A unification of models for meta-analysis of diagnostic accuracy studies

Studies of diagnostic accuracy require more sophisticated methods for their meta-analysis than studies of therapeutic interventions. A number of different, and apparently divergent, methods for meta-analysis of diagnostic studies have been proposed, including two alternative approaches that are statistically rigorous and allow for between-study variability: the hierarchical summary receiver operating characteristic (ROC) model (Rutter and Gatsonis, 2001) and bivariate random-effects meta-analysis (van Houwelingen and others, 1993), (van Houwelingen and others, 2002), (Reitsma and others, 2005). We show that these two models are very closely related, and define the circumstances in which they are identical. We discuss the different forms of summary model output suggested by the two approaches, including summary ROC curves, summary points, confidence regions, and prediction regions.

Statistical inference for the optimal approximating model

In the setting of high-dimensional linear models with Gaussian noise, we investigate the possibility of confidence statements connected to model selection. Although there exist numerous procedures for adaptive (point) estimation, the construction of adaptive confidence regions is severely limited (cf. Li in Ann Stat 17:1001–1008, 1989). The present paper sheds new light on this gap. We develop exact and adaptive confidence regions for the best approximating model in terms of risk. One of our constructions is based on a multiscale procedure and a particular coupling argument. Utilizing exponential inequalities for noncentral χ2-distributions, we show that the risk and quadratic loss of all models within our confidence region are uniformly bounded by the minimal risk times a factor close to one.

Can we constrain the interior structure of rocky exoplanets from mass and radius measurements?

Aims. We present an inversion method based on Bayesian analysis to constrain the interior structure of terrestrial exoplanets, in the form of chemical composition of the mantle and core size. Specifically, we identify what parts of the interior structure of terrestrial exoplanets can be determined from observations of mass, radius, and stellar elemental abundances. Methods. We perform a full probabilistic inverse analysis to formally account for observational and model uncertainties and obtain confidence regions of interior structure models. This enables us to characterize how model variability depends on data and associated uncertainties. Results. We test our method on terrestrial solar system planets and find that our model predictions are consistent with independent estimates. Furthermore, we apply our method to synthetic exoplanets up to 10 Earth masses and up to 1.7 Earth radii, and to exoplanet Kepler-36b. Importantly, the inversion strategy proposed here provides a framework for understanding the level of precision required to characterize the interior of exoplanets. Conclusions. Our main conclusions are (1) observations of mass and radius are sufficient to constrain core size; (2) stellar elemental abundances (Fe, Si, Mg) are principal constraints to reduce degeneracy in interior structure models and to constrain mantle composition; (3) the inherent degeneracy in determining interior structure from mass and radius observations does not only depend on measurement accuracies, but also on the actual size and density of the exoplanet. We argue that precise observations of stellar elemental abundances are central in order to place constraints on planetary bulk composition and to reduce model degeneracy. We provide a general methodology of analyzing interior structures of exoplanets that may help to understand how interior models are distributed among star systems. The methodology we propose is sufficiently general to allow its future extension to more complex internal structures including hydrogen- and water-rich exoplanets.

Oral leukoplakia in China: a review

BACKGROUND: Most prevalence studies on oral leukoplakia (OL) in China have been published in the Chinese language. The present review on the literature in Chinese aimed at making the data available to colleagues who are not familiar with the Chinese language. METHODS: The overall rate and 95% confidence interval of OL were calculated using Excel 2003. RESULTS: Overall prevalence of OL was 9.18% (95%CI = 9.06-9.30%). Gender ratio of prevalence was 8.03:1 (males/females). Prevalence was high in age groups over 40 years with the highest in the group aged 60-69 years (21.04%, 95%CI = 19.95-22.13%). The buccal mucosa was most commonly affected (47.08%, 95%CI = 46.52-47.64%), followed by lip (39.09%), palate (9.85%), gingiva (1.80%), and tongue (1.46%). The prevalence in smokers was 23.43% and in non-smokers 1.93%. Among three variants of smoking, the traditional Hanyan pipe smoking carried the highest risk for the development of OL followed by cigarette and Shuiyan water pipe smoking. The rate of alcohol drinkers with OL was 54.50% and 22.21% in individuals without OL. No case of oral cancer was found in six surveys. CONCLUSIONS: The present data on the prevalence of OL in China are comparable to those in other parts of the world. Some traditional smoking habits, however, are particular to certain regions of China.

Ventilation-perfusion ratio in perflubron during partial liquid ventilation

BACKGROUND: Functional magnetic resonance imaging (fMRI) of fluorine-19 allows for the mapping of oxygen partial pressure within perfluorocarbons in the alveolar space (Pao(2)). Theoretically, fMRI-detected Pao(2) can be combined with the Fick principle approach, i.e., a mass balance of oxygen uptake by ventilation and delivery by perfusion, to quantify the ventilation-perfusion ratio (Va/Q) of a lung region: The mixed venous blood and the inspiratory oxygen fraction, which are equal for all lung regions, are measured. In addition, the local expiratory oxygen fraction and the end capillary oxygen content, both of which may differ between the lung regions, are calculated using the fMRI-detected Pao(2). We investigated this approach by numerical simulations and applied it to quantify local Va/Q in the perfluorocarbons during partial liquid ventilation. METHODS: Numerical simulations were performed to analyze the sensitivity of the Va/Q calculation and to compare this approach with another one proposed by Rizi et al. in 2004 (Magn Reson Med 2004;52:65-72). Experimentally, the method was used during partial liquid ventilation in 7 anesthetized pigs. The Pao(2) distribution in intraalveolar perflubron was measured by fluorine-19 MRI. Respiratory gas fractions together with arterial and mixed venous blood samples were taken to quantify oxygen partial pressure and content. Using the Fick principle, the local Va/Q was estimated. The impact of gravity (nondependent versus dependent) of perflubron dose (10 vs 20 mL/kg body weight) and of inspired oxygen fraction (Fio(2)) (0.4-1.0) on Va/Q was examined. RESULTS: In numerical simulations, the Fick principle proved to be appropriate over the Va/Q range from 0.02 to 2.5. Va/Q values were in acceptable agreement with the method published by Rizi et al. In the experimental setting, low mean Va/Q values were found in perflubron (confidence interval [CI] 0.08-0.29 with 20 mL/kg perflubron). At this dose, Va/Q in the nondependent lung was higher (CI 0.18-0.39) than in the dependent lung regions (CI 0.06-0.16; P = 0.006; Student t test). Differences depending on Fio(2) or perflubron dose were, however, small. CONCLUSION: The results show that derivation of Va/Q from local Po(2) measurements using fMRI in perflubron is feasible. The low detected Va/Q suggests that oxygen transport into the perflubron-filled alveolar space is significantly restrained.

Antibiotic use in adult outpatients in Switzerland in relation to regions, seasonality and point of care tests

The use of antibiotics is highest in primary care and directly associated with antibiotic resistance in the community. We assessed regional variations in antibiotic use in primary care in Switzerland and explored prescription patterns in relation to the use of point of care tests. Defined daily doses of antibiotics per 1000 inhabitants (DDD(1000pd) ) were calculated for the year 2007 from reimbursement data of the largest Swiss health insurer, based on the anatomic therapeutic chemical classification and the DDD methodology recommended by WHO. We present ecological associations by use of descriptive and regression analysis. We analysed data from 1 067 934 adults, representing 17.1% of the Swiss population. The rate of outpatient antibiotic prescriptions in the entire population was 8.5 DDD(1000pd) , and varied between 7.28 and 11.33 DDD(1000pd) for northwest Switzerland and the Lake Geneva region. DDD(1000pd) for the three most prescribed antibiotics were 2.90 for amoxicillin and amoxicillin-clavulanate, 1.77 for fluoroquinolones, and 1.34 for macrolides. Regions with higher DDD(1000pd) showed higher seasonal variability in antibiotic use and lower use of all point of care tests. In regression analysis for each class of antibiotics, the use of any point of care test was consistently associated with fewer antibiotic prescriptions. Prescription rates of primary care physicians showed variations between Swiss regions and were lower in northwest Switzerland and in physicians using point of care tests. Ecological studies are prone to bias and whether point of care tests reduce antibiotic use has to be investigated in pragmatic primary care trials.

Appropriateness of reporting statistical results in orthodontics: the dominance of P values over confidence intervals

The purpose of this study was to search the orthodontic literature and determine the frequency of reporting of confidence intervals (CIs) in orthodontic journals with an impact factor. The six latest issues of the American Journal of Orthodontics and Dentofacial Orthopedics, the European Journal of Orthodontics, and the Angle Orthodontist were hand searched and the reporting of CIs, P values, and implementation of univariate or multivariate statistical analyses were recorded. Additionally, studies were classified according to the type/design as cross-sectional, case-control, cohort, and clinical trials, and according to the subject of the study as growth/genetics, behaviour/psychology, diagnosis/treatment, and biomaterials/biomechanics. The data were analyzed using descriptive statistics followed by univariate examination of statistical associations, logistic regression, and multivariate modelling. CI reporting was very limited and was recorded in only 6 per cent of the included published studies. CI reporting was independent of journal, study area, and design. Studies that used multivariate statistical analyses had a higher probability of reporting CIs compared with those using univariate statistical analyses. Misunderstanding of the use of P values and CIs may have important implications in implementation of research findings in clinical practice.