A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

Effect of initial treatment strategy on survival of patients with advanced-stage Hodgkin's lymphoma: a systematic review and network meta-analysis

BACKGROUND Several treatment strategies are available for adults with advanced-stage Hodgkin's lymphoma, but studies assessing two alternative standards of care-increased dose bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone (BEACOPPescalated), and doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD)-were not powered to test differences in overall survival. To guide treatment decisions in this population of patients, we did a systematic review and network meta-analysis to identify the best initial treatment strategy. METHODS We searched the Cochrane Library, Medline, and conference proceedings for randomised controlled trials published between January, 1980, and June, 2013, that assessed overall survival in patients with advanced-stage Hodgkin's lymphoma given BEACOPPbaseline, BEACOPPescalated, BEACOPP variants, ABVD, cyclophosphamide (mechlorethamine), vincristine, procarbazine, and prednisone (C[M]OPP), hybrid or alternating chemotherapy regimens with ABVD as the backbone (eg, COPP/ABVD, MOPP/ABVD), or doxorubicin, vinblastine, mechlorethamine, vincristine, bleomycin, etoposide, and prednisone combined with radiation therapy (the Stanford V regimen). We assessed studies for eligibility, extracted data, and assessed their quality. We then pooled the data and used a Bayesian random-effects model to combine direct comparisons with indirect evidence. We also reconstructed individual patient survival data from published Kaplan-Meier curves and did standard random-effects Poisson regression. Results are reported relative to ABVD. The primary outcome was overall survival. FINDINGS We screened 2055 records and identified 75 papers covering 14 eligible trials that assessed 11 different regimens in 9993 patients, providing 59 651 patient-years of follow-up. 1189 patients died, and the median follow-up was 5·9 years (IQR 4·9-6·7). Included studies were of high methodological quality, and between-trial heterogeneity was negligible (τ(2)=0·01). Overall survival was highest in patients who received six cycles of BEACOPPescalated (HR 0·38, 95% credibility interval [CrI] 0·20-0·75). Compared with a 5 year survival of 88% for ABVD, the survival benefit for six cycles of BEACOPPescalated is 7% (95% CrI 3-10)-ie, a 5 year survival of 95%. Reconstructed individual survival data showed that, at 5 years, BEACOPPescalated has a 10% (95% CI 3-15) advantage over ABVD in overall survival. INTERPRETATION Six cycles of BEACOPPescalated significantly improves overall survival compared with ABVD and other regimens, and thus we recommend this treatment strategy as standard of care for patients with access to the appropriate supportive care.

Adjudication-related processes are underreported and lack standardization in clinical trials of venous thromboembolism: a systematic review

OBJECTIVES Although the use of an adjudication committee (AC) for outcomes is recommended in randomized controlled trials, there are limited data on the process of adjudication. We therefore aimed to assess whether the reporting of the adjudication process in venous thromboembolism (VTE) trials meets existing quality standards and which characteristics of trials influence the use of an AC. STUDY DESIGN AND SETTING We systematically searched MEDLINE and the Cochrane Library from January 1, 2003, to June 1, 2012, for randomized controlled trials on VTE. We abstracted information about characteristics and quality of trials and reporting of adjudication processes. We used stepwise backward logistic regression model to identify trial characteristics independently associated with the use of an AC. RESULTS We included 161 trials. Of these, 68.9% (111 of 161) reported the use of an AC. Overall, 99.1% (110 of 111) of trials with an AC used independent or blinded ACs, 14.4% (16 of 111) reported how the adjudication decision was reached within the AC, and 4.5% (5 of 111) reported on whether the reliability of adjudication was assessed. In multivariate analyses, multicenter trials [odds ratio (OR), 8.6; 95% confidence interval (CI): 2.7, 27.8], use of a data safety-monitoring board (OR, 3.7; 95% CI: 1.2, 11.6), and VTE as the primary outcome (OR, 5.7; 95% CI: 1.7, 19.4) were associated with the use of an AC. Trials without random allocation concealment (OR, 0.3; 95% CI: 0.1, 0.8) and open-label trials (OR, 0.3; 95% CI: 0.1, 1.0) were less likely to report an AC. CONCLUSION Recommended processes of adjudication are underreported and lack standardization in VTE-related clinical trials. The use of an AC varies substantially by trial characteristics.

Biodiversity effects on nitrate concentrations in soil solution: a Bayesian model

Ecosystems are faced with high rates of species loss which has consequences for their functions and services. To assess the effects of plant species diversity on the nitrogen (N) cycle, we developed a model for monthly mean nitrate (NO3-N) concentrations in soil solution in 0-30 cm mineral soil depth using plant species and functional group richness and functional composition as drivers and assessing the effects of conversion of arable land to grassland, spatially heterogeneous soil properties, and climate. We used monthly mean NO3-N concentrations from 62 plots of a grassland plant diversity experiment from 2003 to 2006. Plant species richness (1-60) and functional group composition (1-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Plant community composition, time since conversion from arable land to grassland, soil texture, and climate data (precipitation, soil moisture, air and soil temperature) were used to develop one general Bayesian multiple regression model for the 62 plots to allow an in-depth evaluation using the experimental design. The model simulated NO3-N concentrations with an overall Bayesian coefficient of determination of 0.48. The temporal course of NO3-N concentrations was simulated differently well for the individual plots with a maximum plot-specific Nash-Sutcliffe Efficiency of 0.57. The model shows that NO3-N concentrations decrease with species richness, but this relation reverses if more than approx. 25 % of legume species are included in the mixture. Presence of legumes increases and presence of grasses decreases NO3-N concentrations compared to mixtures containing only small and tall herbs. Altogether, our model shows that there is a strong influence of plant community composition on NO3-N concentrations.

WGTTEST: Stata module to test the impact of sampling weights in regression analysis

wgttest performs a test proposed by DuMouchel and Duncan (1983) to evaluate whether the weighted and unweighted estimates of a regression model are significantly different.

The nasal microbiota in infants with cystic fibrosis in the first year of life: a prospective cohort study.

BACKGROUND Respiratory tract infections and subsequent airway inflammation occur early in the life of infants with cystic fibrosis. However, detailed information about the microbial composition of the respiratory tract in infants with this disorder is scarce. We aimed to undertake longitudinal in-depth characterisation of the upper respiratory tract microbiota in infants with cystic fibrosis during the first year of life. METHODS We did this prospective cohort study at seven cystic fibrosis centres in Switzerland. Between Feb 1, 2011, and May 31, 2014, we enrolled 30 infants with a diagnosis of cystic fibrosis. Microbiota characterisation was done with 16S rRNA gene pyrosequencing and oligotyping of nasal swabs collected every 2 weeks from the infants with cystic fibrosis. We compared these data with data for an age-matched cohort of 47 healthy infants. We additionally investigated the effect of antibiotic treatment on the microbiota of infants with cystic fibrosis. Statistical methods included regression analyses with a multivariable multilevel linear model with random effects to correct for clustering on the individual level. FINDINGS We analysed 461 nasal swabs taken from the infants with cystic fibrosis; the cohort of healthy infants comprised 872 samples. The microbiota of infants with cystic fibrosis differed compositionally from that of healthy infants (p=0·001). This difference was also found in exclusively antibiotic-naive samples (p=0·001). The disordering was mainly, but not solely, due to an overall increase in the mean relative abundance of Staphylococcaceae in infants with cystic fibrosis compared with healthy infants (multivariable linear regression model stratified by age and adjusted for season; second month: coefficient 16·2 [95% CI 0·6-31·9]; p=0·04; third month: 17·9 [3·3-32·5]; p=0·02; fourth month: 21·1 [7·8-34·3]; p=0·002). Oligotyping analysis enabled differentiation between Staphylococcus aureus and coagulase-negative Staphylococci. Whereas the analysis showed a decrease in S aureus at and after antibiotic treatment, coagulase-negative Staphylococci increased. INTERPRETATION Our study describes compositional differences in the microbiota of infants with cystic fibrosis compared with healthy controls, and disordering of the microbiota on antibiotic administration. Besides S aureus, coagulase-negative Staphylococci also contributed to the disordering identified in these infants. These findings are clinically important in view of the crucial role that bacterial pathogens have in the disease progression of cystic fibrosis in early life. Our findings could be used to inform future studies of the effect of antibiotic treatment on the microbiota in infants with cystic fibrosis, and could assist in the prevention of early disease progression in infants with this disorder. FUNDING Swiss National Science Foundation, Fondation Botnar, the Swiss Society for Cystic Fibrosis, and the Swiss Lung Association Bern.