Label-invariant models for the analysis of meta-epidemiological data.

Rich meta-epidemiological data sets have been collected to explore associations between intervention effect estimates and study-level characteristics. Welton et al proposed models for the analysis of meta-epidemiological data, but these models are restrictive because they force heterogeneity among studies with a particular characteristic to be at least as large as that among studies without the characteristic. In this paper we present alternative models that are invariant to the labels defining the 2 categories of studies. To exemplify the methods, we use a collection of meta-analyses in which the Cochrane Risk of Bias tool has been implemented. We first investigate the influence of small trial sample sizes (less than 100 participants), before investigating the influence of multiple methodological flaws (inadequate or unclear sequence generation, allocation concealment, and blinding). We fit both the Welton et al model and our proposed label-invariant model and compare the results. Estimates of mean bias associated with the trial characteristics and of between-trial variances are not very sensitive to the choice of model. Results from fitting a univariable model show that heterogeneity variance is, on average, 88% greater among trials with less than 100 participants. On the basis of a multivariable model, heterogeneity variance is, on average, 25% greater among trials with inadequate/unclear sequence generation, 51% greater among trials with inadequate/unclear blinding, and 23% lower among trials with inadequate/unclear allocation concealment, although the 95% intervals for these ratios are very wide. Our proposed label-invariant models for meta-epidemiological data analysis facilitate investigations of between-study heterogeneity attributable to certain study characteristics

Transoral laser surgery for laryngeal carcinoma: has Steiner achieved a genuine paradigm shift in oncological surgery?

Transoral laser microsurgery applies to the piecemeal removal of malignant tumours of the upper aerodigestive tract using the CO2 laser under the operating microscope. This method of surgery is being increasingly popularised as a single modality treatment of choice in early laryngeal cancers (T1 and T2) and occasionally in the more advanced forms of the disease (T3 and T4), predomi- nantly within the supraglottis. Thomas Kuhn, the American physicist turned philosopher and historian of science, coined the phrase ‘paradigm shift’ in his groundbreaking book The Structure of Scientific Revolutions. He argued that the arrival of the new and often incompatible idea forms the core of a new paradigm, the birth of an entirely new way of thinking. This article discusses whether Steiner and col- leagues truly brought about a paradigm shift in oncological surgery. By rejecting the principle of en block resection and by replacing it with the belief that not only is it oncologically safe to cut through the substance of the tumour but in doing so one can actually achieve better results, Steiner was able to truly revolutionise the man- agement of laryngeal cancer. Even though within this article the repercussions of his insight are limited to the upper aerodigestive tract oncological surgery, his willingness to question other peoples’ dogma makes his contribution truly a genuine paradigm shift

Adjusting trial results for biases in meta-analysis: combining data-based evidence on bias with detailed trial assessment.

Flaws in the conduct of randomized trials can lead to biased estimation of the intervention effect. Methods for adjustment of within-trial biases in meta-analysis include the use of empirical evidence from an external collection of meta-analyses, and the use of expert opinion informed by the assessment of detailed trial information. Our aim is to present methods to combine these two approaches to gain the advantages of both. We make use of the risk of bias information that is routinely available in Cochrane reviews, by obtaining empirical distributions for the bias associated with particular bias profiles (combinations of risk of bias judgements). We propose three methods: a formal combination of empirical evidence and opinion in a Bayesian analysis; asking experts to give an opinion on bias informed by both summary trial information and a bias distribution from the empirical evidence, either numerically or by selecting areas of the empirical distribution. The methods are demonstrated through application to two example binary outcome meta-analyses. Bias distributions based on opinion informed by trial information alone were most dispersed on average, and those based on opinions obtained by selecting areas of the empirical distribution were narrowest. Although the three methods for combining empirical evidence with opinion vary in ease and speed of implementation, they yielded similar results in the two examples

Qualitative Environmental Health Research: An Analysis of the Literature, 1991-2008

BACKGROUND. Recent articles have advocated for the use of qualitative methods in environmental health research. Qualitative research uses nonnumeric data to understand people's opinions, motives, understanding, and beliefs about events or phenomena. OBJECTIVE. In this analysis of the literature, I report the use of qualitative methods and data in the study of the relationship between environmental exposures and human health. DATA SOURCES. A primary search on ISI Web of Knowledge/Web of Science for peer-reviewed journal articles dated from 1991 through 2008 included the following three terms: qualitative, environ*, and health. Inclusion and exclusion criteria are described. DATA EXTRACTION. Searches resulted in 3,155 records. Data were extracted and findings of articles analyzed to determine where and by whom qualitative environmental health research is conducted and published, the types of methods and analyses used in qualitative studies of environmental health, and the types of information qualitative data contribute to environmental health. DATA SYNTHESIS. Ninety-one articles met inclusion criteria. These articles were published in 58 different journals, with a maximum of eight for a single journal. The results highlight a diversity of disciplines and techniques among researchers who used qualitative methods to study environmental health, with most studies relying on one-on-one interviews. Details of the analyses were absent from a large number of studies. Nearly all of the studies identified increased scientific understanding of lay perceptions of environmental health exposures. DISCUSSION AND CONCLUSIONS. Qualitative data are published in traditionally quantitative environmental health studies to a limited extent. However, this analysis demonstrates the potential of qualitative data to improve understanding of complex exposure pathways, including the influence of social factors on environmental health, and health outcomes.National Institute of Environmental Health Sciences (R25 ES012084, P42ES007381

A comparison of prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill: a cohort study

BACKGROUND: This cohort study compared the prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill. METHODS: The relationships between SIG, lactate, anion gap (AG), anion gap albumin-corrected (AG-corrected), base excess or strong ion difference-effective (SIDe), all obtained within the first hour of intensive care unit (ICU) admission, and the hospital mortality of 6878 patients were analysed. The prognostic significance of each acid-base marker, both alone and in combination with the Admission Mortality Prediction Model (MPM0 III) predicted mortality, were assessed by the area under the receiver operating characteristic curve (AUROC). RESULTS: Of the 6878 patients included in the study, 924 patients (13.4 %) died after ICU admission. Except for plasma chloride concentrations, all acid-base markers were significantly different between the survivors and non-survivors. SIG (with lactate: AUROC 0.631, confidence interval [CI] 0.611-0.652; without lactate: AUROC 0.521, 95 % CI 0.500-0.542) only had a modest ability to predict hospital mortality, and this was no better than using lactate concentration alone (AUROC 0.701, 95 % 0.682-0.721). Adding AG-corrected or SIG to a combination of lactate and MPM0 III predicted risks also did not substantially improve the latter's ability to differentiate between survivors and non-survivors. Arterial lactate concentrations explained about 11 % of the variability in the observed mortality, and it was more important than SIG (0.6 %) and SIDe (0.9 %) in predicting hospital mortality after adjusting for MPM0 III predicted risks. Lactate remained as the strongest predictor for mortality in a sensitivity multivariate analysis, allowing for non-linearity of all acid-base markers. CONCLUSIONS: The prognostic significance of SIG was modest and inferior to arterial lactate concentration for the critically ill. Lactate concentration should always be considered regardless whether physiological, base excess or physical-chemical approach is used to interpret acid-base disturbances in critically ill patients

Gamification and Adherence to Web-Based Mental Health Interventions: A Systematic Review

Background: Adherence to effective Web-based interventions for common mental disorders (CMDs) and well-being remains a critical issue, with clear potential to increase effectiveness. Continued identification and examination of “active” technological components within Web-based interventions has been called for. Gamification is the use of game design elements and features in nongame contexts. Health and lifestyle interventions have implemented a variety of game features in their design in an effort to encourage engagement and increase program adherence. The potential influence of gamification on program adherence has not been examined in the context of Web-based interventions designed to manage CMDs and well-being. Objective: This study seeks to review the literature to examine whether gaming features predict or influence reported rates of program adherence in Web-based interventions designed to manage CMDs and well-being. Methods: A systematic review was conducted of peer-reviewed randomized controlled trials (RCTs) designed to manage CMDs or well-being and incorporated gamification features. Seven electronic databases were searched. Results: A total of 61 RCTs met the inclusion criteria and 47 different intervention programs were identified. The majority were designed to manage depression using cognitive behavioral therapy. Eight of 10 popular gamification features reviewed were in use. The majority of studies utilized only one gamification feature (n=58) with a maximum of three features. The most commonly used feature was story/theme. Levels and game leaders were not used in this context. No studies explicitly examined the role of gamification features on program adherence. Usage data were not commonly reported. Interventions intended to be 10 weeks in duration had higher mean adherence than those intended to be 6 or 8 weeks in duration. Conclusions: Gamification features have been incorporated into the design of interventions designed to treat CMD and well-being. Further research is needed to improve understanding of gamification features on adherence and engagement in order to inform the design of future Web-based health interventions in which adherence to treatment is of concern. Conclusions were limited by varied reporting of adherence and usage dat

Diagnostic test accuracy and cost‐effectiveness of tests for codeletion of chromosomal arms 1p and 19q in people with glioma

This is a protocol for a Cochrane Review (Diagnostic test accuracy). The objectives are as follows: To estimate the sensitivity and specificity of each technique for determining 1p/19q codeletion status in glioma, with a view to determining the most sensitive and specific technique(s)

MGMT promoter methylation testing to predict overall survival in people with glioblastoma treated with temozolomide: a comprehensive meta-analysis based on a Cochrane Systematic Review

BACKGROUND: The DNA repair protein O6 methylguanine-DNA methyltransferase (MGMT) causes resistance of tumour cells to alkylating agents. It is a predictive biomarker in high grade gliomas treated with temozolomide, however there is no consensus on which test method, methylation sites, and cut-off values to use. METHODS: We performed a Cochrane Review to examine studies using different techniques to measure MGMT and predict survival in glioblastoma patients treated with temozolomide. Eligible longitudinal studies included adults with glioblastoma treated with temozolomide with or without radiotherapy, or surgery; where MGMT status was determined in tumour tissue, and assessed by one or more technique; and where overall survival was an outcome parameter, with sufficient information to estimate hazard ratios. Two or more methods were compared in 32 independent cohorts with 3474 patients. RESULTS: Methylation-specific PCR (MSP) and pyrosequencing (PSQ) techniques were more prognostic than immunohistochemistry for MGMT protein, and PSQ is a slightly better predictor than MSP. CONCLUSIONS: We cannot draw strong conclusions about use of frozen tissue versus formalin-fixed paraffin embedded in MSP and PSQ. Also, our meta-analysis does not provide strong evidence about the best CpG sites or threshold. MSP has been studied mainly for CpG sites 76-80 and 84-87 and Pyrosequencing at CpG sites ranging from 72 to 95. A cut-off threshold of 9% for CpG sites 74-78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies. 190 studies were identified presenting hazard ratios from survival analysis in patients in which MGMT methylation was measured by one technique only

Agreement was moderate between data-based and opinion-based assessments of biases affecting randomised trials within meta-analyses

BACKGROUND: Randomised trials included in meta-analyses are often affected by bias caused by methodological flaws or limitations, but the degree of bias is unknown. Two proposed methods adjust trial results for bias using: (1) empirical evidence from published meta-epidemiological studies; or (2) expert opinion. METHODS: We investigated agreement between data-based and opinion-based approaches to assessing bias in each of four domains: sequence generation, allocation concealment, blinding and incomplete outcome data. From each sampled meta-analysis, a pair of trials with the highest and lowest empirical model-based bias estimates was selected. Independent assessors were asked which trial within each pair was judged more biased on the basis of detailed trial design summaries. RESULTS: Assessors judged trials to be equally biased in 68% of pairs evaluated. When assessors judged one trial as more biased, the proportion of judgements agreeing with the model-based ranking was highest for allocation concealment (79%) and blinding (79%) and lower for sequence generation (59%) and incomplete outcome data (56%). CONCLUSIONS: Most trial pairs found to be discrepant empirically were judged to be equally biased by assessors. We found moderate agreement between opinion and data-based evidence in pairs where assessors ranked one trial as more biased