Avoiding misclassification bias with the traditional Charnley classification: rationale for a fourth Charnley class BB

Long-term follow up of patients with total hip arthroplasty (THA) revealed a marked deterioration of walking capacities in Charnley class B after postoperative year 4. We hypothesized that a specific group of patients, namely those with unilateral hip arthroplasty and an untreated but affected contralateral hip was responsible for this observation. Therefore, we conducted a study taking into consideration the two subclasses that make up Charnley class B: patients with unilateral THA and contralateral hip disease and patients with bilateral THA. A sample of 15,160 patients with 35,773 follow ups that were prospectively collected over 10 years was evaluated. The sample was categorized into four classes according to a new modified Charnley classification. Annual analyses of the proportion of patients with ambulation longer than 60 min were conducted. The traditionally labeled Charnley class B consists of two very different patient groups with respect to their walking capacities. Those with unilateral THA and contralateral hip disease have underaverage walking capacities and a deterioration of ambulation beginning 3 to 4 years after surgery. Those with bilateral THA have stable overaverage walking capacities similar to Charnley class A. An extension of the traditional Charnley classification is proposed, taking into account the two different patient groups in Charnley class B. The new fourth Charnley class consists of patients with bilateral THA and was labeled BB in order to express the presence of two artificial hip joints and to preserve the traditional classification A through C.

Association between reported exposure to road traffic and respiratory symptoms in children: evidence of bias

BACKGROUND: Many studies showing effects of traffic-related air pollution on health rely on self-reported exposure, which may be inaccurate. We estimated the association between self-reported exposure to road traffic and respiratory symptoms in preschool children, and investigated whether the effect could have been caused by reporting bias. METHODS: In a random sample of 8700 preschool children in Leicestershire, UK, exposure to road traffic and respiratory symptoms were assessed by a postal questionnaire (response rate 80%). The association between traffic exposure and respiratory outcomes was assessed using unconditional logistic regression and conditional regression models (matching by postcode). RESULTS: Prevalence odds ratios (95% confidence intervals) for self-reported road traffic exposure, comparing the categories 'moderate' and 'dense', respectively, with 'little or no' were for current wheezing: 1.26 (1.13-1.42) and 1.30 (1.09-1.55); chronic rhinitis: 1.18 (1.05-1.31) and 1.31 (1.11-1.56); night cough: 1.17 (1.04-1.32) and 1.36 (1.14-1.62); and bronchodilator use: 1.20 (1.04-1.38) and 1.18 (0.95-1.46). Matched analysis only comparing symptomatic and asymptomatic children living at the same postcode (thus exposed to similar road traffic) showed similar ORs, suggesting that parents of children with respiratory symptoms reported more road traffic than parents of asymptomatic children. CONCLUSIONS: Our study suggests that reporting bias could explain some or even all the association between reported exposure to road traffic and disease. Over-reporting of exposure by only 10% of parents of symptomatic children would be sufficient to produce the effect sizes shown in this study. Future research should be based only on objective measurements of traffic exposure.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

A non-spatial bias favouring fixated stimuli revealed in patients with spatial neglect

The cardinal feature of spatial neglect is severely impaired exploration of the contralesional space, a failure resulting in unawareness of many contralesional stimuli. This deficit is exacerbated by a reflexive attentional bias toward ipsilesional items. Here we show that, in addition to these spatially lateralized failures, neglect patients also exhibit a severe bias favouring stimuli presented at fixation. We tested neglect patients and matched healthy and right-hemisphere damaged patients without neglect in a task requiring saccade execution to targets in the left or right hemifield. Targets were presented alone or simultaneously with a distracter that appeared in the same hemifield, in the opposite hemifield, or at fixation. We found two fundamental biases in saccade initiation of neglect patients: irrelevant distracters presented in the preserved hemifield tended to capture gaze reflexively, resulting in a large number of saccades erroneously directed toward the distracter. Additionally, distracters presented at fixation severely disrupted saccade initiation irrespective of saccade direction, leading to disproportionately increased latencies of left and right saccades. This latency increase was specific to oculomotor responses of neglect patients and was not observed when a manual response was required. These results show that, in addition to their failure to inhibit reflexive glances toward ipsilesional items neglect patients exhibit a strong oculomotor bias favouring fixated stimuli. We conclude that impaired initiation of saccades in any direction contributes to the deficits of spatial exploration that characterize spatial neglect.

Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study

OBJECTIVE: To examine whether the association of inadequate or unclear allocation concealment and lack of blinding with biased estimates of intervention effects varies with the nature of the intervention or outcome. DESIGN: Combined analysis of data from three meta-epidemiological studies based on collections of meta-analyses. DATA SOURCES: 146 meta-analyses including 1346 trials examining a wide range of interventions and outcomes. MAIN OUTCOME MEASURES: Ratios of odds ratios quantifying the degree of bias associated with inadequate or unclear allocation concealment, and lack of blinding, for trials with different types of intervention and outcome. A ratio of odds ratios <1 implies that inadequately concealed or non-blinded trials exaggerate intervention effect estimates. RESULTS: In trials with subjective outcomes effect estimates were exaggerated when there was inadequate or unclear allocation concealment (ratio of odds ratios 0.69 (95% CI 0.59 to 0.82)) or lack of blinding (0.75 (0.61 to 0.93)). In contrast, there was little evidence of bias in trials with objective outcomes: ratios of odds ratios 0.91 (0.80 to 1.03) for inadequate or unclear allocation concealment and 1.01 (0.92 to 1.10) for lack of blinding. There was little evidence for a difference between trials of drug and non-drug interventions. Except for trials with all cause mortality as the outcome, the magnitude of bias varied between meta-analyses. CONCLUSIONS: The average bias associated with defects in the conduct of randomised trials varies with the type of outcome. Systematic reviewers should routinely assess the risk of bias in the results of trials, and should report meta-analyses restricted to trials at low risk of bias either as the primary analysis or in conjunction with less restrictive analyses.

Systematic review of the empirical evidence of study publication bias and outcome reporting bias

BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention. METHODOLOGY/PRINCIPAL FINDINGS: We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7). In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.