Is the allegiance effect an epiphenomenon of true efficacy differences between treatments? a meta-analysis

Many meta-analyses of comparative outcome studies found a substantial association of researcher allegiance (RA) and relative treatment effects. Therefore, RA is regarded as a biasing factor in comparative outcome research (RA bias hypothesis). However, the RA bias hypothesis has been criticized as causality might be reversed. That is, RA might be a reflection of true efficacy differences between treatments (true efficacy hypothesis). Consequently, the RA-outcome association would not be indicative of bias but an epiphenomenon of true efficacy differences. This meta-analysis tested the validity of the true efficacy hypothesis. This was done by controlling the RA-outcome association for true efficacy differences by restricting analysis to direct comparisons of treatments with equivalent efficacy. We included direct comparisons of different versions of trauma-focused therapy (TFT) in the treatment of posttraumatic stress disorder (PTSD). RA was measured from the research reports. Relative effect sizes for symptoms of PTSD were calculated. Random effects meta-regression was conducted. Twenty-nine comparisons of TFTs from 20 studies were identified. Initial heterogeneity among relative effect sizes was low. RA was a significant predictor of outcome and explained 12% of the variance in outcomes. The true efficacy hypothesis predicted the RA-outcome association to be zero; however, a substantial association was found. Thus, this study does not support the true efficacy hypothesis. Given findings from psychotherapy research and other fields that support a biasing influence of researcher preferences, RA should be regarded as a causal factor and conceptualized as a threat to the validity of conclusions from comparative outcome studies.

Analysis of postprandial lipemia as a Cardiovascular Disease risk factor using genetic and clinical information: an Artificial Neural Network perspective

Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies

Low self-esteem and depression are strongly related, but there is not yet consistent evidence on the nature of the relation. Whereas the vulnerability model states that low self-esteem contributes to depression, the scar model states that depression erodes self-esteem. Furthermore, it is unknown whether the models are specific for depression or whether they are also valid for anxiety. We evaluated the vulnerability and scar models of low self-esteem and depression, and low self-esteem and anxiety, by meta-analyzing the available longitudinal data (covering 77 studies on depression and 18 studies on anxiety). The mean age of the samples ranged from childhood to old age. In the analyses, we used a random-effects model and examined prospective effects between the variables, controlling for prior levels of the predicted variables. For depression, the findings supported the vulnerability model: The effect of self-esteem on depression (β = -.16) was significantly stronger than the effect of depression on self-esteem (β = -.08). In contrast, the effects between low self-esteem and anxiety were relatively balanced: Self-esteem predicted anxiety with β = -.10, and anxiety predicted self-esteem with β = -.08. Moderator analyses were conducted for the effect of low self-esteem on depression; these suggested that the effect is not significantly influenced by gender, age, measures of self-esteem and depression, or time lag between assessments. If future research supports the hypothesized causality of the vulnerability effect of low self-esteem on depression, interventions aimed at increasing self-esteem might be useful in reducing the risk of depression.

A Comparative Analysis of Bronchial Stricture After Lung Transplantation in Recipients With and Without Early Acute Rejection

BACKGROUND: Risk factors and outcomes of bronchial stricture after lung transplantation are not well defined. An association between acute rejection and development of stricture has been suggested in small case series. We evaluated this relationship using a large national registry. METHODS: All lung transplantations between April 1994 and December 2008 per the United Network for Organ Sharing (UNOS) database were analyzed. Generalized linear models were used to determine the association between early rejection and development of stricture after adjusting for potential confounders. The association of stricture with postoperative lung function and overall survival was also evaluated. RESULTS: Nine thousand three hundred thirty-five patients were included for analysis. The incidence of stricture was 11.5% (1,077/9,335), with no significant change in incidence during the study period (P=0.13). Early rejection was associated with a significantly greater incidence of stricture (adjusted odds ratio [AOR], 1.40; 95% confidence interval [CI], 1.22-1.61; p<0.0001). Male sex, restrictive lung disease, and pretransplantation requirement for hospitalization were also associated with stricture. Those who experienced stricture had a lower postoperative peak percent predicted forced expiratory volume at 1 second (FEV1) (median 74% versus 86% for bilateral transplants only; p<0.0001), shorter unadjusted survival (median 6.09 versus 6.82 years; p<0.001) and increased risk of death after adjusting for potential confounders (adjusted hazard ratio 1.13; 95% CI, 1.03-1.23; p=0.007). CONCLUSIONS: Early rejection is associated with an increased incidence of stricture. Recipients with stricture demonstrate worse postoperative lung function and survival. Prospective studies may be warranted to further assess causality and the potential for coordinated rejection and stricture surveillance strategies to improve postoperative outcomes.

What do brain network interactions tell about cognitive processes? How to seek causality?

Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.