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During spring, migratory birds are required to optimally balance energetic costs of migration across heterogeneous landscapes and weather conditions to survive and reproduce successfully. Therefore, an individual's migratory performance may influence reproductive outcomes. Given large-scale changes in land use, climate, and potential carry-over effects, understanding how individuals migrate in relation to breeding outcomes is critical to predicting how future scenarios may affect populations. We used GPS tracking devices on 56 Greater White-fronted Geese (Anser albifrons) during four spring migrations to examine whether migration characteristics influenced breeding propensity and breeding outcome. We found a strong longitudinal difference in arrival to the breeding areas (18 days earlier), pre-nesting duration (90.9% longer), and incubation initiation dates (9 days earlier) between western- and eastern-Arctic breeding regions, with contrasting effects on breeding outcomes, but no migration characteristic strongly influenced breeding outcome. We found that breeding region influenced whether an individual likely pursued a capital or income breeding strategy. Where individuals fell along the capital-income breeding continuum was influenced by longitude, revealing geographic effects of life-history strategy among conspecifics. Factors that govern breeding outcomes likely occur primarily upon arrival to breeding areas or are related to individual quality and previous breeding outcome, and may not be directly tied to migratory decision-making across broad scales.

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The spatial availability of social resources is speculated to structure animal movement decisions, but the effects of social resources on animal movements are difficult to identify because social resources are rarely measured. Here, we assessed whether varying availability of a key social resource-access to receptive mates-produces predictable changes in movement decisions among bighorn sheep in Nevada, the United States. We compared the probability that males made long-distance 'foray' movements, a critical driver of connectivity, across three ecoregions with varying temporal duration of a socially mediated factor, breeding season. We used a hidden Markov model to identify foray events and then quantified the effects of social covariates on the probability of foray using a discrete choice model. We found that males engaged in forays at higher rates when the breeding season was short, suggesting that males were most responsive to the social resource when its existence was short lived. During the breeding season, males altered their response to social covariates, relative to the non-breeding season, though patterns varied, and age was associated with increased foray probability. Our results suggest that animals respond to the temporal availability of social resources when making the long-distance movements that drive connectivity. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

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Background: The HIMALAYA trial found that durvalumab plus tremelimumab significantly prolonged progression-free survival and overall survival in patients with unresectable hepatocellular carcinoma (HCC) compared with sorafenib. Objective: This study aimed to investigate the cost-effectiveness of durvalumab plus tremelimumab compared with sorafenib in the first-line HCC setting. Design: A Markov model-based cost-effectiveness analysis. Methods: We created a Markov model to compare healthcare costs and clinical outcomes of HCC patients treated with durvalumab plus tremelimumab in the first-line setting compared with sorafenib. We estimated transition probabilities from randomized trials. Lifetime direct healthcare costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios were calculated for first-line durvalumab plus tremelimumab compared with sorafenib from a US payer's perspective. Results: In the base case, first-line durvalumab plus tremelimumab was associated with an improvement of 0.29 QALYs compared with sorafenib. While both treatment strategies were associated with considerable lifetime expenditures, first-line durvalumab plus tremelimumab was less expensive than sorafenib ($188,405 vs $218,584). The incremental net monetary benefit for durvalumab plus tremelimumab versus sorafenib was $72,762 (valuing QALYs at $150,000 each). The results of durvalumab plus tremelimumab were better in terms of costs and health outcomes in patients with HBV-related HCC and high alpha-fetoprotein levels. Conclusion: First-line durvalumab plus tremelimumab was estimated to be dominant for the treatment of unresectable HCC compared with sorafenib from a US payer's perspective.

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Groundwater pollution risk evaluation is an important basis for developing groundwater protection measures and management strategies, and its accuracy directly affects the effectiveness of protection measures. The heterogeneity of the aquifer significantly affects the transport process of pollutants, increasing the uncertainty of pollutant risk assessment. However, in the actual site, borehole data that reveal aquifer heterogeneity are costly, and only a limited number of borehole data are available, which cannot accurately describe the heterogeneity of the aquifer, thus limiting the accuracy of groundwater pollution risk assessment. In order to overcome the above problems, this paper proposes a groundwater pollution risk assessment framework based on the stochastic and deterministic simulation of aquifer lithology. Based on the statistical characteristics of the change of lithology type in the actual borehole, the framework uses Markov chain to generate some sets of random lithology field and transforms them into heterogeneity parameter field, so as to realize the stochastic assessment of the pollution risk of groundwater resource wells. Furthermore, combined with the pumping test data, the parameter field that is most suitable for the actual situation is selected to evaluate the pollution risk deterministically. Finally, the stochastic and deterministic results are combined to comprehensively evaluate the pollution risk of groundwater resource wells. Through a case study in a river valley plain, the feasibility of the above framework is verified, and good application effects are achieved. This study provides a feasible method for accurately assessing groundwater pollution risk, which is helpful to reduce the impact of uncertain factors on pollution risk assessment, and thus provides a more reliable basis for groundwater management and decision-making.

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BACKGROUND: There is growing interest in understanding the dynamic functional connectivity (DFC) between distributed brain regions. However, it remains challenging to reliably estimate the temporal dynamics from resting-state functional magnetic resonance imaging (rs-fMRI) due to the limitations of current methods. NEW METHODS: We propose a new model called HDP-HSMM-BPCA for sparse DFC analysis of high-dimensional rs-fMRI data, which is a temporal extension of probabilistic principal component analysis using Bayesian nonparametric hidden semi-Markov model (HSMM). Specifically, we utilize a hierarchical Dirichlet process (HDP) prior to remove the parametric assumption of the HMM framework, overcoming the limitations of the standard HMM. An attractive superiority is its ability to automatically infer the state-specific latent space dimensionality within the Bayesian formulation. RESULTS: The experiment results of synthetic data show that our model outperforms the competitive models with relatively higher estimation accuracy. In addition, the proposed framework is applied to real rs-fMRI data to explore sparse DFC patterns. The findings indicate that there is a time-varying underlying structure and sparse DFC patterns in high-dimensional rs-fMRI data. COMPARISON WITH EXISTING METHODS: Compared with the existing DFC approaches based on HMM, our method overcomes the limitations of standard HMM. The observation model of HDP-HSMM-BPCA can discover the underlying temporal structure of rs-fMRI data. Furthermore, the relevant sparse DFC construction algorithm provides a scheme for estimating sparse DFC. CONCLUSION: We describe a new computational framework for sparse DFC analysis to discover the underlying temporal structure of rs-fMRI data, which will facilitate the study of brain functional connectivity.

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BACKGROUND: Tislelizumab combined with chemotherapy has shown significant clinical benefits in improving overall survival compared to chemotherapy alone for patients with extensive-stage small-cell lung cancer (ES-SCLC). AIM: This study aimed to evaluate the cost-effectiveness of tislelizumab plus chemotherapy versus standard chemotherapy as a first-line treatment for ES-SCLC from the US payer perspective and the perspective of the Chinese healthcare system. METHOD: We conducted an economic evaluation using a Markov state-transition model, reflecting the US payer perspective and the perspective of the Chinese healthcare system. Baseline patient characteristics and essential clinical data were obtained from the RATIONALE-312 trial. The costs and utilities were derived from open-access databases and published literature. The primary outcomes measured included quality-adjusted life years (QALYs), incremental cost-effectiveness ratio (ICER), incremental net health benefit (INHB), and incremental net monetary benefit (INMB). Uncertainties in the model were addressed by probabilistic sensitivity analysis (PSA) and one-way sensitivity analysis (OWSA). RESULTS: In the base-case analysis, the addition of tislelizumab to chemotherapy provided an incremental gain of 0.16 QALYs at an additional cost of $7430.73, resulting in an ICER of $46,132.33 per QALY. Although above the willingness-to-pay (WTP) threshold of China of $38,042.49 per QALY, the cost-effectiveness was marginal, with an INHB of - 0.03 QALYs and an INMB of $- 1303.06. In the US, despite a slightly higher effectiveness gain of 0.28 QALYs, the increased cost of $45,157.35 resulted in an unfavorable ICER of $163,885.06 per QALY, exceeding the US WTP threshold of $150,000.00. PSA showed probabilities of cost-effectiveness of tislelizumab plus chemotherapy at 17.18% in China and 40.41% in the US. CONCLUSION: Tislelizumab combined with chemotherapy was not a cost-effective first-line treatment option for ES-SCLC in China or the US; however, the margin of cost-effectiveness was narrow.

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Gaussia luciferase (Gluc) is currently known as the smallest naturally secreted luciferase. Due to its small molecular size, high sensitivity, short half-life, and high secretion efficiency, it has become an ideal reporter gene and is widely used in monitoring promoter activity, studying protein-protein interactions, protein localization, high-throughput drug screening, and real-time monitoring of tumor occurrence and development. Although studies have shown that different Gluc mutations exhibit different bioluminescent properties, their mechanisms have not been further investigated. The purpose of this study is to reveal the relationship between the conformational changes of Gluc mutants and their bioluminescent properties through molecular dynamics simulation combined with neural relationship inference (NRI) and Markov models. Our results indicate that, after binding to the luciferin coelenterazine (CTZ), the α-helices of the 109-119 residues of the Gluc Mutant2 (GlucM2, the flash-type mutant) are partially unraveled, while the α-helices of the same part of the Gluc Mutant1 (GlucM1, the glow-type mutant) are clearly formed. The results of Markov flux analysis indicate that the conformational differences between glow-type and flash-type mutants when combined with luciferin substrate CTZ mainly involve the helicity change of α7. The most representative conformation and active pocket distance analysis indicate that compared to the flash-type mutant GlucM2, the glow-type mutant GlucM1 has a higher degree of active site closure and tighter binding. In summary, we provide a theoretical basis for exploring the relationship between the conformational changes of Gluc mutants and their bioluminescent properties, which can serve as a reference for the modification and evolution of luciferases.

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Sleep is a complex biological process regulated by networks of neurons and environmental factors. As one falls asleep, neurotransmitters from sleep-wake regulating neurones work in synergy to control the switching of different sleep states throughout the night. As sleep disorders or underlying neuropathology can manifest as irregular switching, analysing these patterns is crucial in sleep medicine and neuroscience. While hypnograms represent the switching of sleep states well, current analyses of hypnograms often rely on oversimplified temporal descriptive statistics (TDS, e.g., total time spent in a sleep state), which miss the opportunity to study the sleep state switching by overlooking the complex structures of hypnograms. In this paper, we propose analysing sleep hypnograms using a seven-state continuous-time Markov model (CTMM). This proposed model leverages the CTMM to depict the time-varying sleep-state transitions, and probes three types of insomnia by distinguishing three types of wake states. Fitting the proposed model to data from 2056 ageing adults in the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study, we profiled sleep architectures in this population and identified the various associations between the sleep state transitions and demographic factors and subjective sleep questions. Ageing, sex, and race all show distinctive patterns of sleep state transitions. Furthermore, we also found that the perception of insomnia and restless sleep are significantly associated with critical transitions in the sleep architecture. By incorporating three wake states in a continuous-time Markov model, our proposed method reveals interesting insights into the relationships between objective hypnogram data and subjective sleep quality assessments.

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Rotavirus (RV) vaccines have demonstrated substantial effectiveness in reducing the healthcare burden caused by gastroenteritis (RVGE) worldwide. This study aims to understand the differential impact of RV vaccination in reducing RVGE burden in children under 7 years old in China. A Markov Model was used to investigate the health impact of introducing two different RV vaccines into the Chinese population. The analysis was conducted for RV5, a live pentavalent human-bovine reassortant vaccine, and Lanzhou Lamb RV (LLR), a live-attenuated monovalent RV vaccine, separately, by comparing the strategy of each vaccine to no vaccination within a Chinese birth cohort, including 100,000 children modeled until 7 years of age. The vaccination scenario assumed a vaccination coverage of 2.5%, 2.5%, 90% and 5% for doses one, two, three and no vaccine, respectively, for both vaccines. Strategies with RV5, LLR, and no vaccination were associated with 9,895, 49,069, and 64,746 symptomatic RV infections, respectively. RV5 and LLR were associated with an 85% and 24% reduction in the total symptomatic RV infections, respectively, suggesting that the health benefits of RV5 are at least three-fold greater than those associated with the LLR. Further, strategies with RV5 and LLR resulted in an estimated 206 and 59-year increase in quality-adjusted life years (QALYs), respectively. Sensitivity and scenario analyses supported the robustness of the base-case findings. Use of RV vaccine is expected to improve RV-associated health outcomes and its adoption will help alleviate the burden of RVGE in China. RV5 use will result in significantly better health outcomes.

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The characterisation of resting-state networks (RSNs) using neuroimaging techniques has significantly contributed to our understanding of the organisation of brain activity. Prior work has demonstrated the electrophysiological basis of RSNs and their dynamic nature, revealing transient activations of brain networks with millisecond timescales. While previous research has confirmed the comparability of RSNs identified by electroencephalography (EEG) to those identified by magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), most studies have utilised static analysis techniques, ignoring the dynamic nature of brain activity. Often, these studies use high-density EEG systems, which limit their applicability in clinical settings. Addressing these gaps, our research studies RSNs using medium-density EEG systems (61 sensors), comparing both static and dynamic brain network features to those obtained from a high-density MEG system (306 sensors). We assess the qualitative and quantitative comparability of EEG-derived RSNs to those from MEG, including their ability to capture age-related effects, and explore the reproducibility of dynamic RSNs within and across the modalities. Our findings suggest that both MEG and EEG offer comparable static and dynamic network descriptions, albeit with MEG offering some increased sensitivity and reproducibility. Such RSNs and their comparability across the two modalities remained consistent qualitatively but not quantitatively when the data were reconstructed without subject-specific structural MRI images.

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Background: NVX-CoV2373 is one of the vaccines marketed for COVID-19 prevention in Japan. Information on its cost-effectiveness is important for making well-informed decisions on the future of Japan's COVID-19 vaccination programme from the public healthcare payer's perspective. The aim of this study was to evaluate the cost-effectiveness of NVX-CoV2373 vaccination in the elderly Japanese population. Methods: Two analysis populations that included elderly Japanese individuals (aged ≥ 65 years) were defined in this study: those who had not received a COVID-19 vaccine or had not completed a primary vaccination series (i.e., first two vaccinations) with an approved COVID-19 vaccine (analysis population 1), and those who had received two primary vaccinations with an approved COVID-19 vaccine (analysis population 2). A literature-informed Markov model for each analysis population was developed to evaluate the cost-effectiveness of vaccination with NVX-CoV2373 against no vaccination with NVX-CoV2373 from the public healthcare payer's perspective as a base-case analysis and from the societal perspective as a scenario analysis. Vaccine efficacy was estimated from a phase 3 study of NVX-CoV2373 (EudraCT number: 2020-004123-16). Cost-effectiveness was assessed using a willingness-to-pay threshold of Japanese yen (JPY) 5 million per quality-adjusted life-year (QALY). Deterministic and probabilistic sensitivity analyses were also performed. Results: For analysis population 1, NVX-CoV2373 primary and booster vaccinations would reduce costs by JPY 37,647 and prolong QALYs by 0.01601. Therefore, NVX-CoV2373 primary and booster vaccinations were considered to be dominant over no vaccination. For analysis population 2, an NVX-CoV2373 booster vaccination would increase costs by JPY 5010 and prolong QALYs by 0.00550, with the incremental cost-effectiveness ratio of JPY 910,566 per QALY gained. Conclusions: Our analyses suggest that a vaccination strategy with NVX-CoV2373 is cost-effective in the elderly population (aged ≥ 65 years) of Japan.

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In movement analysis, correlated random walk (CRW) models often use so-called turning angles, which are measured relative to the previous movement direction. To segregate between different movement modes, hidden Markov models (HMMs) describe movements as piecewise stationary CRWs in which the distributions of turning angles and step sizes depend on the underlying state. This typically allows for the segregation of movement modes that show different movement speeds. We show that in some cases, it may be interesting to investigate absolute angles, that is, biased random walks (BRWs) instead of turning angles. In particular, while discrimination between states in the turning angle setting can only rely on movement speed, models with absolute angles can be used to discriminate between sections of different movement directions. A preprocessing algorithm is provided that enables the analysis of absolute angles in the existing R package moveHMM. In a data set of movements of cell organelles, models using not the turning angle but the absolute angle could capture interesting additional properties. Goodness-of-fit was increased for HMMs with absolute angles, and HMMs with absolute angles tended to choose a higher number of states, suggesting the existence and relevance of prominent directional changes in the present data set. These results suggest that models with absolute angles can provide important information in the analysis of movement patterns if the existence and frequency of directional changes is of biological importance.

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Female genital schistosomiasis is a chronic gynaecological disease caused by the waterborne parasite Schistosoma (S.) haematobium. It affects an estimated 30-56 million girls and women globally, mostly in sub-Saharan Africa where it is endemic, and negatively impacts their sexual and reproductive life. Recent studies found evidence of an association between female genital schistosomiasis and increased prevalence of HIV and cervical precancer lesions. Despite the large population at risk, the burden and impact of female genital schistosomiasis are scarcely documented, resulting in neglect and insufficient resource allocation. There is currently no standardised method for individual or population-based female genital schistosomiasis screening and diagnosis which hinders accurate assessment of disease burden in endemic countries. To optimise financial allocations for female genital schistosomiasis screening, it is necessary to explore the cost-effectiveness of different strategies by combining cost and impact estimates. Yet, no economic evaluation has explored the value for money of alternative screening methods. This paper describes a novel application of health decision analytical modelling to evaluate the cost-effectiveness of different female genital schistosomiasis screening strategies across endemic settings. The model combines a decision tree for female genital schistosomiasis screening strategies, and a Markov model for the natural history of cervical cancer to estimate the cost per disability-adjusted life-years averted for different screening strategies, stratified by HIV status. It is a starting point for discussion and for supporting priority setting in a data-sparse environment.

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Background: Tislelizumab is the first PD-1 inhibitor in China to demonstrate superior efficacy in second-line or third-line treatment of patients with advanced or metastatic non-small-cell lung cancer (NSCLC). This study aimed to evaluate the cost-effectiveness of tislelizumab compared to docetaxel from a Chinese healthcare system perspective. Methods: A dynamic Markov model was developed to evaluate the cost-effectiveness of tislelizumab in comparison to docetaxel in second or third-line treatment. The efficacy data utilized in the model were derived from the RATIONALE-303 clinical trial, while cost and utility values were obtained from the drug data service platform and published studies. The primary outcomes of the model encompassed quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to validate the robustness of the base case analysis results. Results: The tislelizumab group demonstrated a cost increase of CNY 117,473 and a gain of 0.58 QALYs compared to the docetaxel group, resulting in an ICER value of CNY 202,927 per QALY gained. Conclusion: The administration of tislelizumab in patients with advanced or metastatic NSCLC not only extends the progression-free survival (PFS) and overall survival (OS). Moreover, this treatment demonstrates a favorable cost-effectiveness profile across the Chinese population.

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Background: Point-of-care Testing (POCT) glycosylated hemoglobin (HbA1c) is a convenient, cheap, effective and accessible screening method for type 2 diabetes in rural areas and community settings that is widely used in the European region and Japan, but not yet widespread in China. The study is the first to evaluate the cost-effectiveness of POCT HbA1c, fasting capillary glucose (FCG), and venous blood HbA1c to screen for type 2 diabetes in urban and rural areas of China, and to identify the best socio-economically beneficial screening strategy. Methods: Based on urban and rural areas in China, economic models for type 2 diabetes screening were constructed from a social perspective. The subjects of this study were adults aged 18-80 years with undiagnosed type 2 diabetes. Three screening strategies were established for venous blood HbA1c, FCG and POCT HbA1c, and cost-effectiveness analysis was performed by Markov models. One-way sensitivity analysis and probabilistic sensitivity analysis were performed on all parameters of the model to verify the stability of the results. Results: Compared with FCG, POCT HbA1c was cost-effective with an incremental cost-utility ratio (ICUR) of $500.06/quality-adjusted life year (QALY) in urban areas and an ICUR of $185.10/QALY in rural areas, within the willingness-to-pay threshold (WTP = $37,653). POCT HbA1c was cost-effective with lower cost and higher utility compared with venous blood HbA1c in both urban and rural areas. In the comparison of venous blood HbA1c and FCG, venous blood HbA1c was cost-effective (ICUR = $20,833/QALY) in urban areas but not in rural areas (ICUR = $41,858/QALY). Sensitivity analyses showed that the results of the study were stable and credible. Conclusions: POCT HbA1c was cost-effective for type 2 diabetes screening in both urban and rural areas of China, which could be considered for future clinical practice in China. Factors such as geographic location, local financial situation and resident compliance needed to be considered when making the choice of venous blood HbA1c or FCG.

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BACKGROUD: Temporal lobe epilepsy (TLE) is associated with abnormal dynamic functional connectivity patterns, but the dynamic changes in brain activity at each time point remain unclear, as does the potential molecular mechanisms associated with the dynamic temporal characteristics of TLE. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 84 TLE patients and 35 healthy controls (HCs). The data was then used to conduct HMM analysis on rs-fMRI data from TLE patients and an HC group in order to explore the intricate temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI). Additionally, we aim to examine the gene expression profiles associated with the dynamic modular characteristics in TLE patients using the Allen Human Brain Atlas (AHBA) database. RESULTS: Five HMM states were identified in this study. Compared with HCs, TLE and TLE-CI patients exhibited distinct changes in dynamics, including fractional occupancy, lifetimes, mean dwell time and switch rate. Furthermore, transition probability across HMM states were significantly different between TLE and TLE-CI patients (p < 0.05). The temporal reconfiguration of states in TLE and TLE-CI patients was associated with several brain networks (including the high-order default mode network (DMN), subcortical network (SCN), and cerebellum network (CN). Furthermore, a total of 1580 genes were revealed to be significantly associated with dynamic brain states of TLE, mainly enriched in neuronal signaling and synaptic function. CONCLUSIONS: This study provides new insights into characterizing dynamic neural activity in TLE. The brain network dynamics defined by HMM analysis may deepen our understanding of the neurobiological underpinnings of TLE and TLE-CI, indicating a linkage between neural configuration and gene expression in TLE.

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BACKGROUND: Forecasting the intensity, source, and cost of informal care for older adults in China is essential to establish and enhance policy support systems for informal care within the context of East Asian traditional culture that emphasizes filial piety. This study aims to analyze the current situation and influencing factors for the informal care needs and predict the trends of informal care needs for older adults in China from 2020 to 2040. METHODS: Using the CHARLS database from 2015 to 2018, this study first combined a two-part model and a multinomial logit to analyze the influencing factors for the informal care needs of urban-rural older adults in China. Secondly, a multi-state Markov model was constructed to forecast the number of urban-rural older populations in each health state from 2020 to 2040. Finally, based on a microsimulation model, this study predicted the trends of informal care intensity, source, and cost for older adults in urban and rural areas from 2020 to 2040. RESULTS: In 2040, the size of the disabled older population in China will expand further. In rural areas, the total number of disabled people in 2040 (39.77 million) is 1.50 times higher than that in 2020; In urban areas, the total number of disabled people in 2040 (56.01 million) is 2.51 times higher than that in 2020. Compared with 2020, older adults population with mild, moderate and severe disability in 2040 would increase by 87.60%, 101.70%, and 115.08%, respectively. In 2040, the number of older adults receiving low-, medium-, and high-intensity care in China will be 38.60 million, 22.89 million, and 41.69 million, respectively, and older people will still rely on informal care provided by spouses and children (from spouses only: 39.26 million, from children only: 36.74 million, from spouses and children only: 16.79 million, other: 10.39 million). The total cost of informal care in 2040 will be 1,086.65 billion yuan, 2.22 times that of 2020 (490.31 billion yuan), which grows faster than the economic growth rate. CONCLUSION: From 2020 to 2040, the informal care needs of older people in rural areas will increase first and then decrease due to the demographic structure and rapid urbanization. In contrast, the informal care needs of older people in urban areas will continuously increase from 2020 to 2040, with the growth rate gradually slowing down. This study provides an evidence-based rationale for scientifically measuring the economic value of informal care and reasonably allocating care resources.

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OBJECTIVES: Recently, the IMmotion151 trial evaluated the safety and efficacy of atezolizumab plus bevacizumab in metastatic renal cell carcinoma (mRCC) and found that this combination led to longer progression-free survival. However, no studies have evaluated the cost-effectiveness of atezolizumab plus bevacizumab. METHODS: We constructed a Markov model to evaluate the cost-effectiveness of atezolizumab plus bevacizumab, using costs and utilities from the published studies. We set the willingness-to-pay (WTP) threshold at $150,000. One-way and probabilistic sensitivity analyses were performed to ensure that our results were robust. We performed a threshold analysis to explore a more appropriate price for atezolizumab. RESULTS: Our results found that although atezolizumab plus bevacizumab provided more quality-adjusted life years (QALYs), its incremental cost-effectiveness ratio (ICER) was $1,640,532/QALY, well above the WTP threshold. One-way and probabilistic sensitivity analysis results confirmed the robust of this conclusion. Based on the threshold analysis, for atezolizumab plus bevacizumab to be cost-effective, the price of them would need to be reduced by 46.3% or more. CONCLUSIONS: From the perspective of US payers, atezolizumab plus bevacizumab is not cost-effective for mRCC patients. To make this combination cost-effective in the future, the price of atezolizumab and bevacizumab needs to be reduced.

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Feature representations with rich topic information can greatly improve the performance of story segmentation tasks. VAEGAN offers distinct advantages in feature learning by combining variational autoencoder (VAE) and generative adversarial network (GAN), which not only captures intricate data representations through VAE's probabilistic encoding and decoding mechanism but also enhances feature diversity and quality via GAN's adversarial training. To better learn topical domain representation, we used a topical classifier to supervise the training process of VAEGAN. Based on the learned feature, a segmentor splits the document into shorter ones with different topics. Hidden Markov model (HMM) is a popular approach for story segmentation, in which stories are viewed as instances of topics (hidden states). The number of states has to be set manually but it is often unknown in real scenarios. To solve this problem, we proposed an infinite HMM (IHMM) approach which utilized an HDP prior on transition matrices over countably infinite state spaces to automatically infer the state's number from the data. Given a running text, a Blocked Gibbis sampler labeled the states with topic classes. The position where the topic changes was a story boundary. Experimental results on the TDT2 corpus demonstrated that the proposed topical VAEGAN-IHMM approach was significantly better than the traditional HMM method in story segmentation tasks and achieved state-of-the-art performance.

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Background: Pembrolizumab is a potentially valuable treatment. However, patients, doctors, and healthcare decision-makers are uncertain about its cost-effectiveness and an appropriate pricing for this new therapy. This study aims to appraise the cost-effectiveness of pembrolizumab as a first-line treatment for advanced biliary tract cancer (BTC) patients in China and the United States (US). Methods: A Markov model was constructed from the perspectives of healthcare systems in both China and the US for pharmacoeconomic evaluation. Patient baseline characteristics and key clinical data were sourced from the KEYNOTE-966 trial (ClinicalTrials.gov, NCT04003636). Costs and utilities were collected from drug cost websites and published literature. Cumulative costs (in USD), life years (LYs), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) were measured and compared. Price simulations were conducted under given willingness-to-pay (WTP) thresholds to provide pricing scheme references. The model's robustness was analyzed through one-way sensitivity analysis and probabilistic sensitivity analysis. Results: Basic data analysis illustrates that pembrolizumab ($2662.41/100 mg) in combination with chemotherapy regimen was not cost-effective relative to chemotherapy regimens at the WTP threshold of $38,201.19 in China, and the additional cost relative to chemotherapy regimens was $77,114.94 (ICER $556,689.47/QALY) while increasing 0.14 QALYs. Pembrolizumab ($54.71/1 mg) also increased efficacy by 0.14 QALYs in the US, but remained also not cost-effective at the US WTP threshold of $229,044, and the total cost increased by $160,425.24 (ICER $1,109,462.92/QALY). Conclusion: Compared with chemotherapy, pembrolizumab plus chemotherapy reduces the disease of burden. However, at its current price, it may not be a cost-effective treatment for advanced BTC in both China and the US. This study can aid decision-makers in making optimal choices.