A powerful approach to identify replicable variants in genome-wide association studies.

Replicability is the cornerstone of modern scientific research. Reliable identifications of genotype-phenotype associations that are significant in multiple genome-wide association studies (GWASs) provide stronger evidence for the findings. Current replicability analysis relies on the independence assumption among single-nucleotide polymorphisms (SNPs) and ignores the linkage disequilibrium (LD) structure. We show that such a strategy may produce either overly liberal or overly conservative results in practice. We develop an efficient method, ReAD, to detect replicable SNPs associated with the phenotype from two GWASs accounting for the LD structure. The local dependence structure of SNPs across two heterogeneous studies is captured by a four-state hidden Markov model (HMM) built on two sequences of p values. By incorporating information from adjacent locations via the HMM, our approach provides more accurate SNP significance rankings. ReAD is scalable, platform independent, and more powerful than existing replicability analysis methods with effective false discovery rate control. Through analysis of datasets from two asthma GWASs and two ulcerative colitis GWASs, we show that ReAD can identify replicable genetic loci that existing methods might otherwise miss.

Cost-effectiveness of restorative treatments for permanent molars with severe molar incisor hypomineralization: perspectives for the Brazilian public health system.

OBJECTIVES: To undertake a cost-effectiveness analysis of restorative treatments for a first permanent molar with severe molar incisor hypomineralization from the perspective of the Brazilian public system. MATERIALS AND METHODS: Two models were constructed: a one-year decision tree and a ten-year Markov model, each based on a hypothetical cohort of one thousand individuals through Monte Carlo simulation. Eight restorative strategies were evaluated: high viscosity glass ionomer cement (HVGIC); encapsulated GIC; etch and rinse adhesive + composite; self-etch adhesive + composite; preformed stainless steel crown; HVGIC + etch and rinse adhesive + composite; HVGIC + self-etch adhesive + composite, and encapsulated GIC + etch and rinse adhesive + composite. Effectiveness data were sourced from the literature. Micro-costing was applied using 2022 USD market averages with a 5% variation. Incremental cost-effectiveness ratio (ICER), net monetary benefit (%NMB), and the budgetary impact were obtained. RESULTS: Cost-effective treatments included HVGIC (%NMB = 0%/ 0%), encapsulated GIC (%NMB = 19.4%/ 19.7%), and encapsulated GIC + etch and rinse adhesive + composite (%NMB = 23.4%/ 24.5%) at 1 year and 10 years, respectively. The benefit gain of encapsulated GIC + etch and rinse adhesive + composite in relation to encapsulated GIC was small when compared to the cost increase at 1 year (gain of 3.28% and increase of USD 24.26) and 10 years (gain of 4% and increase of USD 15.54). CONCLUSION: Within the horizon and perspective analyzed, the most cost-effective treatment was encapsulated GIC restoration. CLINICAL RELEVANCE: This study can provide information for decision-making.

Cost-utility analysis of add-on vericiguat for the treatment of chronic heart failure with reduced ejection fraction in China.

OBJECTIVE: This study aimed to evaluate the cost-utility of the addition of vericiguat for treating chronic heart failure (CHF) in China from the healthcare payer's perspective. METHODS: A Markov model was built to estimate the cost and utility of treating CHF using vericiguat plus standard treatment (vericiguat group) vs. standard treatment alone (standard treatment group). The clinical parameters (mortality of cardiovascular and hospitalization rate of HF) were calculated according to the VICTORIA clinical trial. The HF cost and utility data were obtained from the literature published in China. One-way sensitivity analysis and probability sensitivity analysis were performed. RESULTS: According to the 13-year model, vericiguat was more expensive (155599.07 CNY vs. 259396.83 CNY) and more effective (4.41 QALYs vs. 4.54 QALYs). The incremental cost-utility ratio (ICUR) was 802389.27 CNY per QALY. One-way sensitivity analysis revealed that cardiovascular mortality in the two groups was the parameter that had the greatest impact on the results. The GDP per capita in 2022 in China was 85,700 CNY. The probability sensitivity analysis (PSA) showed that the probability of vericiguat being cost-effective was only 41.7% at the willingness-to-pay (WTP) threshold of 3 times GDP per capita (257,100 CNY). CONCLUSIONS: In China, the treatment of CHF with vericiguat is not cost-effective. The drug price could decrease to 145.8 CNY, which could be considered cost-effective.

Post-task responses following working memory and movement are driven by transient spectral bursts with similar characteristics.

The post-movement beta rebound has been studied extensively using magnetoencephalography (MEG) and is reliably modulated by various task parameters as well as illness. Our recent study showed that rebounds, which we generalise as "post-task responses" (PTRs), are a ubiquitous phenomenon in the brain, occurring across the cortex in theta, alpha, and beta bands. Currently, it is unknown whether PTRs following working memory are driven by transient bursts, which are moments of short-lived high amplitude activity, similar to those that drive the post-movement beta rebound. Here, we use three-state univariate hidden Markov models (HMMs), which can identify bursts without a priori knowledge of frequency content or response timings, to compare bursts that drive PTRs in working memory and visuomotor MEG datasets. Our results show that PTRs across working memory and visuomotor tasks are driven by pan-spectral transient bursts. These bursts have very similar spectral content variation over the cortex, correlating strongly between the two tasks in the alpha (R2 = .89) and beta (R2 = .53) bands. Bursts also have similar variation in duration over the cortex (e.g., long duration bursts occur in the motor cortex for both tasks), strongly correlating over cortical regions between tasks (R2 = .56), with a mean over all regions of around 300 ms in both datasets. Finally, we demonstrate the ability of HMMs to isolate signals of interest in MEG data, such that the HMM probability timecourse correlates more strongly with reaction times than frequency filtered power envelopes from the same brain regions. Overall, we show that induced PTRs across different tasks are driven by bursts with similar characteristics, which can be identified using HMMs. Given the similarity between bursts across tasks, we suggest that PTRs across the cortex may be driven by a common underlying neural phenomenon.

Traffic trajectory data analysis technology based on HMM model map matching algorithm.

The rapid growth of traffic trajectory data and the development of positioning technology have driven the demand for its analysis. However, in the current application scenarios, there are some problems such as the deviation between positioning data and real roads and low accuracy of existing trajectory data traffic prediction models. Therefore, a map matching algorithm based on hidden Markov models is proposed in this study. The algorithm starts from the global route, selects K nearest candidate paths, and identifies candidate points through the candidate paths. It uses changes in speed, angle, and other information to generate a state transition matrix that match trajectory points to the actual route. When processing trajectory data in the experiment, K = 5 is selected as the optimal value, the algorithm takes 51 ms and the accuracy is 95.3%. The algorithm performed well in a variety of road conditions, especially in parallel and mixed road sections, with an accuracy rate of more than 96%. Although the time loss of this algorithm is slightly increased compared with the traditional algorithm, its accuracy is stable. Under different road conditions, the accuracy of the algorithm is 98.3%, 97.5%, 94.8% and 96%, respectively. The accuracy of the algorithm based on traditional hidden Markov models is 95.9%, 95.7%, 95.4% and 94.6%, respectively. It can be seen that the accuracy of the algorithm designed has higher precision. The experiment proves that the map matching algorithms based on hidden Markov models is superior to other algorithms in terms of matching accuracy. This study makes the processing of traffic trajectory data more accurate.

An intelligent model to decode students' behavioral states in physical education using back propagation neural network and Hidden Markov Model.

This paper highlights the need for intelligent analysis of students' behavioral states in physical education tasks. The hand-ring inertial data is used to identify students' motion sequence states. First, statistical feature extraction is performed based on the acceleration and angular velocity data collected from the bracelet. After completing the filtering and noise reduction of the data, we perform feature extraction by Back Propagation Neural Network (BPNN) and use the sliding window method for analysis. Finally, the classification capability of the model sequence is enhanced by the Hidden Markov Model (HMM). The experimental results indicate that the classification accuracy of student action sequences in physical education exceeds 96% after optimization by the HMM method. This provides intelligent means and new ideas for future student state recognition in physical education and teaching reform.

Zika emergence, persistence, and transmission rate in Colombia: a nationwide application of a space-time Markov switching model.

Zika, a viral disease transmitted to humans by Aedes mosquitoes, emerged in the Americas in 2015, causing large-scale epidemics. Colombia alone reported over 72,000 Zika cases between 2015 and 2016. Using national surveillance data from 1121 municipalities over 70 weeks, we identified sociodemographic and environmental factors associated with Zika's emergence, re-emergence, persistence, and transmission intensity in Colombia. We fitted a zero-state Markov-switching model under the Bayesian framework, assuming Zika switched between periods of presence and absence according to spatially and temporally varying probabilities of emergence/re-emergence (from absence to presence) and persistence (from presence to presence). These probabilities were assumed to follow a series of mixed multiple logistic regressions. When Zika was present, assuming that the cases follow a negative binomial distribution, we estimated the transmission intensity rate. Our results indicate that Zika emerged/re-emerged sooner and that transmission was intensified in municipalities that were more densely populated, at lower altitudes and/or with less vegetation cover. Warmer temperatures and less weekly-accumulated rain were also associated with Zika emergence. Zika cases persisted for longer in more densely populated areas with more cases reported in the previous week. Overall, population density, elevation, and temperature were identified as the main contributors to the first Zika epidemic in Colombia. We also estimated the probability of Zika presence by municipality and week, and the results suggest that the disease circulated undetected by the surveillance system on many occasions. Our results offer insights into priority areas for public health interventions against emerging and re-emerging Aedes-borne diseases.

Continuous Markov Models for Analyzing the Effect of Environmental Personal Exposure on Multiple Sclerosis Progression.

Multiple sclerosis (MS) is an inflammatory autoimmune demyelinating disorder of the central nervous system, leading to progressive functional impairments. Predicting disease progression with a probabilistic and time-dependent approach might help suggest interventions for a better management of the disease. Recently, there has been increasing focus on the impact of air pollutants as environmental factors influencing disease progression. This study employs a Continuous-Time Markov Model (CMM) to explore the impact of air pollution measurements on MS progression using longitudinal data from MS patients in Italy between 2013 and 2022. Preliminary findings indicate a relationship between air pollution and MS progression, with pollutants like Particulate Matter with a diameter of 10 micrometers (PM10) or 2.5 micrometers (PM2.5), Nitrogen Dioxide (NO2), and Carbon Monoxide (CO) showing potential effects on disease activity.

Economic evaluation of trastuzumab in HER2-positive early breast cancer in Indonesia: A cost-effectiveness analysis.

BACKGROUND: Trastuzumab has significantly enhanced the survival and prognosis of individuals diagnosed with human epidermal growth factor receptor 2 (HER2)-positive early breast cancer. Considering its relatively high costs, we aimed to examine the cost-effectiveness of trastuzumab plus chemotherapy compared with chemotherapy alone in HER2-positive early breast cancer from an Indonesian healthcare payer's perspective. METHODS: A Markov model was developed to project the lifetime health benefits and costs associated with trastuzumab treatment for a cohort of women with HER2-positive early breast cancer. Efficacy data and baseline characteristics in the base-case analysis were primarily derived from the 11-year results of the HERA trial. Costs were based on verified reimbursement data from Indonesia's Health and Social Security Agency (BPJS Kesehatan) of the year 2020. A scenario analysis was conducted with efficacy data based on the joint analysis from the NSABP B-31 and NCCTG N9831 trials, allowing for subgroup analysis by age at diagnosis. Univariate and probabilistic sensitivity analyses were conducted to assess the influence of parameter uncertainty. RESULTS: In the base-case analysis, the results indicated that the lifetime costs for trastuzumab plus chemotherapy and chemotherapy alone were US$33,744 and US$22,720, respectively, resulting in substantial incremental savings of US$11,024 per patient for the former. Trastuzumab plus chemotherapy also led to higher total quality-adjusted life years (QALYs) and life years gained (LYG), resulting in incremental cost-effectiveness ratios (ICERs) of US$6,842 per QALY and US$5,510 per LYG. In scenario analysis, the subgroup with an age at diagnosis <40 years old reflected the most cost-effective subgroup. Both the base-case and scenario analyses demonstrated cost-effectiveness with a willingness-to-pay threshold of three-times Gross Domestic Product (GDP). Sensitivity analyses confirmed the robustness of the findings and conclusions. CONCLUSION: In Indonesia, trastuzumab plus chemotherapy can be considered cost-effective compared to chemotherapy alone at a willingness-to-pay threshold of three times GDP, and it is likely most cost-effective in women <40 years of age.

Conformational Dynamics in Corynebacterium glutamicum Diaminopimelate Epimerase: Insights from Ligand Parameterization, Atomistic Simulation, and Markov State Modeling.

The microbial enzyme diaminopimelate epimerase (DapF), a vital enzyme in the lysine biosynthetic pathway, catalyzes the conversion of L, L-diaminopimelate (L, L-DAP) to D, L-diaminopimelate (D, L-DAP) using a catalytic cysteine dyad with one cysteine in thiol state and another in thiolate. Under oxidizing conditions, the catalytic cysteines of apo DapF form a disulfide bond that alters the structure and function of DapF. Given its potential as a target for antimicrobial resistance treatments, understanding DapF's functional dynamics is imperative. In the present work, we employ microsecond-scale all-atom molecular dynamics simulations of product-bound DapF and apo-DapF under oxidized and reduced conditions. We employ a polarized charge model for the ligand and the active site residues, which was necessary to preserve the electrostatic environment in the active site and retain the ligand in the active site. The product-bound DapF and apo-DapF in oxidized and reduced conditions exhibit a closed, semi-open, and open conformation, respectively, as identified using the internal coordinates of the dimeric enzyme and the principal component analysis. The conformational switch is guided by the dynamic catalytic (DC) loop, loop II, and loop III movements in the active site. The time scale of the close-to-open conformational transition is estimated to be 0.8 µs through Markov state modeling (MSM) and transition path theory (TPT). The present study explains the role of various active site residues and loops in ligand binding and protein dynamics in the DapF enzyme under different redox conditions. Such information will be helpful in future inhibitor design studies targeting the DapF enzyme.

The Hill function is the universal Hopfield barrier for sharpness of input-output responses.

The Hill functions, [Formula: see text], have been widely used in biology for over a century but, with the exception of [Formula: see text], they have had no justification other than as a convenient fit to empirical data. Here, we show that they are the universal limit for the sharpness of any input-output response arising from a Markov process model at thermodynamic equilibrium. Models may represent arbitrary molecular complexity, with multiple ligands, internal states, conformations, coregulators, etc, under core assumptions that are detailed in the paper. The model output may be any linear combination of steady-state probabilities, with components other than the chosen input ligand held constant. This formulation generalizes most of the responses in the literature. We use a coarse-graining method in the graph-theoretic linear framework to show that two sharpness measures for input-output responses fall within an effectively bounded region of the positive quadrant, [Formula: see text], for any equilibrium model with [Formula: see text] input binding sites. [Formula: see text] exhibits a cusp which approaches, but never exceeds, the sharpness of [Formula: see text], but the region and the cusp can be exceeded when models are taken away from thermodynamic equilibrium. Such fundamental thermodynamic limits are called Hopfield barriers, and our results provide a biophysical justification for the Hill functions as the universal Hopfield barriers for sharpness. Our results also introduce an object, [Formula: see text], whose structure may be of mathematical interest, and suggest the importance of characterizing Hopfield barriers for other forms of cellular information processing.

Markovian Approach for Exploring Competitive Diseases with Heterogeneity-Evidence from COVID-19 and Influenza in China.

Due to the complex interactions between multiple infectious diseases, the spreading of diseases in human bodies can vary when people are exposed to multiple sources of infection at the same time. Typically, there is heterogeneity in individuals' responses to diseases, and the transmission routes of different diseases also vary. Therefore, this paper proposes an SIS disease spreading model with individual heterogeneity and transmission route heterogeneity under the simultaneous action of two competitive infectious diseases. We derive the theoretical epidemic spreading threshold using quenched mean-field theory and perform numerical analysis under the Markovian method. Numerical results confirm the reliability of the theoretical threshold and show the inhibitory effect of the proportion of fully competitive individuals on epidemic spreading. The results also show that the diversity of disease transmission routes promotes disease spreading, and this effect gradually weakens when the epidemic spreading rate is high enough. Finally, we find a negative correlation between the theoretical spreading threshold and the average degree of the network. We demonstrate the practical application of the model by comparing simulation outputs to temporal trends of two competitive infectious diseases, COVID-19 and seasonal influenza in China.

Polygenic risk-stratified screening for nasopharyngeal carcinoma in high-risk endemic areas of China: a cost-effectiveness study.

Background: Nasopharyngeal carcinoma (NPC) has an extremely high incidence rate in Southern China, resulting in a severe disease burden for the local population. Current EBV serologic screening is limited by false positives, and there is opportunity to integrate polygenic risk scores for personalized screening which may enhance cost-effectiveness and resource utilization. Methods: A Markov model was developed based on epidemiological and genetic data specific to endemic areas of China, and further compared polygenic risk-stratified screening [subjects with a 10-year absolute risk (AR) greater than a threshold risk underwent EBV serological screening] to age-based screening (EBV serological screening for all subjects). For each initial screening age (30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, and 65-69 years), a modeled cohort of 100,000 participants was screened until age 69, and then followed until age 79. Results: Among subjects aged 30 to 54 years, polygenic risk-stratified screening strategies were more cost-effective than age-based screening strategies, and almost comprised the cost-effectiveness efficiency frontier. For men, screening strategies with a 1-year frequency and a 10-year absolute risk (AR) threshold of 0.7% or higher were cost-effective, with an incremental cost-effectiveness ratio (ICER) below the willingness to pay (¥203,810, twice the local per capita GDP). Specifically, the strategies with a 10-year AR threshold of 0.7% or 0.8% are the most cost-effective strategies, with an ICER ranging from ¥159,752 to ¥201,738 compared to lower-cost non-dominated strategies on the cost-effectiveness frontiers. The optimal strategies have a higher probability (29.4-35.8%) of being cost-effective compared to other strategies on the frontier. Additionally, they reduce the need for nasopharyngoscopies by 5.1-27.7% compared to optimal age-based strategies. Likewise, for women aged 30-54 years, the optimal strategy with a 0.3% threshold showed similar results. Among subjects aged 55 to 69 years, age-based screening strategies were more cost-effective for men, while no screening may be preferred for women. Conclusion: Our economic evaluation found that the polygenic risk-stratified screening could improve the cost-effectiveness among individuals aged 30-54, providing valuable guidance for NPC prevention and control policies in endemic areas of China.

Predicting the prevalence of type 2 diabetes in Brazil: a modeling study.

Aims: We adopted a modeling approach to predict the likely future prevalence of type 2 diabetes, taking into account demographic changes and trends in obesity and smoking in Brazil. We then used the model to estimate the likely future impact of different policy scenarios, such as policies to reduce obesity. Methods: The IMPACT TYPE 2 DIABETES model uses a Markov approach to integrate population, obesity, and smoking trends to estimate future type 2 diabetes prevalence. We developed a model for the Brazilian population from 2006 to 2036. Data on the Brazilian population in relation to sex and age were collected from the Brazilian Institute of Geography and Statistics, and data on the prevalence of type 2 diabetes, obesity, and smoking were collected from the Surveillance of Risk and Protection Factors for Chronic Diseases by Telephone Survey (VIGITEL). Results: The observed prevalence of type 2 diabetes among Brazilians aged over 25 years was 10.8% (5.2-14.3%) in 2006, increasing to 13.7% (6.9-18.4%) in 2020. Between 2006 and 2020, the observed prevalence in men increased from 11.0 to 19.1% and women from 10.6 to 21.3%. The model forecasts a dramatic rise in prevalence by 2036 (27.0% overall, 17.1% in men and 35.9% in women). However, if obesity prevalence declines by 1% per year from 2020 to 2036 (Scenario 1), the prevalence of diabetes decreases from 26.3 to 23.7, which represents approximately a 10.0% drop in 16 years. If obesity declined by 5% per year in 16 years as an optimistic target (Scenario 2), the prevalence of diabetes decreased from 26.3 to 21.2, representing a 19.4% drop in diabetes prevalence. Conclusion: The model predicts an increase in the prevalence of type 2 diabetes in Brazil. Even with ambitious targets to reduce obesity prevalence, type 2 diabetes in Brazil will continue to have a large impact on Brazilian public health.

Immune checkpoint inhibitors as the second-line treatment for advanced esophageal squamous cell carcinoma: a cost-effectiveness analysis based on network meta-analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have demonstrated superior clinical efficacy in prolonging overall survival (OS) as the second-line treatment for advanced or metastatic esophageal squamous cell carcinoma (ESCC), and were recommended by the guidelines. However, it remains uncertain which ICI is the most cost-effective. This study assessed the cost-effectiveness of ICIs as the second-line treatment for ESCC based on the perspective of the Chinese healthcare system. METHODS: A network meta-analysis (NMA) was performed to obtain the Hazard ratios (HRs) for indirect comparisons. A three-state Markov model with a 10-year time horizon was conducted to assess the cost-effectiveness. The state transition probabilities were calculated with Kaplan-Meier (KM) curves data from clinical trial and HRs from the NMA. Utilities and costs were derived from local charges or previously published studies. Univariate and probabilistic sensitivity analyses (PSA) were performed to examine model robustness. The results were assessed based on the total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). RESULTS: Five clinical trials (ATTRACTION-3, ESCORT, KEYNOTE-181, ORIENT-2, RATIONALE-302) with a total of 1797 patients were included in the NMA. The NMA showed that both camrelizumab and tislelizumab received relatively high rankings for progression-free survival (PFS) and OS. Compared with sintilimab, treatment with tislelizumab and camrelizumab gained 0.018 and 0.034 additional QALYs, resulting in incremental ICERs of $75,472.65/QALY and $175,681.9/QALY, respectively. Nivolumab and pembrolizumab produced lower QALYs and greater costs, suggesting that both were dominated in comparison to sintilimab. HRs and health state utilities were the most influential parameters in most univariate sensitivity analyses of paired comparisons. PSA results suggested that sintilimab had an 84.4% chance of being the most cost-effective treatment regimen at the WTP threshold of $38,223.34/QALY. In the scenario analysis, sintilimab would no longer be cost-effective, if the price of camrelizumab was assumed to decrease by 64.6% or the price of tislelizumab was assumed to decrease by 16.9%. CONCLUSIONS AND RELEVANCE: Among the five potential competing ICIs, sintilimab was likely to be the most cost-effective regimen as the second-line treatment for locally advanced or metastatic ESCC in China.

International Cost-Effectiveness Analysis of Durvalumab in Stage III Non-Small Cell Lung Cancer.

Importance: Standard of care for unresectable locally advanced non-small cell lung cancer (NSCLC) involves definitive chemoradiotherapy followed by maintenance therapy with durvalumab. However, the cost of durvalumab has been cited as a barrier to its use in various health systems. Objective: To evaluate the cost-effectiveness of durvalumab vs placebo as maintenance therapy in patients with unresectable stage III NSCLC from 4 international payer perspectives (US, Brazil, Singapore, and Spain). Design, Setting, and Participants: In this economic evaluation, a Markov model was designed to compare the lifetime cost-effectiveness of maintenance durvalumab for unresectable stage III NSCLC with that of placebo, using 5-year outcomes data from the PACIFIC randomized placebo-controlled trial. Individual patient data were extracted from the PACIFIC, KEYNOTE-189, ADAURA, ALEX, and REVEL randomized clinical trials to develop a decision-analytic model to determine the cost-effectiveness of durvalumab compared with placebo maintenance therapy over a 10-year time horizon. Direct costs, adverse events, and patient characteristics were based on country-specific payer perspectives and demographic characteristics. The study was conducted from June 1, 2022, through December 27, 2023. Main Outcomes and Measures: Life-years, quality-adjusted life years (QALYs), lifetime costs, and incremental cost-effectiveness ratios (ICERs) were estimated at country-specific willingness-to-pay thresholds ([data reported in US$] US: $150 000 per QALY; Brazil: $22 251 per QALY; Singapore: $55 288 per QALY, and Spain: $107 069 per QALY). One-way and probabilistic sensitivity analyses were performed to account for parameters of uncertainty. A cost-threshold analysis was also performed. Results: The US base-case model found that treatment with durvalumab was associated with an increased cost of $114 394 and improved effectiveness of 0.50 QALYs compared with placebo, leading to an ICER of $228 788 per QALY. Incremental cost-effectiveness ratios, according to base-case models, were $141 146 for Brazil, $153 461 for Singapore, and $125 193 for Spain. Durvalumab price adjustments to the PACIFIC data improved cost-effectiveness in Singapore, with an ICER of $45 164. The model was most sensitive to the utility of durvalumab. Conclusions and Relevance: In this cost-effectiveness analysis of durvalumab as maintenance therapy for unresectable stage III NSCLC, the therapy was found to be cost-prohibitive from the perspective of various international payers according to country-specific willingness-to-pay thresholds per QALY. The findings of the study suggest that discounted durvalumab acquisition costs, as possible in Singapore, might improve cost-effectiveness globally.

A Bayesian hierarchical hidden Markov model for clustering and gene selection: Application to kidney cancer gene expression data.

We introduce a Bayesian approach for biclustering that accounts for the prior functional dependence between genes using hidden Markov models (HMMs). We utilize biological knowledge gathered from gene ontologies and the hidden Markov structure to capture the potential coexpression of neighboring genes. Our interpretable model-based clustering characterized each cluster of samples by three groups of features: overexpressed, underexpressed, and irrelevant features. The proposed methods have been implemented in an R package and are used to analyze both the simulated data and The Cancer Genome Atlas kidney cancer data.

Bayesian meta-analysis of penetrance for cancer risk.

Multi-gene panel testing allows many cancer susceptibility genes to be tested quickly at a lower cost making such testing accessible to a broader population. Thus, more patients carrying pathogenic germline mutations in various cancer-susceptibility genes are being identified. This creates a great opportunity, as well as an urgent need, to counsel these patients about appropriate risk-reducing management strategies. Counseling hinges on accurate estimates of age-specific risks of developing various cancers associated with mutations in a specific gene, ie, penetrance estimation. We propose a meta-analysis approach based on a Bayesian hierarchical random-effects model to obtain penetrance estimates by integrating studies reporting different types of risk measures (eg, penetrance, relative risk, odds ratio) while accounting for the associated uncertainties. After estimating posterior distributions of the parameters via a Markov chain Monte Carlo algorithm, we estimate penetrance and credible intervals. We investigate the proposed method and compare with an existing approach via simulations based on studies reporting risks for two moderate-risk breast cancer susceptibility genes, ATM and PALB2. Our proposed method is far superior in terms of coverage probability of credible intervals and mean square error of estimates. Finally, we apply our method to estimate the penetrance of breast cancer among carriers of pathogenic mutations in the ATM gene.

Cost-effectiveness analysis of adult pneumococcal conjugate vaccines for pneumococcal disease in Japan.

BACKGROUND: The 23-valent pneumococcal polysaccharide vaccine (PPSV23) is used in the Japanese National Immunization Program for older adults and adults with increased risk for pneumococcal disease, however, disease incidence and associated burden remain high. We evaluated the cost-effectiveness of pneumococcal conjugate vaccines (PCVs) for adults aged 65 years and high-risk adults aged 60-64 years in Japan. RESEARCH DESIGN AND METHODS: Using a Markov model, we evaluated lifetime costs using societal and healthcare payer perspectives and estimated quality-adjusted life-years (QALYs), and number of prevented cases and deaths caused by invasive pneumococcal disease (IPD) and non-IPD. The base case analysis used a societal perspective. RESULTS: In comparison with PPSV23, the 20-valent PCV (PCV20) prevented 127 IPD cases 10,813 non-IPD cases (inpatients: 2,461, outpatients: 8,352) and 226 deaths, and gained more QALYs (+0.0015 per person) with less cost (-JPY22,513 per person). All sensitivity and scenario analyses including a payer perspective analysis indicated that the incremental cost-effectiveness ratios (ICERs) were below the cost-effectiveness threshold value in Japan (JPY5 million/QALY). CONCLUSIONS: PCV20 is both cost saving and more effective than PPSV23 for adults aged 65 years and high-risk adults aged 60-64 years in Japan.

The Pentameric Ligand-Gated Ion Channel Family: A New Member of the Voltage Gated Ion Channel Superfamily?

In this report we present seven lines of bioinformatic evidence supporting the conclusion that the Pentameric Ligand-gated Ion Channel (pLIC) Family is a member of the Voltage-gated Ion Channel (VIC) Superfamily. In our approach, we used the Transporter Classification Database (TCDB) as a reference and applied a series of bioinformatic methods to search for similarities between the pLIC family and members of the VIC superfamily. These include: (1) sequence similarity, (2) compatibility of topology and hydropathy profiles, (3) shared domains, (4) conserved motifs, (5) similarity of Hidden Markov Model profiles between families, (6) common 3D structural folds, and (7) clustering analysis of all families. Furthermore, sequence and structural comparisons as well as the identification of a 3-TMS repeat unit in the VIC superfamily suggests that the sixth transmembrane segment evolved into a re-entrant loop. This evidence suggests that the voltage-sensor domain and the channel domain have a common origin. The classification of the pLIC family within the VIC superfamily sheds light onto the topological origins of this family and its evolution, which will facilitate experimental verification and further research into this superfamily by the scientific community.