Optimal dose-finding for efficacy-safety models.

Dose-finding is an important part of the clinical development of a new drug. The purpose of dose-finding studies is to determine a suitable dose for future development based on both efficacy and safety. Optimal experimental designs have already been used to determine the design of this kind of studies, however, often that design is focused on efficacy only. We consider an efficacy-safety model, which is a simplified version of the bivariate Emax model. We use here the clinical utility index concept, which provides the desirable balance between efficacy and safety. By maximizing the utility of the patients, we get the estimated dose. This desire leads us to locally c -optimal designs. An algebraic solution for c -optimal designs is determined for arbitrary c vectors using a multivariate version of Elfving's method. The solution shows that the expected therapeutic index of the drug is a key quantity determining both the number of doses, the doses itself, and their weights in the optimal design. A sequential design is proposed to solve the complication of parameter dependency, and it is illustrated in a simulation study.

Individual differences in behaviour explain variation in survival: a meta-analysis.

Research focusing on among-individual differences in behaviour ('animal personality') has been blooming for over a decade. Central theories explaining the maintenance of such behavioural variation posits that individuals expressing greater "risky" behaviours should suffer higher mortality. Here, for the first time, we synthesize the existing empirical evidence for this key prediction. Our results did not support this prediction as there was no directional relationship between riskier behaviour and greater mortality; however there was a significant absolute relationship between behaviour and survival. In total, behaviour explained a significant, but small, portion (5.8%) of the variance in survival. We also found that risky (vs. "shy") behavioural types live significantly longer in the wild, but not in the laboratory. This suggests that individuals expressing risky behaviours might be of overall higher quality but the lack of predation pressure and resource restrictions mask this effect in laboratory environments. Our work demonstrates that individual differences in behaviour explain important differences in survival but not in the direction predicted by theory. Importantly, this suggests that models predicting behaviour to be a mediator of reproduction-survival trade-offs may need revision and/or empiricists may need to reconsider their proxies of risky behaviours when testing such theory.

Data-based bivariate uncertainty assessment of extreme rainfall-runoff using copulas: comparison between annual maximum series (AMS) and peaks over threshold (POT).

Bivariate frequency analysis of extreme rainfall and runoff is crucial for water resource planning and management in a river basin. This study is aimed at accounting for uncertainties in bivariate analysis of extreme rainfall-runoff frequency in the Taleghan watershed, one of the major watersheds in northern Iran, using copulas. Two types of paired rainfall and runoff data, including annual maximum series (AMS) and peaks over threshold (POT) are adopted to investigate the uncertainties that arose due to the input data. The Cramer von-Mises goodness-of-fit test and Akaike information criteria (AIC) reveal that the Student's t copula is the best-fit copula for PAMS-QAMS with Gaussian-Pearson III (P3) margins, while the Plackett copula is the best-fit copula for PPOT-QPOT with generalized Pareto (GPAR-GPAR) margins. A nonparametric bootstrapping method for sampling from p-level curves is established to investigate the effects of univariate and bivariate models selection and uncertainties induced by input data. The results indicated that the sampling uncertainty reduces POT data compared to AMS data due to the increased sample size. However, the parameterization uncertainty of the POT data increases because of the weaker dependence structure between rainfall and runoff for the POT data. The results also reveal that the larger sampling uncertainties are associated with higher p-level curves for both AMS and POT data which are induced by lower data density in the upper tail. For the study area, the input-data uncertainty is most significant in bivariate rainfall-runoff frequency analysis and quantile estimation, while the uncertainty induced by probabilistic model selection is least significant.

Heritability of hippocampal subfield volumes using a twin and non-twin siblings design.

The hippocampus is composed of distinct subfields linked to diverse functions and disorders. The subfields can be mapped using high-resolution magnetic resonance images, and their volumes can potentially be used as quantitative phenotypes for genetic investigation of hippocampal function. We estimated the heritability of hippocampus subfield volumes of 465 subjects from the Human Connectome Project (twins and non-twin siblings) using two methods. The first used a univariate model to estimate heritability with and without adjustment for total brain volume (TBV) and ipsilateral hippocampal volume to determine if heritability was uniquely attributable to subfield volume rather than confounds that attributed to global volumes. We observed the right: subiculum, cornu ammonis 2/3, and cornu ammonis 4/dentate gyrus subfields had the highest significant heritability estimates after adjusting for ipsilateral hippocampal volume. In the second analysis, we used a bivariate model to investigate the shared heritability and genetic correlation of the subfield volumes with TBV and ipsilateral hippocampal volume. Genetic correlation demonstrates shared genetic architecture between phenotypes and shared heritability is what proportion of the genetic architecture of one trait is shared by the other. Highest genetic correlations were between subfield volumes and ipsilateral hippocampal volume than with TBV. The pattern was opposite for shared heritability suggesting that subfields share greater proportion of the genetic architecture with TBV than with ipsilateral hippocampal volume. The relationship between the genetic architecture of TBV, hippocampal volume, and of individual subfields should be accounted for when using hippocampal subfield volumes as quantitative phenotypes for imaging genetics studies. Hum Brain Mapp 38:4337-4352, 2017. © 2017 Wiley Periodicals, Inc.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows.

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.

Accuracy of visual inspection with acetic acid and with Lugol's iodine for cervical cancer screening: Meta-analysis.

The aim of this review was to provide an updated summary estimation of the accuracy of visual inspection with acetic acid (VIA) and with Lugol's iodine (VILI) in detecting cervical cancer and precancer. Studies on VIA/VILI accuracy were eligible in which VIA/VILI was performed on asymptomatic women who all underwent confirmatory testing of histology, combination of colposcopy and histology, or combination of multiple screening tests, colposcopy and histology, to detect cervical intraepithelial neoplasia grade 2 or worse (CIN2+ or CIN3+). A bivariate model was fitted to estimate the accuracy of VIA/VILI and provide estimates of heterogeneity. Subgroup analysis was used to investigate the source of heterogeneity. A total of 29 studies on VIA and 19 studies on VILI were included finally in the meta-analysis. The summary sensitivity and specificity of VIA for CIN2+ were 73.2% (95%CI: 66.5-80.0%) and 86.7% (95%CI: 82.9-90.4%), respectively, and those for VILI were 88.1% (95%CI: 81.5-94.7%) and 85.9% (95%CI: 81.7-90.0%), respectively. VIA and VILI were both more sensitive in detecting more severe outcome, although there was a slight loss in specificity. Apparent heterogeneity existed in sensitivity and specificity for both VIA and VILI. High sensitivity of both VIA and VILI for CIN2+ was found when a combination of colposcopy and histology was used as disease confirmation. VIA, VILI, even a combination of them in parallel, could be good options for cervical screening in low-resource settings. Significant differences in sensitivity between different gold standards might provide a proxy for optimization of ongoing cervical cancer screening programs.

Using multiparametric Magnetic Resonance Imaging and Prostate Specific Membrane Antigen Positron Emission Tomography to detect and delineate the gross tumour volume of intraprostatic lesions - A systematic review and meta-analysis.

BACKGROUND AND PURPOSE: Radiation therapy is used frequently for patients with prostate cancer. Dose escalation to intraprostatic lesions (IPLs) has been shown to improve oncologic outcomes, without increasing toxicity. Both multiparametric MRI (mpMRI) and PSMA PET can be used to identify IPLs. MATERIALS AND METHODS: A systematic review was conducted to determine the ability of mpMRI, PSMA PET and their combination to detect IPLs prior to radical prostatectomy (RP) as correlated with the histology. Trials included patients that had mpMRI, PSMA PET, or both, prior to RP. The quality of the histopathological-radiological co-registration was assessed as high or low for each study. Recorded outcomes include sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). A meta-analysis was conducted using a bivariate model to determine the pooled sensitivity and specificity for each imaging modality. This systematic review was registered through PROSPERO (CRD42023389092). RESULTS: Altogether, 42 studies were included in the systematic review. Of these, 20 could be included in the meta-analysis. The pooled sensitivity (95 % CI), specificity (95 % CI) and AUROC for mpMRI (n = 13 studies) were 64.7 % (50.2 % - 76.9 %), 86.4 % (79.7 % - 91.1 %), and 0.852; the pooled outcomes for PSMA PET (n = 12) were 75.7 % (64.0 % - 84.5 %), 87.1 % (80.2 % - 91.9 %), and 0.889; for their combination (n = 5), the pooled outcomes were 70.3 % (64.1 % - 75.9 %), 81.9 % (71.9 % - 88.8 %), and 0.796. When reviewing studies with a high-quality histopathological-radiological co-registration, IPL delineation recommendations varied by study and the imaging modality used. CONCLUSION: All of mpMRI, PSMA PET or their combination were found to have very good diagnostic outcomes for detecting IPLs. Recommendations for delineating IPLs varied based on the imaging modalities used and between research groups. Consensus guidelines for IPL delineation would help with creating consistency for focal boost radiation treatments in future studies.

Diagnostic Accuracy of Cord Bilirubin to Predict the Need for Phototherapy in Healthy Neonates >35-Week Gestational Age: A Systematic Review and Meta-Analysis.

Objective: Early discharge puts neonates at risk of delayed detection of jaundice and resulting neurological injury. In these neonates, we can use cord bilirubin to make predictions. In this meta-analysis, we assessed the diagnostic accuracy of cord bilirubin in predicting the need for phototherapy (AAP-2004 or NICE-2010 charts). Methods: We searched the databases of PubMed, Embase, Cochrane Library, Google Scholar, and Index Medicus for Southeast Asian Region. We included all observational studies that assessed the diagnostic accuracy of cord bilirubin. A bivariate model was used to pool the data in prespecified range of cord bilirubin levels (<1.5 mg/dl, 1.5-2.0 mg/dl, 2.0-2.5 mg/dl, 2.5-3.0 mg/dl, and >3.0 mg/dl). Data were pooled separately for studies including all neonates (no risk stratification), high-risk neonates (Rh and/or ABO incompatibility only), and low-risk neonates (excluded Rh and ABO incompatibility). Results: Of the 1990 unique records, we studied 153 full texts and included 54 studies in the meta-analysis. For all the three groups of studies, the highest diagnostic odds ratio was noted for a cord bilirubin cut-off of 2.5-3.0 mg/dl (all neonates: 22.5, 95% CI: 21.1, 22.9; high-risk neonates: 75.5, 95% CI: 63, 85.7; low-risk neonates: 91.9; 95% CI: 64, 134.14). Using the same cut-off, the studies including all neonates without risk stratification had a pooled sensitivity of 0.31 (95% CI: 0.18, 0.47) and a pooled specificity of 0.98 (0.96, 0.99) in predicting the need for phototherapy. In studies on high-risk neonates, the pooled sensitivity was 0.8 (0.39, 0.96) and pooled specificity was 0.95 (0.78, 0.99). In studies on low-risk neonates, the pooled sensitivity was 0.74 (0.39, 0.93) and pooled specificity of 0.97 (0.91, 0.99). We noted significant heterogeneity and a high risk of bias in the index test's conduct. Conclusion: A cord bilirubin cut-off of 2.5-3 mg/dl has good diagnostic accuracy in predicting the need for phototherapy in neonates. Registration number: CRD42020196216.

On estimating a constrained bivariate random effects model for meta-analysis of test accuracy studies.

Tailored meta-analysis uses setting-specific knowledge for the test positive rate and disease prevalence to constrain the possible values for a test's sensitivity and specificity. The constrained region is used to select those studies relevant to the setting for meta-analysis using an unconstrained bivariate random effects model (BRM). However, sometimes there may be no studies to aggregate, or the summary estimate may lie outside the plausible or "applicable" region. Potentially these shortcomings may be overcome by incorporating the constraints in the BRM to produce a constrained model. Using a penalised likelihood approach we developed an optimisation algorithm based on co-ordinate ascent and Newton-Raphson iteration to fit a constrained bivariate random effects model (CBRM) for meta-analysis. Using numerical examples based on simulation studies and real datasets we compared its performance with the BRM in terms of bias, mean squared error and coverage probability. We also determined the 'closeness' of the estimates to their true values using the Euclidian and Mahalanobis distances. The CBRM produced estimates which in the majority of cases had lower absolute mean bias and greater coverage probability than the BRM. The estimated sensitivities and specificity for the CBRM were, in general, closer to the true values than the BRM. For the two real datasets, the CBRM produced estimates which were in the applicable region in contrast to the BRM. When combining setting-specific data with test accuracy meta-analysis, a constrained model is more likely to yield a plausible estimate for the sensitivity and specificity in the practice setting than an unconstrained model.

Theoretical Model and Actual Characteristics of Air Pollution Affecting Health Cost: A Review.

BACKGROUND: The impact of environmental pollution (such as air pollution) on health costs has received a great deal of global attention in the last 20 years. METHODS: This review aims to summarize the theoretical analysis model of air pollution affecting health costs, and further explore the actual characteristics of the impact of air pollution on health costs. The following main databases were taken into account: Web of Science Core Collection, Medline, SCOPUS, PubMed, and CNKI (China). As of 30 March 2021, we retrieved a total of 445 papers and ended up with 52 articles. RESULTS: This review mainly expounds clarification of the concept of air pollution and health costs, the theoretical model and the actual characteristics of air pollution affecting health costs. In addition, it also discusses other related factors affecting health costs. CONCLUSION: Our conclusion is that, while academic research on the relationship between air pollution and health costs has made some progress, there are still some shortcomings, such as insufficient consideration of individual avoidance behavior and rural-urban and international mobility. Therefore, the simple use of the original data obtained in the statistical yearbook of the health cost caused by air pollution is also the reason for the errors in the empirical results. In addition, the choice of proxy variables of environmental pollution by scholars is relatively simple, mainly focusing on air pollutants, while the impact of water quality or soil pollution safety on health costs is becoming increasingly prominent, and will become the focus of future research.

Accuracy of Serum Biomarker Panel (GastroPanel®) in the Diagnosis of Atrophic Gastritis of the Corpus. Systematic Review and Meta-analysis.

BACKGROUND/AIM: The serological biomarker panel (GastroPanel®)(GP) developed by Biohit Oyj (Helsinki, Finland) has gained increasing global acceptance in the diagnosis of atrophic gastritis (AG). This is a systematic review and meta-analysis of the studies on diagnostic accuracy of GP (GPA). MATERIALS AND METHODS: Core electronic databases were searched until the end of December 2021, following the principles of the PRISMA-P and using the QUADAS-2 quality assessment tool. STATA software with relevant packages (metandi, midas, mylabels) was used for meta-analysis, with AG of the corpus (AGC) as the endpoint. Summary estimates of Se and Sp, LR+ and LR- were calculated using random effect bivariate model (Forest plots), and summary receiver operating characteristic (SROC) curves by hierarchical SROC (HSROC) model. RESULTS: Altogether, 49 studies were found eligible, comprising 22,597 patients examined by the GP test. Significant heterogeneity across the studies was confirmed in Forest plots, HSROC and bivariate boxplot. The pooled Se of GP in diagnosis of AGC was 0.70 (95%CI=0.64-0.76) and pooled Sp was 0.93 (95%CI=0.90-0.95), with AUC=0.900 (95%CI=0.170-1.000) in HSROC. In Fagan's nomogram, positive GP test predicts AGC at population level with the likelihood of 72%. Meta-regression and subgroup meta-analysis disclosed publication year (<2008>) as the only significant source of heterogeneity, geographic origin of the study being of borderline significance. CONCLUSION: These meta-analytical results confirm the accuracy of GastroPanel® test in the diagnosis of AGC, advocating its applicability i) in screening for gastric cancer risk conditions (AG, Helicobacter pylori), as well as ii) in non-invasive diagnosis of dyspeptic patients, and iii) in follow-up of AG-patients.

Application of Bivariate Extreme Value models to describe the joint behavior of temporal and speed related surrogate measures of safety.

Limitations of historical crash data and the advantages of surrogate measures of safety have already been stressed by various authors. To describe nearness-to-collision, mostly time-based indicators are applied, and there is a consensus among researchers that speed-related indicators are needed to account for the severity dimension. There have been attempts to fit bivariate Extreme Value models to predict the number of crashes, however modeling crash frequency together with severity has received much less attention. The aim of this paper is to apply Extreme Value models to various pairs of temporal and speed-related indicators in order to investigate the dependence structure between them as well as to construct probability based risk levels and examine them in relation to severity levels. Bivariate threshold excess models were fitted to a dataset of left-turning and straight moving vehicle interactions recorded in a signalized intersection. The dependence structure between variable pairs were thoroughly investigated; it was concluded that temporal and speed related indicators were found independent, which means that road users getting close to each other in time does not necessarily come with high speeds. Therefore these indicators should be combined in order to properly predict severity; a temporal indicator on its own is not enough to make inferences about the severity of events. Using the calculated joint probability of events risk levels were constructed illustrating the events of equal probability.

The reference method influence on the sensitivity of the Clostridium difficile enzyme immunoassays: A meta analysis.

The use of enzyme immunoassays to screen for toxins A and B produced by Clostridium difficile is a common procedure in algorithms designed for its detection. Moreover, the absence of a unique test capable of providing reliable results at low cost motivates a great discussion about which algorithm is the best. Thus, several studies have evaluated the performance of these enzyme immunoassays. However, all fail to provide sufficient explanations for the different behaviours observed in different studies that evaluate the same index test against a common reference method. Our main goal was to find out which factors affect the sensitivity of these assays, since the specificity is very close to 1. In this research, we verified that sensitivity increases with the prevalence rate and with the proportion of reported cases of onset diarrhea. Therefore, its use is advisable for high prevalence rates (e.g. in an epidemic setting). As far as reference methods are concerned, nucleic acid amplification tests can be used as a reference method, with a performance similar to the well-accepted toxigenic culture. The method chosen for toxigenicity screening in a toxigenic culture also seems to affect the evaluation performance of tests and should be better studied in the future.

Maximum likelihood estimation based on Newton-Raphson iteration for the bivariate random effects model in test accuracy meta-analysis.

A bivariate generalised linear mixed model is often used for meta-analysis of test accuracy studies. The model is complex and requires five parameters to be estimated. As there is no closed form for the likelihood function for the model, maximum likelihood estimates for the parameters have to be obtained numerically. Although generic functions have emerged which may estimate the parameters in these models, they remain opaque to many. From first principles we demonstrate how the maximum likelihood estimates for the parameters may be obtained using two methods based on Newton-Raphson iteration. The first uses the profile likelihood and the second uses the Observed Fisher Information. As convergence may depend on the proximity of the initial estimates to the global maximum, each algorithm includes a method for obtaining robust initial estimates. A simulation study was used to evaluate the algorithms and compare their performance with the generic generalised linear mixed model function glmer from the lme4 package in R before applying them to two meta-analyses from the literature. In general, the two algorithms had higher convergence rates and coverage probabilities than glmer. Based on its performance characteristics the method of profiling is recommended for fitting the bivariate generalised linear mixed model for meta-analysis.

The relation between working conditions, aberrant driving behaviour and crash propensity among taxi drivers in China.

Although the taxi industry is playing an important role in Chinese everyday life, little attention has been posed towards occupational health issues concerning the taxi drivers' working conditions, driving behaviour and road safety. A cross-sectional survey was administered to 1021 taxi drivers from 21 companies in four Chinese cities and collected information about (i) sociodemographic characteristics, (ii) working conditions, (iii) frequency of daily aberrant driving behaviour, and (iv) involvement in property-damage-only (PDO) and personal injury (PI) crashes over the past two years. A hybrid bivariate model of crash involvement was specified: (i) the hybrid part concerned a latent variable model capturing unobserved traits of the taxi drivers; (ii) the bivariate part modelled jointly both types of crashes while capturing unobserved correlation between error terms. The survey answers paint a gloomy picture in terms of workload, as taxi drivers reported averages of 9.4 working hours per day and 6.7 working days per week that amount on average to about 63.0 working hours per week. Moreover, the estimates of the hybrid bivariate model reveal that increasing levels of fatigue, reckless behaviour and aggressive behaviour are positively related to a higher propensity of crash involvement. Lastly, the heavy workload is also positively correlated with the higher propensity of crashing, not only directly as a predictor of crash involvement, but also indirectly as a covariate of fatigue and aberrant driving behaviour. The findings from this study provide insights into potential strategies for preventive education and taxi industry management to improve the working conditions and hence reduce fatigue and road risk for the taxi drivers.

The diagnostic accuracy of magnetic resonance angiography for blunt vertebral artery injury detection in trauma patients: A systematic review and meta-analysis.

The role of magnetic resonance angiography (MRA) in the evaluation of patients with blunt vertebral artery has not been fully established. Our aim is to define the diagnostic accuracy of MRA in comparison to digital subtraction angiography (DSA) for the detection of blunt vertebral artery injury in trauma patients. A computer-assisted literature search of the PubMed, Scopus, Highwire, Web of Science, and LILACS was conducted, in order to identify studies reporting on the sensitivity and specificity of MRA in comparison to DSA for the detection of blunt vertebral artery injury in trauma patients. The Database search retrieved 91 studies. Five studies fulfilled our eligibility criteria. Two authors assessed the risk of bias and applicability concerns using QUADAS-2. Two-by-two contingency tables were constructed on a per-vessel level. Heterogeneity was tested by the statistical significance of Cochran's Q, and was quantified by the Higgins's I2 metric. The pooled estimates of sensitivity and specificity for blunt vertebral artery injury detection with MRA in comparison to DSA were calculated based on the bivariate model. The meta-analysis was supplemented by subgroup and sensitivity analysis, as well as analysis for publication bias. There was significant clinical heterogeneity in the targeted population, inclusion criteria, and MRA related parameters. The reporting bias and applicability concerns were moderate and low, respectively. In the overall analysis, the sensitivity ranged from 25% to 85%, while the specificity varied from 65% to 99%, across studies. According to the bivariate model, the pooled sensitivity and specificity of MRA in the evaluation of patients with blunt vertebral artery was as high as 55% (95% CI 32.1%-76.7%), and 91% (95% CI 66.3%-98.2%), respectively. Subgroup analysis in terms of MRA sequence sensitivity of phase, the contrasted MRA (75% [95% CI 43%-92%]) seemed to be superior to the TOF MRA (46% [95%CI 20%-74%]). The addition of contrast enhancement did not seem to improve the diagnostic yield of MRA. The Egger's test did not identify any significant publication bias (p=0.2). An important limitation of the current meta-analysis is the small number of eligible studies, as well as the lack of studies on newer, high-field MR scanners. We concluded that MRA has a moderate diagnostic accuracy in the diagnosis of blunt vertebral artery injuries. Further studies on high-field magnetic resonance scanners are recommended.

Performance of methods for meta-analysis of diagnostic test accuracy with few studies or sparse data.

Hierarchical models such as the bivariate and hierarchical summary receiver operating characteristic (HSROC) models are recommended for meta-analysis of test accuracy studies. These models are challenging to fit when there are few studies and/or sparse data (for example zero cells in contingency tables due to studies reporting 100% sensitivity or specificity); the models may not converge, or give unreliable parameter estimates. Using simulation, we investigated the performance of seven hierarchical models incorporating increasing simplifications in scenarios designed to replicate realistic situations for meta-analysis of test accuracy studies. Performance of the models was assessed in terms of estimability (percentage of meta-analyses that successfully converged and percentage where the between study correlation was estimable), bias, mean square error and coverage of the 95% confidence intervals. Our results indicate that simpler hierarchical models are valid in situations with few studies or sparse data. For synthesis of sensitivity and specificity, univariate random effects logistic regression models are appropriate when a bivariate model cannot be fitted. Alternatively, an HSROC model that assumes a symmetric SROC curve (by excluding the shape parameter) can be used if the HSROC model is the chosen meta-analytic approach. In the absence of heterogeneity, fixed effect equivalent of the models can be applied.

Development and heritability of subcortical brain volumes at ages 9 and 12.

Subcortical brain structures are involved in a variety of cognitive and emotional functions and follow different trajectories of increase and decrease in volume from childhood to adulthood. The heritability of development of subcortical brain volumes during adolescence has not been studied comprehensively. In a longitudinal twin study, we estimated to what extent subcortical brain volumes are influenced by genetic factors at ages 9 and 12. In addition, we assessed whether new genes are expressed at age 12 and whether there is evidence for genotype by sex interaction. Brain scans were acquired for 112 and 89 twin pairs at 9 and 12 years of age. In both boys and girls, there was an increase in volumes of the thalamus, hippocampus, amygdala and pallidum, and a decrease in volumes of the caudate and nucleus accumbens. The putamen showed a decrease in boys bilaterally and an increase in girls in the left hemisphere. Heritability was high (>50%) for all structures - except for the left nucleus accumbens - with heritabilities ranging from 0.50 to 0.91 at age 9, and from 0.59 to 0.88 at age 12. There were no significant new genetic effects coming into play at age 12, and there was no evidence for genotype by sex interactions. These findings suggest that despite their sensitivity to environmental effects, the heritability of subcortical brain structures is high from childhood on, resembling estimates found in adult samples.

A Bivariate Mixed-Effects Location-Scale Model with application to Ecological Momentary Assessment (EMA) data.

A bivariate mixed-effects location-scale model is proposed for estimation of means, variances, and covariances of two continuous outcomes measured concurrently in time and repeatedly over subjects. Modeling the two outcomes jointly allows examination of BS and WS association between the outcomes and whether the associations are related to covariates. The variance-covariance matrices of the BS and WS effects are modeled in terms of covariates, explaining BS and WS heterogeneity. The proposed model relaxes assumptions on the homogeneity of the within-subject (WS) and between-subject (BS) variances. Furthermore, the WS variance models are extended by including random scale effects. Data from a natural history study on adolescent smoking are used for illustration. 461 students, from 9th and 10th grades, reported on their mood at random prompts during seven consecutive days. This resulted in 14,105 prompts with an average of 30 responses per student. The two outcomes considered were a subject's positive affect and a measure of how tired and bored they were feeling. Results showed that the WS association of the outcomes was negative and significantly associated with several covariates. The BS and WS variances were heterogeneous for both outcomes, and the variance of the random scale effects were significantly different from zero.

Toxicity of four spill-treating agents on bacterial growth and sea urchin embryogenesis.

The toxicity of spill-treating agents (STAs) is a topic that needs to be assessed prior to their potential application in environmental disasters. The aim of the present work was to study the effects of four commercial STAs (CytoSol, Finasol OSR 51, Agma OSD 569 and OD4000) on the growth of marine (Phaeobacter sp., Pseudomonas sp.) and terrestrial (Leuconostoc mesenteroides) bacteria, and sea urchin (Paracentrotus lividus) embryolarval development. In general, STA did not inhibit significantly the biomass production of the tested marine bacteria. Finasol OSR 51 and OD4000 clearly inhibited the growth of L. mesenteroides and an accurate description of the kinetics was provided by a proposed bivariate equation. For this species, a global parameter (EC50,τ) was defined to summarize the set of growth kinetics. Using this parameter Finasol OSR 51 was found to be less toxic (754µL L(-1)) than OD4000 (129µL L(-1)). For the sea urchin embryo assay, the ranking of toxicity as EC50 (µL L(-1)) was Agma OSD 569 (34.0)