The cost effectiveness of Naltrexone added to cognitive-behavioral therapy in the treatment of alcohol dependence

he purpose of this study was to evaluate the comparative cost of treating alcohol dependence with either cognitive behavioral therapy (CBT) alone or CBT combined with naltrexone (CBT+naltrexone). Two hundred ninety-eight outpatients dependent on alcohol who were consecutively treated for alcohol dependence participated in this study. One hundred seven (36%) patients received adjunctive pharmacotherapy (CBT+naltrexone). The Drug Abuse Treatment Cost Analysis Program was used to estimate treatment costs. Adjunctive pharmacotherapy (CBT+naltrexone) introduced an additional treatment cost and was 54% more expensive than CBT alone. When treatment abstinence rates (36.1% CBT; 62.6% CBT+naltrexone) were applied to cost effectiveness ratios, CBT+naltrexone demonstrated an advantage over CBT alone. There were no differences between groups on a preference-based health measure (SF-6D). In this treatment center, to achieve 100 abstainers over a 12-week program, 280 patients require CBT compared with 160 CBT+naltrexone. The dominant choice was CBT+naltrexone based on modest economic advantages and significant efficiencies in the numbers needed to treat.

Morphine-induced receptor endocytosis in a novel knockin mouse reduces tolerance and dependence

Abstract Opioid drugs, such as morphine, are among the most effective analgesics available. However, their utility for the treatment of chronic pain is limited by side effects including tolerance and dependence. Morphine acts primarily through the mu-opioid receptor (MOP-R) , which is also a target of endogenous opioids. However, unlike endogenous ligands, morphine fails to promote substantial receptor endocytosis both in vitro, and in vivo. Receptor endocytosis serves at least two important functions in signal transduction. First, desensitization and endocytosis act as an "off" switch by uncoupling receptors from G protein. Second, endocytosis functions as an "on" switch, resensitizing receptors by recycling them to the plasma membrane. Thus, both the off and on function of the MOP-R are altered in response to morphine compared to endogenous ligands. To examine whether the low degree of endocytosis induced by morphine contributes to tolerance and dependence, we generated a knockin mouse that expresses a mutant MOP-R that undergoes morphine-induced endocytosis. Morphine remains an excellent antinociceptive agent in these mice. Importantly, these mice display substantially reduced antinociceptive tolerance and physical dependence. These data suggest that opioid drugs with a pharmacological profile similar to morphine but the ability to promote endocytosis could provide analgesia while having a reduced liability for promoting tolerance and dependence

Business cycle dynamics with duration dependence and leading indicators

Durland and McCurdy [Durland, J.M., McCurdy, T.H., 1994. Duration-dependent transitions in a Markov model of US GNP growth. Journal of Business and Economic Statistics 12, 279–288] investigated the issue of duration dependence in US business cycle phases using a Markov regime-switching approach, introduced by Hamilton [Hamilton, J., 1989. A new approach to the analysis of time series and the business cycle. Econometrica 57, 357–384] and extended to the case of variable transition parameters by Filardo [Filardo, A.J., 1994. Business cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12, 299–308]. In Durland and McCurdy’s model duration alone was used as an explanatory variable of the transition probabilities. They found that recessions were duration dependent whilst expansions were not. In this paper, we explicitly incorporate the widely-accepted US business cycle phase change dates as determined by the NBER, and use a state-dependent multinomial Logit modelling framework. The model incorporates both duration and movements in two leading indexes – one designed to have a short lead (SLI) and the other designed to have a longer lead (LLI) – as potential explanatory variables. We find that doing so suggests that current duration is not only a significant determinant of transition out of recessions, but that there is some evidence that it is also weakly significant in the case of expansions. Furthermore, we find that SLI has more informational content for the termination of recessions whilst LLI does so for expansions.

Multifractal analysis of geomagnetic storm and solar flare indices and their class dependence

The multifractal properties of two indices of geomagnetic activity, D st (representative of low latitudes) and a p (representative of the global geomagnetic activity), with the solar X-ray brightness, X l , during the period from 1 March 1995 to 17 June 2003 are examined using multifractal detrended fluctuation analysis (MF-DFA). The h(q) curves of D st and a p in the MF-DFA are similar to each other, but they are different from that of X l , indicating that the scaling properties of X l are different from those of D st and a p . Hence, one should not predict the magnitude of magnetic storms directly from solar X-ray observations. However, a strong relationship exists between the classes of the solar X-ray irradiance (the classes being chosen to separate solar flares of class X-M, class C, and class B or less, including no flares) in hourly measurements and the geomagnetic disturbances (large to moderate, small, or quiet) seen in D st and a p during the active period. Each time series was converted into a symbolic sequence using three classes. The frequency, yielding the measure representations, of the substrings in the symbolic sequences then characterizes the pattern of space weather events. Using the MF-DFA method and traditional multifractal analysis, we calculate the h(q), D(q), and τ (q) curves of the measure representations. The τ (q) curves indicate that the measure representations of these three indices are multifractal. On the basis of this three-class clustering, we find that the h(q), D(q), and τ (q) curves of the measure representations of these three indices are similar to each other for positive values of q. Hence, a positive flare storm class dependence is reflected in the scaling exponents h(q) in the MF-DFA and the multifractal exponents D(q) and τ (q). This finding indicates that the use of the solar flare classes could improve the prediction of the D st classes.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

Sequential fusion of decisions with favorable dependence for controlled verification errors

Statistical dependence between classifier decisions is often shown to improve performance over statistically independent decisions. Though the solution for favourable dependence between two classifier decisions has been derived, the theoretical analysis for the general case of 'n' client and impostor decision fusion has not been presented before. This paper presents the expressions developed for favourable dependence of multi-instance and multi-sample fusion schemes that employ 'AND' and 'OR' rules. The expressions are experimentally evaluated by considering the proposed architecture for text-dependent speaker verification using HMM based digit dependent speaker models. The improvement in fusion performance is found to be higher when digit combinations with favourable client and impostor decisions are used for speaker verification. The total error rate of 20% for fusion of independent decisions is reduced to 2.1% for fusion of decisions that are favourable for both client and impostors. The expressions developed here are also applicable to other biometric modalities, such as finger prints and handwriting samples, for reliable identity verification.

A DRD2 and ANKK1 haplotype is associated with nicotine dependence

To test the importance of the dopamine D2 receptor (DRD2) region in nicotine dependence, 150 smokers and 228 controls were genotyped for the DRD2 C957T, -141delC and ANKK1 TaqIA polymorphisms (rs6277, rs1799732 and rs1800497, respectively). The -141delC SNP did not show any association but both the C957T and TaqIA SNPs showed association at the allele, genotype, haplotype and combined genotype levels. The 957C/TaqI A1 haplotype was more than 3.5 times as likely to be associated with nicotine dependence compared with the 957T/TaqI A1 haplotype (P = 0.003). Analysis of the combined genotypes of both SNPs revealed that individuals who were homozygous for the 957C-allele (CC) and had either one or two copies of the TaqI A1-allele were 3.3 times as likely to have nicotine dependence compared to all other genotype combinations (P = 0.0003) and that these genotypes accounted for approximately 13% of the susceptibility to nicotine addiction in our population. Our findings suggest that the DRD2 C957T polymorphism and the ANKK1 TaqIA polymorphism are key contributors to the genetic susceptibility to nicotine dependence.

DRD2 C957T and TaqIA genotyping reveals gender effects and unique low-risk and high-risk genotypes in alcohol dependence

AIMS: As recent conflicting reports describe a genetic association between both the C- and the T-alleles of the dopamine D2 receptor (DRD2) C957T polymorphism (rs6277) in alcohol-dependent subjects, our aim was to examine this polymorphism and TaqIA (rs1800497) in Australian alcohol-dependent subjects. METHODS: The C957T polymorphism was genotyped in 228 patients with alcohol dependence (72 females and 156 males) and 228 healthy controls. RESULTS: The C-allele and C/C genotype of C957T was associated with alcohol dependence, whereas the TaqIA polymorphism was not. When analysed separately for C957T, males showed an even stronger association with the C-allele and females showed no association. The C957T and TaqIA haplotyping revealed a strong association with alcohol dependence and a double-genotype analysis (combining C957T and TaqIA genotypes) revealed that the relative risk of different genotypes varied by up to 27-fold with the TT/A1A2 having an 8.5-fold lower risk of alcohol dependence than other genotypes. CONCLUSION: Decreased DRD2 binding associated with the C-allele of the DRD2 C957T polymorphism is likely to be important in the underlying pathophysiology of at least some forms of alcohol dependence, and this effect appears to be limited to males only.

Maintenance optimisation of a multi-state series-parallel system considering economic dependence and state-dependent inspection intervals

This paper presents a maintenance optimisation method for a multi-state series-parallel system considering economic dependence and state-dependent inspection intervals. The objective function considered in the paper is the average revenue per unit time calculated based on the semi-regenerative theory and the universal generating function (UGF). A new algorithm using the stochastic ordering is also developed in this paper to reduce the search space of maintenance strategies and to enhance the efficiency of optimisation algorithms. A numerical simulation is presented in the study to evaluate the efficiency of the proposed maintenance strategy and optimisation algorithms. The simulation result reveals that maintenance strategies with opportunistic maintenance and state-dependent inspection intervals are more cost-effective when the influence of economic dependence and inspection cost is significant. The study further demonstrates that the optimisation algorithm proposed in this paper has higher computational efficiency than the commonly employed heuristic algorithms.