Assessment of publication bias in dental specialty journals

OBJECTIVE: The purpose of this study was to investigate the presence of publication bias (acceptance of articles indicating statistically significant results). METHODS: The journals possessing the highest impact factor (2008 data) in each dental specialty were included in the study. The content of the 6 most recent issues of each journal was hand searched and research articles were classified into 4 type categories: cross-sectional, case-control, cohort, and interventional (nonrandomized clinical trials and randomized controlled trials). In total, 396 articles were included in the analysis. Descriptive statistics and univariate and multivariate logistic regression was used to examine the association between article-reported statistical significance (dependent variable) and journal impact factor and article study type subject area (independent variables). RESULTS: A statistically significant acceptance rate of positive result was found, ranging from 75% to 90%, whereas the value of impact factor was not related to publication bias among leading dental journals. Compared with other research designs, clinical intervention studies (randomized or nonrandomized) presented the highest percentage of nonsignificant findings (20%); RCTs represented 6% of the examined investigations. CONCLUSIONS: Compared with the Journal of Clinical Periodontology, all other subspecialty journals, except the Journal of Oral and Maxillofacial Surgery, showed significantly decreased odds of publishing an RCT, which ranged from 60% to 93% (P < .05).

Search for a heavy particle decaying into an electron and a muon with the ATLAS detector in sqrt[s] = 7 TeV pp collisions at the LHC

This Letter presents the first search for a heavy particle decaying into an e ± μ(-/+) final state in sqrt[s] = 7 TeV pp collisions at the LHC. The data were recorded by the ATLAS detector during 2010 and correspond to a total integrated luminosity of 35 pb(-1). No excess above the standard model background expectation is observed. Exclusions at 95% confidence level are placed on two representative models. In an R-parity violating supersymmetric model, tau sneutrinos with a mass below 0.75 TeV are excluded, assuming all R-parity violating couplings are zero except λ(311)' = 0.11 and λ312 = 0.07. In a lepton flavor violating model, a Z'-like vector boson with masses of 0.70-1.00 TeV and corresponding cross sections times branching ratios of 0.175-0.183 pb is excluded. These results extend to higher mass R-parity violating sneutrinos and lepton flavor violating Z's than previous constraints from the Tevatron.

Simultaneous Multiscale Polyaffine Registration by Incorporating Deformation Statistics

Locally affine (polyaffine) image registration methods capture intersubject non-linear deformations with a low number of parameters, while providing an intuitive interpretation for clinicians. Considering the mandible bone, anatomical shape differences can be found at different scales, e.g. left or right side, teeth, etc. Classically, sequential coarse to fine registration are used to handle multiscale deformations, instead we propose a simultaneous optimization of all scales. To avoid local minima we incorporate a prior on the polyaffine transformations. This kind of groupwise registration approach is natural in a polyaffine context, if we assume one configuration of regions that describes an entire group of images, with varying transformations for each region. In this paper, we reformulate polyaffine deformations in a generative statistical model, which enables us to incorporate deformation statistics as a prior in a Bayesian setting. We find optimal transformations by optimizing the maximum a posteriori probability. We assume that the polyaffine transformations follow a normal distribution with mean and concentration matrix. Parameters of the prior are estimated from an initial coarse to fine registration. Knowing the region structure, we develop a blockwise pseudoinverse to obtain the concentration matrix. To our knowledge, we are the first to introduce simultaneous multiscale optimization through groupwise polyaffine registration. We show results on 42 mandible CT images.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

Stroke events, and case fatalities in Switzerland based on hospital statistics and cause of death statistics

OBJECTIVE: In Switzerland there is a shortage of population-based information on stroke incidence and case fatalities (CF). The aim of this study was to estimate stroke event rates and both in- and out-of-hospital CF rates. METHODS: Data on stroke diagnoses, coded according to I60-I64 (ICD 10), were taken from the Federal Hospital Discharge Statistics database (HOST) and the Cause of Death database (CoD) for the year 2004. The number of total stroke events and of age- and gender-specific and agestandardised event rates were estimated; overall CF, in-hospital and out-of-hospital, were determined. RESULTS: Among the overall number of 13 996 hospital discharges from stroke (HOST) the number was lower in women (n = 6736) than in men (n = 7260). A total of 3568 deaths (2137 women and 1431 men) due to stroke were recorded in the CoD database. The number of estimated stroke events was 15 733, and higher in women (n = 7933) than in men (n = 7800). Men presented significantly higher age-specific stroke event rates and a higher age-standardised event rate (178.7/100 000 versus 119.7/100 000). Overall CF rates were significantly higher for women (26.9%) than for men (18.4%). The same was true of out-of-hospital CF but not of in-hospital CF rates. CONCLUSION: The data on estimated stroke events obtained indicate that stroke discharge rate underestimates the stroke event rate. Out-of-hospital deaths from stroke accounted for the largest proportion of total stroke deaths. Sex differences in both number of total stroke events and deaths could be explained by the higher proportion of women than men aged 55+ in the Swiss population.

Bayesian statistics in oncology: a guide for the clinical investigator

The rise of evidence-based medicine as well as important progress in statistical methods and computational power have led to a second birth of the >200-year-old Bayesian framework. The use of Bayesian techniques, in particular in the design and interpretation of clinical trials, offers several substantial advantages over the classical statistical approach. First, in contrast to classical statistics, Bayesian analysis allows a direct statement regarding the probability that a treatment was beneficial. Second, Bayesian statistics allow the researcher to incorporate any prior information in the analysis of the experimental results. Third, Bayesian methods can efficiently handle complex statistical models, which are suited for advanced clinical trial designs. Finally, Bayesian statistics encourage a thorough consideration and presentation of the assumptions underlying an analysis, which enables the reader to fully appraise the authors' conclusions. Both Bayesian and classical statistics have their respective strengths and limitations and should be viewed as being complementary to each other; we do not attempt to make a head-to-head comparison, as this is beyond the scope of the present review. Rather, the objective of the present article is to provide a nonmathematical, reader-friendly overview of the current practice of Bayesian statistics coupled with numerous intuitive examples from the field of oncology. It is hoped that this educational review will be a useful resource to the oncologist and result in a better understanding of the scope, strengths, and limitations of the Bayesian approach.

Self-reported alcohol consumption and its association with adherence and outcome of antiretroviral therapy in the Swiss HIV Cohort Study

BACKGROUND: Alcohol consumption leading to morbidity and mortality affects HIV-infected individuals. Here, we aimed to study self-reported alcohol consumption and to determine its association with adherence to antiretroviral therapy (ART) and HIV surrogate markers. METHODS: Cross-sectional data on daily alcohol consumption from August 2005 to August 2007 were analysed and categorized according to the World Health Organization definition (light, moderate or severe health risk). Multivariate logistic regression models and Pearson's chi(2) statistics were used to test the influence of alcohol use on endpoints. RESULTS: Of 6,323 individuals, 52.3% consumed alcohol less than once a week in the past 6 months. Alcohol intake was deemed light in 39.9%, moderate in 5.0% and severe in 2.8%. Higher alcohol consumption was significantly associated with older age, less education, injection drug use, being in a drug maintenance programme, psychiatric treatment, hepatitis C virus coinfection and with a longer time since diagnosis of HIV. Lower alcohol consumption was found in males, non-Caucasians, individuals currently on ART and those with more ART experience. In patients on ART (n=4,519), missed doses and alcohol consumption were positively correlated (P<0.001). Severe alcohol consumers, who were pretreated with ART, were more often off treatment despite having CD4+ T-cell count <200 cells/microl; however, severe alcohol consumption per se did not delay starting ART. In treated individuals, alcohol consumption was not associated with worse HIV surrogate markers. CONCLUSIONS: Higher alcohol consumption in HIV-infected individuals was associated with several psychosocial and demographic factors, non-adherence to ART and, in pretreated individuals, being off treatment despite low CD4+ T-cell counts.

A three-dimensional histological atlas of the human basal ganglia. II. Atlas deformation strategy and evaluation in deep brain stimulation for Parkinson disease

OBJECT: The localization of any given target in the brain has become a challenging issue because of the increased use of deep brain stimulation to treat Parkinson disease, dystonia, and nonmotor diseases (for example, Tourette syndrome, obsessive compulsive disorders, and depression). The aim of this study was to develop an automated method of adapting an atlas of the human basal ganglia to the brains of individual patients. METHODS: Magnetic resonance images of the brain specimen were obtained before extraction from the skull and histological processing. Adaptation of the atlas to individual patient anatomy was performed by reshaping the atlas MR images to the images obtained in the individual patient using a hierarchical registration applied to a region of interest centered on the basal ganglia, and then applying the reshaping matrix to the atlas surfaces. RESULTS: Results were evaluated by direct visual inspection of the structures visible on MR images and atlas anatomy, by comparison with electrophysiological intraoperative data, and with previous atlas studies in patients with Parkinson disease. The method was both robust and accurate, never failing to provide an anatomically reliable atlas to patient registration. The registration obtained did not exceed a 1-mm mismatch with the electrophysiological signatures in the region of the subthalamic nucleus. CONCLUSIONS: This registration method applied to the basal ganglia atlas forms a powerful and reliable method for determining deep brain stimulation targets within the basal ganglia of individual patients.