Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

BACKGROUND AND PURPOSE: Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. METHODS: The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. RESULTS: In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)). CONCLUSIONS: The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

Predictive ability of severe rainfall events over Catalonia for the year 2008

This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9¿10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (¿24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC) rainfall forecasts; therefore we have not taken into account those episodes that might (or might not) have been missed by the official SMC warnings. Therefore, whenever we talk about "misses", it is always in relation to the deterministic LAMs' QPFs.

INTERMED predicts non-return to work in an occupational rehabilitation setting for individuals with orthopaedic trauma-Part I

Introduction.- Knowledge of predictors of an unfavourable outcome, e.g. non-return to work after an injury enables to identify patients at risk and to target interventions for modifiable predictors. It has been recently shown that INTERMED; a tool to measure biopsychosocial complexity in four domains (biologic, psychologic, social and care, with a score between 0-60 points) can be useful in this context. The aim of this study was to set up a predictive model for non-return to work using INTERMED in patients in vocational rehabilitation after orthopaedic injury.Patients and methods.- In this longitudinal prospective study, the cohort consisted of 2156 consecutively included inpatients with orthopaedic trauma attending a rehabilitation hospital after a work, traffic or sport related injury. Two years after discharge, a questionnaire regarding return to work was sent (1502 returned their questionnaires). In addition to INTERMED, 18 predictors known at baseline of the rehabilitation were selected based on previous research. A multivariable logistic regression was performed.Results.- In the multivariate model, not-returning to work at 2 years was significantly predicted by the INTERMED: odds-ratio (OR) 1.08 (95% confidence interval, CI [1.06; 1.11]) for a one point increase in scale; by qualified work-status before the injury OR = 0.74, CI (0.54; 0.99), by using French as preferred language OR = 0.60, CI (0.45; 0.80), by upper-extremity injury OR = 1.37, CI (1.03; 1.81), by higher education (> 9 years) OR = 0.74, CI (0.55; 1.00), and by a 10 year increase in age OR = 1.15, CI (1.02; 1.29). The area under the receiver-operator-characteristics curve (ROC)-curve was 0.733 for the full model (INTERMED plus 18 variables).Discussion.- These results confirm that the total score of the INTERMED is a significant predictor for return to work. The full model with 18 predictors combined with the total score of INTERMED has good predictive value. However, the number of variables (19) to measure is high for the use as screening tool in a clinic.

Glomerular filtration rate: measure creatinine and height rather than cystatin C!

AIM: Inulin clearance (Cin) is the gold standard for assessing glomerular filtration rate (GFR). Other methods are based on the plasma creatinine concentration (Pcreat), creatinine clearance (Ccreat), the Haycock-Schwartz formula and the plasma concentration of cystatin C (PcysC), a 13 kDa basic protein produced at a constant rate by all nucleated cells. The present prospective study was thus designed to evaluate the reliability of PcysC as a marker of GFR in comparison with that of Pcreat, Ccreat and the Haycock-Schwartz formula, using Cin as the gold standard. METHODS: Ninety-nine children (51 m/48 f), with a median age of 8.3 y (1.0-17.9) were studied. Using a cut-off for Cin of 100 ml/min per 1.73 m2, 54 children (54.5%) had impaired GFR. Those with normal GFR were comparable for age, height, weight and body mass index. RESULTS: Logistic regression, ROC analysis and linear regression all showed that Ccreat was the best parameter to discriminate between impaired and normal GFR, followed by the Haycock-Schwartz formula, PcysC, and finally Pcreat, each one being significantly more predictive than the next. CONCLUSION: GFR is better assessed by the Haycock-Schwartz formula than by PcysC or Pcreat alone. It is therefore concluded that when urine collection is not possible, simply measuring the child's Pcreat and height is the best, easiest and cheapest way to assess GFR.

Predictive factors in the long term outcome in gastro-oesophageal reflux disease: six years follow up of 107 patients

There is little information concerning the long term outcome of patients with gastro-oesophageal reflux disease (GORD). Thus 109 patients with reflux symptoms (33 with erosive oesophagitis) with a diagnosis of GORD after clinical evaluation and oesophageal testing were studied. All patients were treated with a stepwise approach: (a) lifestyle changes were suggested aimed at reducing reflux and antacids and the prokinetic agent domperidone were prescribed; (b) H2 blockers were added after two months when symptoms persisted; (c) anti-reflux surgery was indicated when there was no response to (b). Treatment was adjusted to maintain clinical remission during follow up. Long term treatment need was defined as minor when conservative measures sufficed for proper control, and as major if daily H2 blockers or surgery were required. The results showed that one third of the patients each had initial therapeutic need (a), (b), and (c). Of 103 patients available for follow up at three years and 89 at six years, respective therapeutic needs were minor in 52% and 55% and major in 48% and 45%. Eighty per cent of patients in (a), 67% in (b), and 17% in (c) required only conservative measures at six years. A decreasing lower oesophageal sphincter pressure (p < 0.001), radiological reflux (p = 0.028), and erosive oesophagitis (p = 0.031), but not initial clinical scores, were independent predictors of major therapeutic need as shown by multivariate analysis. The long term outcome of GORD is better than previously perceived.

Complete and long-lasting regression of disseminated multiple skin melanoma metastases under treatment with cyclooxygenase-2 inhibitor.

Experimental and clinical evidence indicates that non-steroidal anti-inflammatory drugs and cyclooxygenase-2 inhibitors may have anti-cancer activities. Here we report on a patient with a metastatic melanoma of the leg who experienced a complete and sustained regression of skin metastases upon continuous single treatment with the cyclooxygenase-2 inhibitor rofecoxib. Our observations indicate that the inhibition of cyclooxygenase-2 can lead to the regression of disseminated skin melanoma metastases, even after failure of chemotherapy.

Clinical experience with adalimumab in a multicenter Swiss cohort of patients with Crohn's disease.

BACKGROUND: Controlled clinical trials have demonstrated the efficacy and safety of adalimumab in patients with moderate-to-severe Crohn's disease (CD), but there is, however, only limited long-term experience with adalimumab in daily practice. AIM: To assess the long-term effectiveness and safety of adalimumab in a multicenter cohort of practice-based patients with moderate-to-severe CD. METHODS: We retrospectively reviewed the charts of CD patients who received adalimumab over a 3-year period. Disease severity was scored using the Harvey-Bradshaw index (HBI). Remission was defined as an HBI of <or=4 and response as a reduction in the HBI of >3 points at evaluation compared to the baseline. Univariate logistic regression analysis was used to identify the predictive variables associated with response. RESULTS: The charts of 55 patients were reviewed; remission and response rates observed at weeks 4-6 were 52.7 and 83.6%, respectively. Remission was maintained at weeks 12, 24 and 52 in 89.6, 72.4 and 44.7% of patients, respectively. Remission and response rates were not influenced by smoking status, disease location or duration, the first month total dose, or previous infliximab therapy. The remission rate at weeks 4-6 was significantly higher in patients intolerant of infliximab as compared to those who lost response to this drug. Adalimumab was well tolerated overall. CONCLUSION: Adalimumab can be considered a suitable option in patients with moderate-to-severe CD, demonstrating sustained long-term effectiveness.

Molecular Proxies for Climate Maladaptation in a Long-Lived Tree (Pinus pinaster Aiton, Pinaceae).

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change.

A prospective study of predictors of poststroke depression.

OBJECTIVE: To investigate the association between early depressive behavior after stroke onset and occurrence of poststroke depression (PSD) at 3- and 12-month follow-up evaluations. METHODS: The study prospectively included 273 patients with first-ever single uncomplicated ischemic stroke. In the stroke unit, nurses scored crying, overt sadness, and apathy daily using an observational method to include patients with comprehension deficits. The Barthel Index was used to assess disability. Follow-up evaluation at months 3 and 12 included psychiatric assessment based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition. RESULTS: Crying (19.8%), overt sadness (50.5%), and apathy (47.6%) were observed. Of the patients observed crying, 4 showed pathologic crying, 19 emotionalism, and 12 catastrophic reactions. Crying and overt sadness, but not apathy, were associated with a subjective experience of depression (p < 0.05). Thirty of 52 (58%) patients observed crying, 12 of 19 (63%) patients with emotionalism, and 5 of 12 (41%) patients with catastrophic reactions developed PSD within the first year. Multiple logistic regression analysis showed that only severe functional disability (odds ratio [OR], 4.31; 95% CI, 2.41 to 7.69), crying behaviors (OR, 2.66; 95% CI, 1.35 to 5.27), and an age <68 years (OR, 2.32; 95% CI, 1.30 to 4.13) were (p < 0.05) predictors of late PSD development (13% of the variance). CONCLUSIONS: In the stroke unit, crying and overt sadness are more reliable indicators of depressed mood than apathy. In patients with first-ever stroke, crying behaviors soon after stroke, a younger age, and severe disability are predictors of poststroke depression occurrence within the first year after stroke onset.

What is the influence of vaccination's routes on the regression of tumors located at mucosal sites?

Tumor-regressions following tumor-associated-antigen vaccination in animal models contrast with the limited clinical outcomes in cancer patients. Most animal studies however used subcutaneous-tumor-models and questions arise as whether these are relevant for tumors growing in mucosae; whether specific mucosal-homing instructions are required; and how this may be influenced by the tumor.

Do brief alcohol motivational interventions work like we think they do?

BACKGROUND: Questions remain about how brief motivational interventions (BMIs) for unhealthy alcohol use work, and addressing these questions may be important for improving their efficacy. Therefore, we assessed the effects of various characteristics of BMIs on drinking outcomes across 3 randomized controlled trials (RCTs). METHODS: Audio recordings of 314 BMIs were coded. We used the global rating scales of the Motivational Interviewing Skills Code (MISC) 2.1: counselor's acceptance, empathy, and motivational interviewing (MI) spirit, and patient's self-exploration were rated. MI proficiency was defined as counselor's rating scale scores ≥5. We also used the structure, confrontation, and advice subscale scores of the Therapy Process Rating Scale and the Working Alliance Inventory. We examined these process characteristics in interventions across 1 U.S. RCT of middle-aged medical inpatients with unhealthy alcohol use (n = 124) and 2 Swiss RCTs of young men with binge drinking in a nonclinical setting: Swiss-one (n = 62) and Swiss-two (n = 128). We assessed the associations between these characteristics and drinks/d reported by participants 3 to 6 months after study entry. RESULTS: In all 3 RCTs, mean MISC counselor's rating scales scores were consistent with MI proficiency. In overdispersed Poisson regression models, most BMI characteristics were not significantly associated with drinks/d in follow-up. In the U.S. RCT, confrontation and self-exploration were associated with more drinking. Giving advice was significantly associated with less drinking in the Swiss-one RCT. Contrary to expectations, MI spirit was not consistently associated with drinking across studies. CONCLUSIONS: Across different populations and settings, intervention characteristics viewed as central to efficacious BMIs were neither robust nor consistent predictors of drinking outcome. Although there may be alternative reasons why the level of MI processes was not predictive of outcomes in these studies (limited variability in scores), efforts to understand what makes BMIs efficacious may require attention to factors beyond intervention process characteristics typically examined.

Bootstrapping pairs in Distance-Based Regression

La regressió basada en distàncies és un mètode de predicció que consisteix en dos passos: a partir de les distàncies entre observacions obtenim les variables latents, les quals passen a ser els regressors en un model lineal de mínims quadrats ordinaris. Les distàncies les calculem a partir dels predictors originals fent us d'una funció de dissimilaritats adequada. Donat que, en general, els regressors estan relacionats de manera no lineal amb la resposta, la seva selecció amb el test F usual no és possible. En aquest treball proposem una solució a aquest problema de selecció de predictors definint tests estadístics generalitzats i adaptant un mètode de bootstrap no paramètric per a l'estimació dels p-valors. Incluim un exemple numèric amb dades de l'assegurança d'automòbils.

Pedotransfer functions related to spatial variability of water retention attributes for lowland soils

The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically different from those observed for all measured values. The PTFs that presented the best predictive values of Ug33 kPa and Ug1,500 kPa were not the same that had the best performance to reproduce the structure of spatial variability of these variables.