Cost-effectiveness of a bivalent human papillomavirus vaccination program in Japan

Background Human papillomavirus (HPV) vaccines and their widespread adoption have the potential to relieve a large part of the burden of cervical cancer morbidity and mortality, particularly in countries that have low screening rates or, like Japan, lack a cohesive universal screening program. An economic evaluation was conducted to assess the cost-effectiveness of introducing a bivalent HPV vaccination program in Japan from a healthcare perspective. METHODS: A Markov model of the natural history of HPV infection that incorporates both vaccination and screening was developed for Japan. The modelled intervention, a bivalent HPV vaccine with a 100% lifetime vaccine efficacy and 80% vaccine coverage, given to a cohort of 12-year-old Japanese girls in conjunction with the current screening program, was compared with screening alone in terms of costs and effectiveness. A discount rate of 5% was applied to both costs and utilities where relevant. RESULTS: Vaccination alongside screening compared with screening alone is associated with an incremental cost-effectiveness ratio (ICER) of US$20315 per quality-adjusted-life-year gained if 80% coverage is assumed. The ICER at 5% coverage with the vaccine plus screening, compared with screening alone, is US$1158. CONCLUSION: The cost-effectiveness results suggest that the addition of a HPV vaccination program to Japan's cervical cancer screening program is highly likely to prove a cost-effective way to reduce the burden of cervical cancer, precancerous lesions and HPV16/18-related diseases.

The population cost-effectiveness of delivering universal and indicated school-based interventions to prevent the onset of major depression among youth in Australia

AIMS: School-based psychological interventions encompass: universal interventions targeting youth in the general population; and indicated interventions targeting youth with subthreshold depression. This study aimed to: (1) examine the population cost-effectiveness of delivering universal and indicated prevention interventions to youth in the population aged 11-17 years via primary and secondary schools in Australia; and (2) compare the comparative cost-effectiveness of delivering these interventions using face-to-face and internet-based delivery mechanisms. METHODS: We reviewed literature on the prevention of depression to identify all interventions targeting youth that would be suitable for implementation in Australia and had evidence of efficacy to support analysis. From this, we found evidence of effectiveness for the following intervention types: universal prevention involving group-based psychological interventions delivered to all participating school students; and indicated prevention involving group-based psychological interventions delivered to students with subthreshold depression. We constructed a Markov model to assess the cost-effectiveness of delivering universal and indicated interventions in the population relative to a 'no intervention' comparator over a 10-year time horizon. A disease model was used to simulate epidemiological transitions between three health states (i.e., healthy, diseased and dead). Intervention effect sizes were based on meta-analyses of randomised control trial data identified in the aforementioned review; while health benefits were measured as Disability-adjusted Life Years (DALYs) averted attributable to reductions in depression incidence. Net costs of delivering interventions were calculated using relevant Australian data. Uncertainty and sensitivity analyses were conducted to test model assumptions. Incremental cost-effectiveness ratios (ICERs) were measured in 2013 Australian dollars per DALY averted; with costs and benefits discounted at 3%. RESULTS: Universal and indicated psychological interventions delivered through face-to-face modalities had ICERs below a threshold of $50 000 per DALY averted. That is, $7350 per DALY averted (95% uncertainty interval (UI): dominates - 23 070) for universal prevention, and $19 550 per DALY averted (95% UI: 3081-56 713) for indicated prevention. Baseline ICERs were generally robust to changes in model assumptions. We conducted a sensitivity analysis which found that internet-delivered prevention interventions were highly cost-effective when assuming intervention effect sizes of 100 and 50% relative to effect sizes observed for face-to-face delivered interventions. These results should, however, be interpreted with caution due to the paucity of data. CONCLUSIONS: School-based psychological interventions appear to be cost-effective. However, realising efficiency gains in the population is ultimately dependent on ensuring successful system-level implementation.

Simple approximate MAP inference for Dirichlet processes mixtures

The Dirichlet process mixture model (DPMM) is a ubiquitous, flexible Bayesian nonparametric statistical model. However, full probabilistic inference in this model is analytically intractable, so that computationally intensive techniques such as Gibbs sampling are required. As a result, DPMM-based methods, which have considerable potential, are restricted to applications in which computational resources and time for inference is plentiful. For example, they would not be practical for digital signal processing on embedded hardware, where computational resources are at a serious premium. Here, we develop a simplified yet statistically rigorous approximate maximum a-posteriori (MAP) inference algorithm for DPMMs. This algorithm is as simple as DP-means clustering, solves the MAP problem as well as Gibbs sampling, while requiring only a fraction of the computational effort. (For freely available code that implements the MAP-DP algorithm for Gaussian mixtures see http://www.maxlittle.net/.) Unlike related small variance asymptotics (SVA), our method is non-degenerate and so inherits the “rich get richer” property of the Dirichlet process. It also retains a non-degenerate closed-form likelihood which enables out-of-sample calculations and the use of standard tools such as cross-validation. We illustrate the benefits of our algorithm on a range of examples and contrast it to variational, SVA and sampling approaches from both a computational complexity perspective as well as in terms of clustering performance. We demonstrate the wide applicabiity of our approach by presenting an approximate MAP inference method for the infinite hidden Markov model whose performance contrasts favorably with a recently proposed hybrid SVA approach. Similarly, we show how our algorithm can applied to a semiparametric mixed-effects regression model where the random effects distribution is modelled using an infinite mixture model, as used in longitudinal progression modelling in population health science. Finally, we propose directions for future research on approximate MAP inference in Bayesian nonparametrics.

Weakly-constrained codes for suppression of patterning effects in digital communications

We propose weakly-constrained stream and block codes with tunable pattern-dependent statistics and demonstrate that the block code capacity at large block sizes is close to the the prediction obtained from a simple Markov model published earlier. We demonstrate the feasibility of the code by presenting original encoding and decoding algorithms with a complexity log-linear in the block size and with modest table memory requirements. We also show that when such codes are used for mitigation of patterning effects in optical fibre communications, a gain of about 0.5dB is possible under realistic conditions, at the expense of small redundancy (≈10%). © 2010 IEEE

First comprehensive multi-tissue transcriptome of Cherax quadricarinatus (Decapoda: Parastacidae) reveals unexpected diversity of endogenous cellulase

The Australian freshwater crayfish species, Cherax quadricarinatus Von Martens, 1868, is an important commercial and invasive species that is also being increasingly used as a model organism to address important and interesting questions in crustacean biology. Through deep sequencing of the transcriptome of C. quadricarinatus from the hepatopancreas and four other tissues, we examine the evolution of endogenously transcribed cellulase genes and provide new insights into controversial issues regarding the nutritional biology of crayfishes. A cluster assembly approach yielded one of the highest quality transcriptome assemblies for a decapod crustacean to date. A total of 206,341,872 reads with an average read length of 80 bp were generated from sequencing the transcriptomes from the heart, kidney, hepatopancreas, nerve, and testis tissues. The assembled transcriptome contains a total of 44,525 transcripts. A total of 65 transcripts coding for carbohydrate-active enzymes (CAZy) were identified based on hidden Markov model (HMM), and a majority of them display high relative transcript abundance in the hepatopancreas tissue, supporting their role in nutrient digestion. Comprehensive phylogenetic analyses of proteins belonging to two main glycosyl hydrolase families (GH9 and GH5) suggest shared ancestry of C. quadricarinatus cellulases with other characterized crustacean cellulases. Our study significantly expands the number of known crustacean-derived CAZy-coding transcripts. More importantly, the surprising level of evolutionary diversification of these proteins in C. quadricarinatus suggests that these enzymes may have been of critical importance in the adaptation of freshwater crayfishes to new plant-based food sources as part of their successful invasion of freshwater systems from marine ancestors.

Evaluación de costo efectividad de la profilaxis versus tratamiento a demanda en pacientes con Hemofilia A moderada y severa para prevenir sangrado articular de una aseguradora en Colombia

Introducción: En Colombia existe un protocolo de manejo para pacientes con hemofilia A severa sin inhibidores que recomienda el manejo de profilaxis primaria y secundaria con FVIII. Objetivos: Estimar la relación incremental de costo-efectividad (RICE) de la profilaxis con Factor VIII vs tratamiento a demanda para prevenir sangrados articulares en pacientes con hemofilia A moderada y severa de una aseguradora en Colombia. Materiales y Métodos: Se adaptó un modelo de Markov desde la perspectiva del tercer pagador. Las probabilidades de transición se ajustaron mediante un modelo de regresión logística multinomial explicadas por la edad y el peso. Las tasas de eventos son anuales. Las efectividades se extrajeron de la cohorte de la aseguradora y de la literatura. Los costos incluyeron el FVIII, medicamentos, hospitalización, procedimientos quirúrgicos, apoyo diagnóstico y consultas médicas. La tasa de descuento fue del 3%. Resultados: En pacientes con hemofilia A moderada y severa la profilaxis con FVIII evitará en promedio 7 sangrados articulares, el RICE para el sangrado articular es de $303.457. Conclusiones: La profilaxis con Factor VIII es una estrategia costo-efectiva en el manejo de pacientes con hemofilia A moderada y severa para la aseguradora, disminuyendo el número de sangrados articulares al año.

Markov Chain Model for Cracking Behavior of Reinforced Concrete Beams

In this paper, nonhomogeneous Markov chains are proposed for modeling the cracking behavior of reinforced concrete beams subjected to monotonically increasing loads. The model facilitates prediction of the maximum crackwidth at a given load given the crackwidth at a lower load level, and thus leads to a better understanding of the cracking phenomenon. To illustrate the methodology developed, the results of three reinforced concrete beams tested in the laboratory are analyzed and presented.

Bayesian model selection for time series using Markov chain Monte Carlo

We present a stochastic simulation technique for subset selection in time series models, based on the use of indicator variables with the Gibbs sampler within a hierarchical Bayesian framework. As an example, the method is applied to the selection of subset linear AR models, in which only significant lags are included. Joint sampling of the indicators and parameters is found to speed convergence. We discuss the possibility of model mixing where the model is not well determined by the data, and the extension of the approach to include non-linear model terms.

New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.