pharmaceuticals.

H3K18 lactylation of senescent microglia potentiates brain aging and Alzheimer's disease through the NFκB signaling pathway.

Cellular senescence serves as a fundamental and underlying activity that drives the aging process, and it is intricately associated with numerous age-related diseases, including Alzheimer's disease (AD), a neurodegenerative aging-related disorder characterized by progressive cognitive impairment. Although increasing evidence suggests that senescent microglia play a role in the pathogenesis of AD, their exact role remains unclear. In this study, we quantified the levels of lactic acid in senescent microglia, and hippocampus tissues of naturally aged mice and AD mice models (FAD4T and APP/PS1). We found lactic acid levels were significantly elevated in these cells and tissues compared to their corresponding counterparts, which increased the level of pan histone lysine lactylation (Kla). We aslo identified all histone Kla sites in senescent microglia, and found that both the H3K18 lactylation (H3K18la) and Pan-Kla were significantly up-regulated in senescent microglia and hippocampus tissues of naturally aged mice and AD modeling mice. We demonstrated that enhanced H3K18la directly stimulates the NFκB signaling pathway by increasing binding to the promoter of Rela (p65) and NFκB1(p50), thereby upregulating senescence-associated secretory phenotype (SASP) components IL-6 and IL-8. Our study provides novel insights into the physiological function of Kla and the epigenetic regulatory mechanism that regulates brain aging and AD. Specifically, we have identified the H3K18la/NFκB axis as a critical player in this process by modulating IL-6 and IL-8. Targeting this axis may be a potential therapeutic strategy for delaying aging and AD by blunting SASP.

Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-ß and ISIMatusda in the middle-aged T2D individuals.

This study aims to investigate the correlations between islet function/ insulin resistance and serum lipid levels, as well as to assess whether the strength of such correlations is affected by the GCKR rs1260326 variant in healthy and T2D individuals. We performed an oral glucose tolerance test (OGTT) on 4889 middle-aged adults, including 3135 healthy and 1754 T2D individuals from the REACTION population study in the Nanjing region. We also measured their serum lipid levels and genotyped for rs1260326. We found that serum high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels were independently correlated with indexes of islet function (HOMA-ß and IGI [insulinogenic index]) and insulin resistance (HOMO-IR and ISIMatsuda) in both healthy and T2D individuals. The correlations were significantly decreased in T2D individuals, with significant heterogeneities compared to healthy controls (I2 > 75%, Phet < 0.05). Although no correlation was observed between serum total cholesterol (TC) level and islet function/ insulin resistance in healthy controls, significant correlations were found in T2D individuals, with significant heterogeneity to healthy controls in the correlation with ISIMatsuda(I2 = 85.3%, Phet = 0.009). Furthermore, we found significant interactions of the GCKR rs1260326 variant for the correlations between serum HDL cholesterol and HOMA-ß/ISIMatsuda in T2D subjects (P = 0.015 and 0.038, respectively). These findings illustrate that distinct correlations between serum lipid levels and islet function/ insulin resistance occurred in T2D subjects compared to healthy individuals. Common gene variants, such as rs1260326, might interact substantially when studied in specific populations, especially T2D disease status.

Epileptic detection in single and multi-lead EEG signals using persistent homology based on bi-directional weighted visibility graphs.

Epilepsy is a widespread neurological disorder, and its recurrence and suddenness are making automatic detection of seizure an urgent necessity. For this purpose, this paper performs topological data analysis (TDA) of electroencephalographic (EEG) signals by the medium of graphs to explore the potential brain activity information they contain. Through our innovative method, we first map the time series of epileptic EEGs into bi-directional weighted visibility graphs (BWVGs), which give more comprehensive reflections of the signals compared to previous existing structures. Traditional graph-theoretic measurements are generally partial and mainly consider differences or correlations in vertices or edges, whereas persistent homology (PH), the essential part of TDA, provides an alternative way of thinking by quantifying the topology structure of the graphs and analyzing the evolution of these topological properties with scale changes. Therefore, we analyze the PH for BWVGs and then obtain the two indicators of persistence and birth-death for homology groups to reflect the topology of the mapping graphs of EEG signals and reveal the discrepancies in brain dynamics. Furthermore, we adopt neural networks (NNs) for the automatic detection of epileptic signals and successfully achieve a classification accuracy of 99.67% when distinguishing among three different sets of EEG signals from seizure, seizure-free, and healthy subjects. In addition, to accommodate multi-leads, we propose a classifier that incorporates graph structure to distinguish seizure and seizure-free EEG signals. The classification accuracies of the two subjects used in the classifier are as high as 99.23% and 94.76%, respectively, indicating that our proposed model is useful for the analysis of EEG signals.

TSRRNet: two-stage reflection removal network with reflective guidance.

Due to the shortage of paired images, the training of reflection removal networks relies heavily on synthesized samples, for which the ground truths of transmission and reflection are both known. But most existing CNN-based models cannot fully utilize the reflection information, which may cause performance limitations. In this paper, our goal is to design a novel, to the best of our knowledge, network that can take the reflection layer to refine the transmission layer. To this end, we propose a two-stage generative-adversarial-network-based network, where the first stage is used to obtain the coarse estimation of transmission and reflection, and the second stage is used to achieve the refinement. In addition, instead of just applying two penalty terms on the two coarse predictions in previous works, we consider the coarse reflection as a soft mask overlapped on the transmission and apply the recently proposed gated convolution into the second stage for further refinement. The network is trained with an adversarial frame using WGAN. The experimental results with benchmark datasets indicate that our method outperforms several state-of-the-art networks.

UBE3A alleviates isoproterenol-induced cardiac hypertrophy through the inhibition of the TLR4/MMP-9 signaling pathway.

Cardiac hypertrophy is considered to be a leading factor in heart function-related deaths. In this study, we explored the potential mechanism underlying cardiac hypertrophy induced by isoproterenol. Our results showed that isoproterenol induced cardiac hypertrophy in AC16 cells, as reflected by the increased cell surface area and increased hypertrophic markers, which was accompanied by increased ubiquitin-protein ligase E3a (UBE3A) expression. Moreover, UBE3A knockdown by siRNAs accelerated cardiac hypertrophy, suggesting that increased UBE3A expression induced by isoproterenol might be a protective response and UBE3A might be a protective factor against cardiac hypertrophy. Our study also revealed that UBE3A knockdown increased the protein expression of the TLR4/MMP-9 pathway that has been shown to be associated with cardiac hypertrophy, which suggested that UBE3A-mediated protection is likely to be associated with the blockade of the TLR4/MMP-9 signaling pathway. UBE3A might be thus a potential target gene for the treatment of cardiac hypertrophy.

A COVID-19 Risk Assessment Decision Support System for General Practitioners: Design and Development Study.

BACKGROUND: The coronavirus disease (COVID-19) has become an urgent and serious global public health crisis. Community engagement is the first line of defense in the fight against infectious diseases, and general practitioners (GPs) play an important role in it. GPs are facing unique challenges from disasters and pandemics in delivering health care. However, there is still no suitable mobile management system that can help GPs collect data, dynamically assess risks, and effectively triage or follow-up with patients with COVID-19. OBJECTIVE: The aim of this study is to design, develop, and deploy a mobile-based decision support system for COVID-19 (DDC19) to assist GPs in collecting data, assessing risk, triaging, managing, and following up with patients during the COVID-19 outbreak. METHODS: Based on the actual scenarios and the process of patients using health care, we analyzed the key issues that need to be solved and designed the main business flowchart of DDC19. We then constructed a COVID-19 dynamic risk stratification model with high recall and clinical interpretability, which was based on a multiclass logistic regression algorithm. Finally, through a 10-fold cross-validation to quantitatively evaluate the risk stratification ability of the model, a total of 2243 clinical data consisting of 36 dimension clinical features from fever clinics were used for training and evaluation of the model. RESULTS: DDC19 is composed of three parts: mobile terminal apps for the patient-end and GP-end, and the database system. All mobile terminal devices were wirelessly connected to the back end data center to implement request sending and data transmission. We used low risk, moderate risk, and high risk as labels, and adopted a 10-fold cross-validation method to evaluate and test the COVID-19 dynamic risk stratification model in different scenarios (different dimensions of personal clinical data accessible at an earlier stage). The data set dimensions were (2243, 15) when only using the data of patients' demographic information, clinical symptoms, and contact history; (2243, 35) when the results of blood tests were added; and (2243, 36) after obtaining the computed tomography imaging results of the patient. The average value of the three classification results of the macro-area under the curve were all above 0.71 in each scenario. CONCLUSIONS: DCC19 is a mobile decision support system designed and developed to assist GPs in providing dynamic risk assessments for patients with suspected COVID-19 during the outbreak, and the model had a good ability to predict risk levels in any scenario it covered.

Establishment of clinical diagnosis model of Graves' disease and Hashimoto's thyroiditis.

BACKGROUND: A clinical diagnosis model include thyroid functions, thyroid antibodies and radioactive iodine uptake (RAIU) of patients with hyperthyroidism were established and as new evaluation indicators for the differentiation of the Graves' disease (GD) and Hashimoto's thyroiditis (HT). METHODS: Clinical data of patients with newly diagnosed hyperthyroidism including gender, age, thyroid function, thyroid antibodies (FT3, FT4, TSH, TPOAb, TGAb, TRAb), RAIU (2 h, 6 h, 24 h) were collected. A stepwise regression analysis was performed to establish a model based on these variables. RESULTS: Model 1 was subjected to stepwise regression analysis. After screening, the variables that entered the model included FT3, TGAb, TPOAb, TRAb, 2-h RAIU, 24-h RAIU and gender, in which the variables FT3, TGAb, TRAb, 2-h RAIU, 24-h RAIU, and gender were significantly different. Model 2 without RAIU was also subjected to stepwise regression analysis. After screening, the variables that entered the model included FT4, TGAb, TPOAb, TRAb and gender were statistical significant. The larger value of each variable in the two models indicated the higher probability to diagnose GD. The area under the receiver operating characteristic (ROC) curve of model 1 was 0.843 (95% CI 0.779-0.894), and the area under the ROC curve of model 2 was 0.806 (95% CI 0.685-0.824), which showed good differential diagnostic value. CONCLUSIONS: GD and HT diagnosis model was established according to the variables including gender, FT3, TGAb, TRAb, the 2-h RAIU, the 24-h RAIU in the model 1, and the variables FT4, TGAb, TPOAb, TRAb and gender in the model 2 that did not include RAIU. These models had high value to differentiate GD and HT for patients with early hyperthyroidism.

Impaired ß-cell function and decreased insulin sensitivity in subjects with normal oral glucose tolerance but isolated high glycosylated hemoglobin.

The pathophysiology is distinct in various state of glucose metabolism abnormalities. As the defect of individuals with normal oral glucose tolerance (NGT) but isolated high glycosylated hemoglobin (HbA1c), i.e. iHH, was ambiguous, we aimed to investigate the insulin sensitivity and ß-cell function of iHH. According to the ADA criteria of HbA1c cut-off point (5.7%), 3,517 subjects with NGT screened from a total of 7,855 middle-aged and elderly Chinese without known diabetes were divided into two groups, 1,877 subjects with HbA1c < 5.7% and 1,640 with HbA1c ≥ 5.7% (i.e. iHH). A variety of indexes from blood glucose and insulin levels of oral glucose tolerance were calculated to evaluate insulin sensitivity and ß-cell function. Compared with subjects with HbA1c < 5.7%, individuals with iHH had increased homeostasis model assessment of insulin resistance (HOMA-IR), early-phase and total insulin release indexes (insulin release index 30 min and 120 min, i.e. INRS30 and INSR120), and decreased Matsuda insulin sensitivity index (Matsuda ISI) and early-phase disposition index (DI30). After adjustment for confounding factors, the significant difference of HOMA-IR and INSR30 between the two groups vanished, however, Matsuda ISI and DI30 remained significantly lower and INSR120 was still higher in iHH group compared with HbA1c < 5.7%. In conculsion, subjects with NGT may not be perfectly healthy in glycometabolism, those with iHH have impaired early-phase ß-cell function and decreased insulin sensitivity.

The diagnostic value of TROP-2, SLP-2 and CD56 expression in papillary thyroid carcinoma.

OBJECTIVE: The study aimed to explore some novel diagnostic biomarkers for papillary thyroid carcinoma (PTC) by identifying the different expression of TROP-2, SLP-2 and CD56 in benign and malignant thyroid lesions. METHODS: We evaluated the mRNA expressions of TROP-2 and SLP-2 in fine needle aspirates (FNAs) which contained 10 PTCs and 10 benign follicular adenomas (FAs) using quantitative real-time PCR (qRT-PCR). Immunohistochemical (IHC) staining of TROP-2, SLP-2 and CD56 was also performed on postoperative samples of 30 PTCs and 29 FAs. Membranous or cytoplasmic staining in > 10% of cells was considered as positive. Diagnostic sensitivity, specificity, positive predictive value, negative predictive value (NPV) and diagnostic accuracy of these three biomarkers were carried out. We further analyzed the associations between the clinical features and the expressions of markers in PTCs. RESULTS: The mRNA expressions of both TROP-2 and SLP-2 were increased substantially in PTCs in comparison with those in FAs (P < 0.05). Similarly, IHC for these two proteins demonstrated higher positive staining in PTCs than in FAs (96.5% vs. 12.5% for TROP-2, 83.3% vs. 20.7% for SLP-2, P < 0.05). Conversely, CD56 expression was lost with 86.7% of PTCs. In identifying malignancy, TROP-2 was the most sensitive marker and CD56 was the most specific one. When the markers were combined, the sensitivity and NPV increased to 100% and had better diagnostic accuracy. However, no association was found between biomarker expressions and clinicopathological factors in PTCs. CONCLUSIONS: We found that TROP-2, SLP-2 and CD56 were effective diagnostic markers for PTC, especially when they were combined to use.

Coupled Node Similarity Learning for Community Detection in Attributed Networks.

Attributed networks consist of not only a network structure but also node attributes. Most existing community detection algorithms only focus on network structures and ignore node attributes, which are also important. Although some algorithms using both node attributes and network structure information have been proposed in recent years, the complex hierarchical coupling relationships within and between attributes, nodes and network structure have not been considered. Such hierarchical couplings are driving factors in community formation. This paper introduces a novel coupled node similarity (CNS) to involve and learn attribute and structure couplings and compute the similarity within and between nodes with categorical attributes in a network. CNS learns and integrates the frequency-based intra-attribute coupled similarity within an attribute, the co-occurrence-based inter-attribute coupled similarity between attributes, and coupled attribute-to-structure similarity based on the homophily property. CNS is then used to generate the weights of edges and transfer a plain graph to a weighted graph. Clustering algorithms detect community structures that are topologically well-connected and semantically coherent on the weighted graphs. Extensive experiments verify the effectiveness of CNS-based community detection algorithms on several data sets by comparing with the state-of-the-art node similarity measures, whether they involve node attribute information and hierarchical interactions, and on various levels of network structure complexity.

Health care resource utilization before and after perampanel initiation among patients with epilepsy in the United States.

OBJECTIVE: The purpose of this study was to evaluate changes in health care resource utilization following the initiation of perampanel for the treatment of epilepsy in the United States. METHODS: Health care claims from Symphony Health's Integrated Dataverse database between December 2012 and November 2015 were analyzed. Patients newly initiated on perampanel, having ≥1 epilepsy (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 345.xx, ICD-10-CM code G40.xxx) or nonfebrile convulsion (ICD-9-CM code 780.39, ICD-10-CM code R56.9) diagnosis, and having ≥6 months of baseline and observation periods were included. Patients <12 years old at perampanel initiation were excluded. RESULTS: Of the 2,508 perampanel patients included in the study, the mean [median] (±standard deviation [SD]) age was 35.8 [34] (±16.0) years and 56.2% were female. The mean [median] (±SD) observation duration was 459.8 [462] (±146.3) days in the postperampanel period. The postperampanel period was associated with significantly lower rates of all health care resource utilization outcomes than the pre-period. For the post- versus pre-period, perampanel users had 42.3 versus 53.8 overall hospitalizations per 100 person-years (rate ratio [RR] = 0.80, p < 0.001) and 1,240.2 versus 1,343.8 outpatient visits per 100 person-years (RR = 0.91, p < 0.001). Epilepsy-related hospitalizations and outpatient visits were 25.2 versus 33.6 per 100 person-years (RR = 0.76, p < 0.001) and 327.0 versus 389.0 per 100 person-years (RR = 0.84, p < 0.001), respectively. Additionally, a significantly lower rate of status epilepticus in the post-period (1.8 events per 100 person-years) was observed compared to the pre-period (4.4 events per 100 person-years; RR = 0.43, p < 0.001). The monthly time trend of hospitalizations showed an increasing trend leading up to the initiation of perampanel, after which the hospitalizations decreased steadily. SIGNIFICANCE: Use of perampanel for the treatment of epilepsy was associated with significant reduction in all-cause and epilepsy-related health care resource utilization, including hospitalizations, especially for status epilepticus, and outpatient visits.

Budget impact of perampanel as adjunctive treatment of uncontrolled partial-onset and primary generalized tonic-clonic seizures in the United States.

PURPOSE: To evaluate the budget impact (BI) of adopting perampanel for adjunctive treatment of partial-onset seizures (POS), with or without secondarily generalized seizures, and the adjunctive treatment of primary generalized tonic-clonic seizures (PGTCS) in patients 12years or older in the United States. METHODS: A BI model was developed to estimate the potential BI of adopting adjunctive perampanel from a US payer (direct costs only) and societal (direct and indirect costs) perspective over a 5-year period. Efficacy data for perampanel and antiepileptic drug (AED) maintenance therapy were obtained from perampanel phase III clinical trials. Drug, direct medical (healthcare provider, emergency room, and hospitalizations), and indirect (productivity loss) costs were obtained from appropriate sources (e.g., AnalySource® Online [wholesale acquisition costs], 2013 Optum Insight Clinformatics Database [market share percentages, direct medical costs per unit], and 2011-2013 National Health and Wellness Survey [NHWS; healthcare resource utilization, overall work impairment, and baseline distribution of patients across the 4 health states]). Mapping of seizure frequency to medical resource utilization and work impairment was obtained from Kantar Health's NHWS. RESULTS: In a hypothetical health plan of 1 million members, 660 (0.066%) members ≥12years old had uncontrolled POS (395 [59.8%]) or PGTCS (265 [40.2%]). During the first 5years of adoption of perampanel, absolute BI (including drug, direct medical, and indirect costs) was $852, $2124, $3855, $5318, and $6397, respectively, for a cumulative absolute BI of $18,545. Drug cost was estimated to increase by $13,888, $34,646, $62,863, $86,728, and $104,326, respectively; however, this cost would be mostly offset by decreases in direct medical ($5041, $12,576, $22,818, $31,481, and $37,869, respectively) and indirect ($7995, $19,946, $36,190, $49,929, and $60,060, respectively) costs. Total per-member-per-month cost (drug and direct medical costs) was estimated to increase by $0.0007, $0.0018, $0.0033, $0.0046, and $0.0055 from years 1 to 5. CONCLUSIONS: Based on results of this BI model, increased cost of adopting perampanel in a health plan of 1 million members would be minimal for payers, and societal costs would be close to neutral.

Health-care costs and utilization related to long- or short-acting antiepileptic monotherapy use.

PURPOSE: This study aimed to compare health-care utilization and costs in patients treated with long-acting (LA) vs. short-acting (SA) antiepileptic drug (AED) monotherapy. METHODS: We conducted a cross-sectional study of claims from the OptumInsight™ database. Our analysis was restricted to adults diagnosed with epilepsy and who used AED monotherapy. Patients were excluded if they used >1 type of AED, had <9months of treatment, or had a treatment gap of >60days. Antiepileptic drugs were classified as LA or SA based on published data and expert opinion. Medical and pharmacy claims were used to estimate health-care utilization and costs, and baseline group differences were adjusted using multivariate analyses. RESULTS: There were 4058 (49.6%) LA AED users and 4122 (50.4%) SA AED users. Medication possession ratios (MPRs) were not significantly different between LA AED users and SA AED users (P=0.125). Long-acting AED users had lower mean overall health-care costs ($9757 vs. $12,689), lower epilepsy-related costs ($3539 vs. $5279), and lower rate of overall (8.8% vs. 10.9%) and epilepsy-related hospitalizations (5.7% vs. 7.6%) compared with SA AED users (all P<0.01). After adjusting for demographics and clinical characteristics, mean overall costs were lower by $686 and the mean epilepsy-related costs were lower by $894 in LA AED users. CONCLUSION: Although MPRs were similar in LA AED and SA AED groups, patients treated with LA monotherapy had a lower economic burden compared with those treated with SA monotherapy, indicating that using AEDs with extended duration of action is associated with decreased health-care use and lower health-care costs.

A Chinese risk score model for identifying postprandial hyperglycemia without oral glucose tolerance test.

BACKGROUND: The aim of the study is to develop a risk score model for identifying postprandial hyperglycemia without oral glucose tolerance tests (OGTT) in Chinese population, and minimize the number of subjects needing further OGTT. METHODS: Multivariable stepwise logistic regression was used to develop risk score models in a derivation cohort (7953 participants without known diabetes). The developed models were verified in a validation cohort (another 1455 subjects without known diabetes). All subjects had completed questionnaires, physical examination and OGTT. Performances of the risk score models were estimated using receiver operating characteristic curves. RESULTS: Two risk score models for screening postprandial hyperglycemia were developed. The simple model used non-invasive risk factors (age, height, weight, waist, systolic blood pressure, pulse, hypertension, dyslipidemia and family history of diabetes mellitus), and the full model contained additional variables [fasting blood glucose (FBG), triglyceride/high density lipoprotein cholesterol] obtainable by invasive laboratory tests. The area under receiver operating characteristic curve (AUC) of simple model was similar to FBG and glycated haemoglobin. The full model has the largest AUC [0.799 (0.789-0.809) and 0.730 (0.702-0.758)] in both derivation and validation cohorts (p < 0.001 compared with simple model, FBG, and glycated haemoglobin). At a cutoff point of 80, the sensitivity, specificity and percentage that needed subsequent OGTT were 75.97, 67.56 and 48.38%, respectively. CONCLUSIONS: We developed a risk score model for screening postprandial hyperglycemia based on routine clinical information. It could effectively identify patients at high-risk for postprandial hyperglycemia and remarkably reduce the number of subjects requiring OGTT.

Sunitinib in combination with trastuzumab for the treatment of advanced breast cancer: activity and safety results from a phase II study.

BACKGROUND: This phase II study evaluated the efficacy and safety/tolerability of sunitinib plus trastuzumab in patients with HER2-positive advanced breast cancer (ABC). METHODS: Eligible patients received sunitinib 37.5 mg/day and trastuzumab administered either weekly (loading, 4 mg/kg; then weekly 2 mg/kg) or 3-weekly (loading, 8 mg/kg; then 3-weekly 6 mg/kg). Prior trastuzumab and/or lapatinib treatment were permitted. The primary endpoint was objective response rate (ORR). RESULTS: Sixty patients were enrolled and evaluable for safety; 57 were evaluable for efficacy. The majority of patients (58%) had received no prior chemotherapy in the metastatic setting. The ORR was 37%; the clinical benefit rate (CBR; percent objective response plus stable disease ≥ 24 weeks) was 56%. Among patients who were treatment-naïve or had received only adjuvant therapy, the ORR was 44% and the CBR was 59%. Overall, median overall survival had not been reached and the 1-year survival rate was 91%. The majority of adverse events (AEs) were mild to moderate in severity. Forty percent of patients experienced AEs related to measured left ventricular ejection fraction (LVEF) declines, which occurred more frequently in patients who had received prior anthracycline treatment. Ten percent of patients exhibited symptoms related to LVEF declines. One patient died on study from cardiogenic shock. Antitumor response and several safety parameters appeared to correlate with sunitinib exposure. CONCLUSIONS: Sunitinib plus trastuzumab demonstrated antitumor activity in patients with HER2-positive ABC, particularly those who were treatment-naïve or had only received prior adjuvant treatment. Sunitinib plus trastuzumab had acceptable safety and tolerability in patients with HER2-positive ABC who had not received prior anthracycline therapy. TRIAL REGISTRATION: NCT00243503.