Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Computational problems in perfect phylogeny haplotyping: Typing without calling the allele

A haplotype is an m-long binary vector. The XOR-genotype of two haplotypes is the m-vector of their coordinate-wise XOR. We study the following problem: Given a set of XOR-genotypes, reconstruct their haplotypes so that the set of resulting haplotypes can be mapped onto a perfect phylogeny (PP) tree. The question is motivated by studying population evolution in human genetics and is a variant of the PP haplotyping problem that has received intensive attention recently. Unlike the latter problem, in which the input is '' full '' genotypes, here, we assume less informative input and so may be more economical to obtain experimentally. Building on ideas of Gusfield, we show how to solve the problem in polynomial time by a reduction to the graph realization problem. The actual haplotypes are not uniquely determined by the tree they map onto and the tree itself may or may not be unique. We show that tree uniqueness implies uniquely determined haplotypes, up to inherent degrees of freedom, and give a sufficient condition for the uniqueness. To actually determine the haplotypes given the tree, additional information is necessary. We show that two or three full genotypes suffice to reconstruct all the haplotypes and present a linear algorithm for identifying those genotypes.

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.

At-risk drinking and drug use among patients seeking care in an emergency department.

OBJECTIVE: This study reports the frequency of alcohol use and associated tobacco and drug use among emergency department (ED) patients, in order to increase physician awareness and treatment of women and men seeking care in ED settings. METHOD: All adults seen in the ED at the University Hospital in Lausanne, Switzerland, between 11 AM and 11 PM were screened by direct interview for at-risk drinking, tobacco use, drug use, and depression during an 18-month period. RESULTS: A total of 8,599 patients (4,006 women and 4,593 men) participated in the screening procedure and provided full data on the variables in our analysis. The mean age was 51.9 years for women and 45.0 years for men; 57.5% (n = 2,304) of women and 58.5% (n = 2,688) of men were being treated for trauma. Based on guidelines of the National Institute on Alcohol Abuse and Alcoholism, 13.1% (n = 523) of the women were at-risk drinkers, 57.3% (n = 2,301) were low-risk drinkers, and 29.6% (n = 1,182) were abstinent. Among men, 32.8% (n = 1,507) met criteria for at-risk drinking, 51.8% (n = 2,380) met criteria for low-risk drinking, and 15.4% (n = 706) were abstinent. Younger individuals (ages 18-30) had significantly higher rates of episodic heavy drinking episodes, whereas at-risk older patients were more likely to drink on a daily basis. A binary model found that women and men who drank at at-risk levels are more likely to use tobacco (odds ratio [OR] = 2.48, 95% confidence interval [CI]: 2.0-3.08) and illicit drugs (OR = 5.91, CI: 3.32- 10.54) compared with abstinent and low-risk drinkers. CONCLUSIONS: This study supports systematic alcohol screening of women and men seen in EDs and suggests that patterns of alcohol and drug use vary by age and gender.

GUS gene expression driven by a citrus promoter in transgenic tobacco and 'Valencia' sweet orange

The objective of this work was the transformation of tobacco and 'Valencia' sweet orange with the GUS gene driven by the citrus phenylalanine ammonia-lyase (PAL) gene promoter (CsPP). Transformation was accomplished by co-cultivation of tobacco and 'Valência' sweet orange explants with Agrobacterium tumefaciens containing the binary vector CsPP-GUS/2201. After plant transformation and regeneration, histochemical analyses using GUS staining revealed that CsPP promoter preferentially, but not exclusively, conferred gene expression in xylem tissues of tobacco. Weaker GUS staining was also detected throughout the petiole region in tobacco and citrus CsPP transgenic plants.

Multislice CT for assessing in-stent dimensions after left main coronary artery stenting: a comparison with three dimensional intravascular ultrasound

Objective: To evaluate the agreement between multislice CT (MSCT) and intravascular ultrasound (IVUS) to assess the in-stent lumen diameters and lumen areas of left main coronary artery (LMCA) stents. Design: Prospective, observational single centre study. Setting: A single tertiary referral centre. Patients: Consecutive patients with LMCA stenting excluding patients with atrial fibrillation and chronic renal failure. Interventions: MSCT and IVUS imaging at 912 months follow-up were performed for all patients. Main outcome measures: Agreement between MSCT and IVUS minimum luminal area (MLA) and minimum luminal diameter (MLD). A receiver operating characteristic (ROC) curve was plotted to find the MSCT cut-off point to diagnose binary restenosis equivalent to 6 mm2 by IVUS. Results: 52 patients were analysed. PassingBablok regression analysis obtained a β coefficient of 0.786 (0.586 to 1.071) for MLA and 1.250 (0.936 to 1.667) for MLD, ruling out proportional bias. The α coefficient was −3.588 (−8.686 to −0.178) for MLA and −1.713 (−3.583 to −0.257) for MLD, indicating an underestimation trend of MSCT. The ROC curve identified an MLA ≤4.7 mm2 as the best threshold to assess in-stent restenosis by MSCT. Conclusions: Agreement between MSCT and IVUS to assess in-stent MLA and MLD for LMCA stenting is good. An MLA of 4.7 mm2 by MSCT is the best threshold to assess binary restenosis. MSCT imaging can be considered in selected patients to assess LMCA in-stent restenosis

Statistical mechanics of multi-edge networks

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.

Do stacked species distribution models reflect altitudinal diversity patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.

Cluster glasses of ultrasoft particles

We present molecular dynamics (MD) simulations results for dense fluids of ultrasoft, fully penetrable particles. These are a binary mixture and a polydisperse system of particles interacting via the generalized exponential model, which is known to yield cluster crystal phases for the corresponding monodisperse systems. Because of the dispersity in the particle size, the systems investigated in this work do not crystallize and form disordered cluster phases. The clusteringtransition appears as a smooth crossover to a regime in which particles are mostly located in clusters, isolated particles being infrequent. The analysis of the internal cluster structure reveals microsegregation of the big and small particles, with a strong homo-coordination in the binary mixture. Upon further lowering the temperature below the clusteringtransition, the motion of the clusters" centers-of-mass slows down dramatically, giving way to a cluster glass transition. In the cluster glass, the diffusivities remain finite and display an activated temperature dependence, indicating that relaxation in the cluster glass occurs via particle hopping in a nearly arrested matrix of clusters. Finally we discuss the influence of the microscopic dynamics on the transport properties by comparing the MD results with Monte Carlo simulations.

Local description of quantum inseparability

We show how to decompose any density matrix of the simplest binary composite systems, whether separable or not, in terms of only product vectors. We determine for all cases the minimal number of product vectors needed for such a decomposition. Separable states correspond to mixing from one to four pure product states. Inseparable states can be described as pseudomixtures of four or five pure product states, and can be made separable by mixing them with one or two pure product states.

Análisis de sistemas bucoadhesivos

[spa]Objetivo: El objetivo de este estudio es el diseño de un parche bucoadhesivo para la administración transbucal de clorhidrato de doxepina utilizando diferentes polímeros así como la caracterización de dichos sistemas en cuanto al análisis calorimétrico y la capacidad de hinchamiento.Materiales y métodos: Se ha utilizado clorhidrato de doxepina y diferentes polímeros, carboximetilcelulosa sódica, hidroxipropilmetilcelulosa y chitosan. La calorimetría diferencial de barrido (DSC) se ha realizado en un dispositivo Mettler FP 80 equipado con un horno FP 85 y la capacidad de hinchamiento utilizando placas de agar.Resultados: Se obtienen termogramas de los parches y las mezclas físicas donde se observan transiciones endotérmicas entre 30 y 120º C y el pico endotérmico del principio activo en las mezclas físicas binarias. La entalpía de deshidratación es similar en los polímeros de carboximetilcelulosa sódica y chitosan (281 J/g) siendo menor en la película de hidroxipropilmetilcelulosa (251 J/g), al igual que el porcentaje de hidratación donde se demuestra que los parches elaborados con hidroxipropilmetilcelulosa presenta menor tendencia a captar agua (55,91 %) frente al 67,04 % y 67,30 % de la carboximetilcelulosa sódica y chitosan, respectivamente.Conclusión: Los resultados obtenidos muestran que existe compatibilidad entre los componentes de la formulación y los datos de entalpía se correlacionan con los datos obtenidos en el ensayo de hinchamiento.[eng]The aim of this study is to design a bucoadhesive patch for the transbuccal administration of doxepin hydrochloride using different polymers as well as the characterization of these systems for calorimetric analysis and the swelling capacity. Materials and methods: Doxepin hydrochloride was used as well as various polymers; carboxymethylcellulose sodium, hydroxypropylmethyl cellulose and chitosan. Differential scanning calorimetry (DSC) was carried out using a Mettler FP 80 device equipped with a FP 85 oven and the swelling capacity using agar plates. Results: Thermograms obtained patches and physical mixtures where there are endothermic transitions between 30 and 120º C and the endothermic peak of the active principle in binary physical mixtures. Dehydration enthalpy is similar in polymers of carboxymethylcellulose sodium and chitosan (281 J/g), the film having less hydroxypropylmethylcellulose (251 J/g), the percentage of moisture shows that the patches prepared with hydroxypropylmethylcellulose have less tendency to collect water (55.91 %) compared to 67.04 % and 67.30 % with sodium carboxymethylcellulose and chitosan, respectively. Conclusion: The results show that there is compatibility between the components of the formulation and the enthalpy data correlate

Mood and nonmood components of perceived stress and exacerbation of Crohn's disease.

BACKGROUND: Diverse psychological factors are involved in the pathophysiology of stress. In order to devise effective intervention strategies, it is important to elucidate which factors play the most important role in the association between psychological stress and exacerbation of Crohn's disease (CD). We hypothesized that the association between perceived stress and exacerbation of CD would remain after removal of mood and anxiety components, which are largely involved in stress perception. METHODS: In all, 468 adults with CD were recruited and followed in different hospitals and private practices of Switzerland for 18 months. At inclusion, patients completed the Perceived Stress Questionnaire and anxiety and depression were assessed using the Hospital Anxiety and Depression Scale. During the follow-up, gastroenterologists assessed whether patients presented with a CD exacerbation. By means of binary logistic regression analysis, we estimated the factor by which one standard deviation of perceived stress would increase the odds of exacerbation of CD with and without controlling for anxiety and depression. RESULTS: The odds of exacerbation of CD increased by 1.85 times (95% confidence interval 1.43-2.40, P < 0.001) for 1 standard deviation of perceived stress. After removing the anxiety and depression components, the residuals of perceived stress were no longer associated with exacerbation of CD. CONCLUSIONS: The association between perceived stress and exacerbation of CD was fully attributable to the mood components, specifically anxiety and depression. Future interventional studies should evaluate the treatment of anxiety and depression as a strategy for potential prevention of CD exacerbations.

Bayesian genetic parameters for body weight and survival of Nile tilapia farmed in Brazil

The objective of this study was to estimate genetic parameters for survival and weight of Nile tilapia (Oreochromis niloticus), farmed in cages and ponds in Brazil, and to predict genetic gain under different scenarios. Survival was recorded as a binary response (dead or alive), during harvest time in the 2008 grow-out period. Genetic parameters were estimated using a Bayesian mixed linear-threshold animal model via Gibbs sampling. The breeding population consisted of 2,912 individual fish, which were analyzed together with the pedigree of 5,394 fish. The heritabilities estimates, with 95% posterior credible intervals, for tagging weight, harvest weight and survival were 0.17 (0.09-0.27), 0.21 (0.12-0.32) and 0.32 (0.22-0.44), respectively. Credible intervals show a 95% probability that the true genetic correlations were in a favourable direction. The selection for weight has a positive impact on survival. Estimated genetic gain was high when selecting for harvest weight (5.07%), and indirect gain for tagging weight (2.17%) and survival (2.03%) were also considerable.

Predictors for hospitalization and outpatient visits in patients with inflammatory bowel disease: results from the Swiss Inflammatory Bowel Disease Cohort Study.

OBJECTIVES: Patients with inflammatory bowel disease (IBD) have a high resource consumption, with considerable costs for the healthcare system. In a system with sparse resources, treatment is influenced not only by clinical judgement but also by resource consumption. We aimed to determine the resource consumption of IBD patients and to identify its significant predictors. MATERIALS AND METHODS: Data from the prospective Swiss Inflammatory Bowel Disease Cohort Study were analysed for the resource consumption endpoints hospitalization and outpatient consultations at enrolment [1187 patients; 41.1% ulcerative colitis (UC), 58.9% Crohn's disease (CD)] and at 1-year follow-up (794 patients). Predictors of interest were chosen through an expert panel and a review of the relevant literature. Logistic regressions were used for binary endpoints, and negative binomial regressions and zero-inflated Poisson regressions were used for count data. RESULTS: For CD, fistula, use of biologics and disease activity were significant predictors for hospitalization days (all P-values <0.001); age, sex, steroid therapy and biologics were significant predictors for the number of outpatient visits (P=0.0368, 0.023, 0.0002, 0.0003, respectively). For UC, biologics, C-reactive protein, smoke quitters, age and sex were significantly predictive for hospitalization days (P=0.0167, 0.0003, 0.0003, 0.0076 and 0.0175 respectively); disease activity and immunosuppressive therapy predicted the number of outpatient visits (P=0.0009 and 0.0017, respectively). The results of multivariate regressions are shown in detail. CONCLUSION: Several highly significant clinical predictors for resource consumption in IBD were identified that might be considered in medical decision-making. In terms of resource consumption and its predictors, CD and UC show a different behaviour.