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.

Glomerular filtration rate estimates decrease during high altitude expedition but increase with Lake Louise acute mountain sickness scores

AIM: Acute mountain sickness (AMS) can result in pulmonary and cerebral oedema with overperfusion of microvascular beds, elevated hydrostatic capillary pressure, capillary leakage and consequent oedema as pathogenetic mechanisms. Data on changes in glomerular filtration rate (GFR) at altitudes above 5000 m are very limited. METHODS: Thirty-four healthy mountaineers, who were randomized to two acclimatization protocols, undertook an expedition on Muztagh Ata Mountain (7549 m) in China. Tests were performed at five altitudes: Zurich pre-expedition (PE, 450 m), base camp (BC, 4497 m), Camp 1 (C1, 5533 m), Camp 2 (C2, 6265 m) and Camp 3 (C3, 6865 m). Cystatin C- and creatinine-based (Mayo Clinic quadratic equation) GFR estimates (eGFR) were assessed together with Lake Louise AMS score and other tests. RESULTS: eGFR significantly decreased from PE to BC (P < 0.01). However, when analysing at changes between BC and C3, only cystatin C-based estimates indicated a significant decrease in GFR (P = 0.02). There was a linear decrease in eGFR from PE to C3, with a decrease of approx. 3.1 mL min(-1) 1.73 m(-2) per 1000 m increase in altitude. No differences between eGFR of the two groups with different acclimatization protocols could be observed. There was a significant association between eGFR and haematocrit (P = 0.01), whereas no significant association between eGFR and aldosterone, renin and brain natriuretic peptide could be observed. Finally, higher AMS scores were significantly associated with higher eGFR (P = 0.01). CONCLUSIONS: Renal function declines when ascending from low to high altitude. Cystatin C-based eGFR decreases during ascent in high altitude expedition but increases with AMS scores. For individuals with eGFR <40 mL min(-1) 1.73 m(-2), caution may be necessary when planning trips to high altitude above 4500 m above sea level.

Data-driven estimates of the number of clusters in multivariate time series

An important problem in unsupervised data clustering is how to determine the number of clusters. Here we investigate how this can be achieved in an automated way by using interrelation matrices of multivariate time series. Two nonparametric and purely data driven algorithms are expounded and compared. The first exploits the eigenvalue spectra of surrogate data, while the second employs the eigenvector components of the interrelation matrix. Compared to the first algorithm, the second approach is computationally faster and not limited to linear interrelation measures.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

Non-ignorable loss to follow-up: correcting mortality estimates based on additional outcome ascertainment

Loss to follow-up (LTFU) is a common problem in many epidemiological studies. In antiretroviral treatment (ART) programs for patients with human immunodeficiency virus (HIV), mortality estimates can be biased if the LTFU mechanism is non-ignorable, that is, mortality differs between lost and retained patients. In this setting, routine procedures for handling missing data may lead to biased estimates. To appropriately deal with non-ignorable LTFU, explicit modeling of the missing data mechanism is needed. This can be based on additional outcome ascertainment for a sample of patients LTFU, for example, through linkage to national registries or through survey-based methods. In this paper, we demonstrate how this additional information can be used to construct estimators based on inverse probability weights (IPW) or multiple imputation. We use simulations to contrast the performance of the proposed estimators with methods widely used in HIV cohort research for dealing with missing data. The practical implications of our approach are illustrated using South African ART data, which are partially linkable to South African national vital registration data. Our results demonstrate that while IPWs and proper imputation procedures can be easily constructed from additional outcome ascertainment to obtain valid overall estimates, neglecting non-ignorable LTFU can result in substantial bias. We believe the proposed estimators are readily applicable to a growing number of studies where LTFU is appreciable, but additional outcome data are available through linkage or surveys of patients LTFU. Copyright © 2013 John Wiley & Sons, Ltd.

Spatial heterogeneity and lake morphology affect diffusive greenhouse gas emission estimates of lakes

Most estimates of diffusive flux (F) of methane (CH4) and carbon dioxide (CO2) from lakes are based on single-point flux chamber measurements or on piston velocity (k) modeled from wind speed and single-point measurements of surface water gas concentrations (C-aq). We analyzed spatial variability of F of CH4 and CO2, as well as C-aq and k in 22 European lakes during late summer. F and k were higher in the lake centers, leading to considerable bias when extrapolating single-point chamber measurements to whole-lake estimates. The ratio of our empirical k estimates to wind speed-modeled k was related to lake size and shape, suggesting a lake morphology effect on the relationship between wind speed and k. This indicates that the error inherent to established wind speed models can be reduced by determining k and C-aq at multiple sites on lakes to calibrate wind speed-modeled k to the local system.

Recognition memory across the lifespan: the impact of word frequency and study-test interval on estimates of familiarity and recollection

The goal of this study was to investigate recognition memory performance across the lifespan and to determine how estimates of recollection and familiarity contribute to performance. In each of three experiments, participants from five groups from 14 up to 85 years of age (children, young adults, middle-aged adults, young-old adults, and old-old adults) were presented with high- and low-frequency words in a study phase and were tested immediately afterwards and/or after a one day retention interval. The results showed that word frequency and retention interval affected recognition memory performance as well as estimates of recollection and familiarity. Across the lifespan, the trajectory of recognition memory followed an inverse u-shape function that was neither affected by word frequency nor by retention interval. The trajectory of estimates of recollection also followed an inverse u-shape function, and was especially pronounced for low-frequency words. In contrast, estimates of familiarity did not differ across the lifespan. The results indicate that age differences in recognition memory are mainly due to differences in processes related to recollection while the contribution of familiarity-based processes seems to be age-invariant.