Efficacy and Safety of Adjunctive Aripiprazole, Metformin, and Paeoniae–Glycyrrhiza Decoction for Antipsychotic-Induced Hyperprolactinemia: A Network Meta-Analysis of Randomized Controlled Trials

Aripiprazole, metformin, and paeoniae–glycyrrhiza decoction (PGD) have been widely used as adjunctive treatments to reduce antipsychotic (AP)-induced hyperprolactinemia in patients with schizophrenia. However, the comparative efficacy and safety of these medications have not been previously studied. A network meta-analysis of randomized controlled trials (RCTs) was conducted to compare the efficacy and safety between aripiprazole, metformin, and PGD as adjunctive medications in reducing AP-induced hyperprolactinemia in schizophrenia. Both international (PubMed, PsycINFO, EMBASE, and Cochrane Library databases) and Chinese (WanFang, Chinese Biomedical, and Chinese National Knowledge infrastructure) databases were searched from their inception until January 3, 2019. Data were analyzed using the Bayesian Markov Chain Monte Carlo simulations with the WinBUGS software. A total of 62 RCTs with 5,550 participants were included in the meta-analysis. Of the nine groups of treatments included, adjunctive aripiprazole (<5 mg/day) was associated with the most significant reduction in prolactin levels compared to placebo (posterior MD = −65.52, 95% CI = −104.91, −24.08) and the other eight treatment groups. Moreover, adjunctive PGD (>1:1) was associated with the lowest rate of all-cause discontinuation compared to placebo (posterior odds ratio = 0.45, 95% CI = 0.10, 3.13) and adjunctive aripiprazole (>10 mg/day) was associated with fewer total adverse drug events than placebo (posterior OR = 0.93, 95% CI = 0.65, 1.77) and other eight treatment groups. In addition, when risperidone, amisulpride, and olanzapine were the primary AP medications, adjunctive paeoniae/glycyrrhiza = 1:1, aripiprazole <5 mg/day, and aripiprazole >10 mg/day were the most effective treatments in reducing the prolactin levels, respectively. Adjunctive aripiprazole, metformin, and PGD showed beneficial effects in reducing AP-induced hyperprolactinemia in schizophrenia, with aripiprazole (<5 mg/day) being the most effective one.

Neurally-constrained modeling of human gaze strategies in a change blindness task

Despite possessing the capacity for selective attention, we often fail to notice the obvious. We investigated participants’ (n = 39) failures to detect salient changes in a change blindness experiment. Surprisingly, change detection success varied by over two-fold across participants. These variations could not be readily explained by differences in scan paths or fixated visual features. Yet, two simple gaze metrics–mean duration of fixations and the variance of saccade amplitudes–systematically predicted change detection success. We explored the mechanistic underpinnings of these results with a neurally-constrained model based on the Bayesian framework of sequential probability ratio testing, with a posterior odds-ratio rule for shifting gaze. The model’s gaze strategies and success rates closely mimicked human data. Moreover, the model outperformed a state-of-the-art deep neural network (DeepGaze II) with predicting human gaze patterns in this change blindness task. Our mechanistic model reveals putative rational observer search strategies for change detection during change blindness, with critical real-world implications.

On the Potential Mismatch between the Function of the Bayes Factor and Researchers’ Expectations

The aim of this study is to investigate whether there is a potential mismatch between the usability of a statistical tool and psychology researchers’ expectation of it. Bayesian statistics is often promoted as an ideal substitute for frequentists statistics since it coincides better with researchers’ expectations and needs. A particular incidence of this is the proposal of replacing Null Hypothesis Significance Testing (NHST) by Null Hypothesis Bayesian Testing (NHBT) using the Bayes factor. In this paper, it is studied to what extent the usability and expectations of NHBT match well. First, a study of the reporting practices in 73 psychological publications was carried out. It was found that eight Questionable Reporting and Interpreting Practices (QRIPs) occur more than once among the practitioners when doing NHBT. Specifically, our analysis provides insight into possible mismatches and their occurrence frequencies. A follow-up survey study has been conducted to assess such mismatches. The sample (N = 108) consisted of psychology researchers, experts in methodology (and/or statistics), and applied researchers in fields other than psychology. The data show that discrepancies exist among the participants. Interpreting the Bayes Factor as posterior odds and not acknowledging the notion of relative evidence in the Bayes Factor are arguably the most concerning ones. The results of the paper suggest that a shift of statistical paradigm cannot solve the problem of misinterpretation altogether if the users are not well acquainted with the tools.

A Feasibility Study to Increase Chronic Hepatitis C Virus RNA Testing and Linkage to Care among Clients Attending Homeless Services in Amsterdam, The Netherlands

People who inject drugs (PWID) are disproportionately affected by hepatitis C virus (HCV) infections and are frequently homeless. To improve HCV case finding in these individuals, we examined the feasibility of rapid HCV RNA testing in homeless services in Amsterdam. In 2020, we provided a comprehensive service to homeless facilities, which included workshops on HCV for personnel, a “hepatitis ambassador” at each facility, a rapid, onsite HCV RNA fingerstick test service, and assistance with linkage to care. Risk factors for HCV RNA-positive status were examined using Bayesian logistic regression. Of the 152 participants enrolled, 150 (87% men; median age: 47 years) accepted rapid HCV testing. Seven tested HCV RNA positive (4.7%, 95%CrI = 1.31–8.09; 7/150). Of these, five (71%) were linked to care, of whom four (57%, 4/7) initiated treatment and one (14%, 1/7) delayed treatment due to a drug–drug interaction. Of these four people, two completed treatment (50%), of whom one (25%) achieved sustained virologic response after 12 weeks. HCV RNA-positive individuals were more likely to originate from Eastern Europe (posterior-odds ratio (OR) = 3.59 (95% credible interval (CrI) = 1.27–10.04)) and to inject drugs (ever: posterior-OR = 3.89 (95% CrI = 1.37–11.09); recent: posterior-OR = 3.94 (95% CrI = 1.29–11.71)). We identified HCV RNA-positive individuals and linkage to care was relatively high. Screening in homeless services with rapid testing is feasible and could improve HCV case finding for PWID who do not regularly attend primary care or other harm reduction services for people who use drugs.

New Estimators of the Bayes Factor for Models with High-Dimensional Parameter and/or Latent Variable Spaces

Formal Bayesian comparison of two competing models, based on the posterior odds ratio, amounts to estimation of the Bayes factor, which is equal to the ratio of respective two marginal data density values. In models with a large number of parameters and/or latent variables, they are expressed by high-dimensional integrals, which are often computationally infeasible. Therefore, other methods of evaluation of the Bayes factor are needed. In this paper, a new method of estimation of the Bayes factor is proposed. Simulation examples confirm good performance of the proposed estimators. Finally, these new estimators are used to formally compare different hybrid Multivariate Stochastic Volatility–Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MSV-MGARCH) models which have a large number of latent variables. The empirical results show, among other things, that the validity of reduction of the hybrid MSV-MGARCH model to the MGARCH specification depends on the analyzed data set as well as on prior assumptions about model parameters.

Bayesian Unit Root Test for AR(1) Model with Trend Approximated

The objective of present study is to develop a time series model for handling the non-linear trend process using a spline function. Spline function is a piecewise polynomial segment concerning the time component. The main advantage of spline function is the approximation, non linear time trend, but linear time trend between the consecutive join points. A unit root hypothesis is projected to test the non stationarity due to presence of unit root in the proposed model. In the autoregressive model with linear trend, the time trend vanishes under the unit root case. However, when non-linear trend is present and approximated by the linear spline function, through the trend component is absent under the unit root case, but the intercept term makes a shift with r knots. For decision making under the Bayesian perspective, the posterior odds ratio is used for hypothesis testing problems. We have derived the posterior probability for the assumed hypotheses under appropriate prior information. A simulation study and an empirical application are presented to examine the performance of theoretical outcomes.

Association between Household Livestock Ownership and Childhood Stunting in Bangladesh – A Spatial Analysis

Livestock is an integrated part of agriculture, yet the relationship between household livestock ownership and child nutrition is a significant knowledge gap. The present study aimed to assess the association between household livestock ownership and childhood stunting and to explore the geospatial variations at district level in Bangladesh. A complete data of 19 295 children aged below 5 years were extracted from the latest Bangladesh Multiple Indicator Cluster Survey 2012–13. The tropical livestock unit (TLU) score calculated as a weighted value for each livestock and categorized as low, medium, and high using tertile. A hierarchical Bayesian spatial logistic model was used to assess the association between TLU and childhood stunting. Children from the household with high TLU were 10% less likely to be stunted (adjusted posterior odds ratio: 0.90, 95% credible interval: 0.84–0.97) after controlling for demographic, socioeconomic, morbidity, place of residence and spatial effects. There was also a substantial spatial variation in childhood stunting across districts in Bangladesh with the highest burden in the Northern and North-Eastern regions. The positive effect of household livestock ownership on reducing child stunting suggests that, in addition to nutritional intervention in Bangladesh, efforts to strengthen livestock production would be beneficial for improving child nutrition status. However, a small effect size may be owing to the lack of dietary diversity, livestock health and productivity data as well as the complexity of the relationship, requiring further study. Furthermore, a significant regional disparity in stunting highlighted the importance of spatial targeting during the design of interventions and implementation.

With Bayesian Estimation One Can Get All That Bayes Factors Offer, and More

Null Hypothesis Bayesian Testing (NHBT) has been proposed as an alternative to Null Hypothesis Significance Testing (NHST). Whereas NHST has a close link to parameter estimation via confidence intervals, such a link of NHBT with Bayesian estimation via a posterior distribution is less straightforward, but does exist, and has recently been reiterated by Rouder, Haaf, and Vandekerckhove (2018). It hinges on a combination of a point mass probability and a probability density function as prior (denoted as the spike-and-slab prior). In the present paper it is first carefully explained how the spike-and-slab prior is defined, and how results can be derived for which proofs were not given in Rouder et al. (2018). Next, it is shown that this spike-and-slab prior can be approximated by a pure probability density function with a rectangular peak around the center towering highly above the remainder of the density function. Finally, we will indicate how this ‘hill-and-chimney’ prior may in turn be approximated by fully continuous priors. In this way it is shown that NHBT results can be approximated well by results from estimation using a strongly peaked prior, and it is noted that the estimation itself offers more than merely the posterior odds ratio on which NHBT is based. Thus, it complies with the strong APA requirement of not just mentioning testing results but also offering effect size information. It also offers a transparent perspective on the NHBT approach employing a prior with a strong peak around the chosen point null hypothesis value.