Strokes in the anterior circulation: comparison between bridging and intravenous thrombolysis.

BACKGROUND AND PURPOSE: To compare safety and efficacy of bridging approach with intravenous (IV) thrombolysis in patients with acute anterior strokes and proximal occlusions. PATIENTS AND METHODS: Consecutive patients with ischemic anterior strokes admitted within a 4 h 30 min window in two different centers were included. The first center performed IV therapy (alteplase 0.6 mg/kg) during 30 min and, in absence of clinical improvement, mechanical thrombectomy with flow restoration using a Solitaire stent (StS); the second carried out IV thrombolysis (alteplase 0.9 mg/kg) alone. Only T, M1 or M2 occlusions present on CT angiography were considered. Endpoints were clinical outcome and mortality at 3 months. RESULTS: There were 63 patients in the bridging and 163 in the IV group. No significant differences regarding baseline characteristics were observed. At 3 months, 46% (n = 29) of the patients treated in the combined and 23% (n = 38) of those treated in the IV group had a modified Rankin scale (mRS) of 0-1 (P < 0.001). A statistical significant difference was observed for all sites of occlusion. In a logistic regression model, National Institute of Health Stroke Scale (NIHSS) and bridging therapy were independent predictors of good outcome (respectively, P = 0.001 and P = 0.0018). Symptomatic hemorrhage was documented in 6.3% vs 3.7% in the bridging and in the IV group, respectively (P = 0.32). There was no difference in mortality. CONCLUSIONS: Our results suggest that patients treated with a bridging approach were more likely to have minimal or no deficit at all at 3 months as compared to the IV treated group.

Statins are associated with decreased mortality risk after status epilepticus.

BACKGROUND AND PURPOSE: Statins display anti-inflammatory and anti-epileptogenic properties in animal models, and may reduce the epilepsy risk in elderly humans; however, a possible modulating role on outcome in patients with status epilepticus (SE) has not been assessed. METHODS: This cohort study was based on a prospective registry including all consecutive adults with incident SE treated in our center between April 2006 and September 2012. SE outcome was categorized at hospital discharge into 'return to baseline', 'new disability' and 'mortality'. The role of potential predictors, including statins treatment on admission, was evaluated using a multinomial logistic regression model. RESULTS: Amongst 427 patients identified, information on statins was available in 413 (97%). Mean age was 60.9 (±17.8) years; 201 (49%) were women; 211 (51%) had a potentially fatal SE etiology; and 191 (46%) experienced generalized-convulsive or non-convulsive SE in coma. Statins (simvastatin, atorvastatin or pravastatin) were prescribed prior to admission in 76 (18%) subjects, mostly elderly. Whilst 208 (50.4%) patients returned to baseline, 58 (14%) died. After adjustment for established SE outcome predictors (age, etiology, SE severity score), statins correlated significantly with lower mortality (relative risk ratio 0.38, P = 0.046). CONCLUSION: This study suggests for the first time that exposure to statins before an SE episode is related to its outcome, involving a possible anti-epileptogenic role. Other studies are needed to confirm this intriguing finding.

Incidence and Risk Factors of Abdominal Complications After Lung Transplantation.

BACKGROUND: Due to the underlying diseases and the need for immunosuppression, patients after lung transplantation are particularly at risk for gastrointestinal (GI) complications that may negatively influence long-term outcome. The present study assessed the incidences and impact of GI complications after lung transplantation and aimed to identify risk factors. METHODS: Retrospective analysis of all 227 consecutively performed single- and double-lung transplantations at the University hospitals of Lausanne and Geneva was performed between January 1993 and December 2010. Logistic regressions were used to test the effect of potentially influencing variables on the binary outcomes overall, severe, and surgery-requiring complications, followed by a multiple logistic regression model. RESULTS: Final analysis included 205 patients for the purpose of the present study, and 22 patients were excluded due to re-transplantation, multiorgan transplantation, or incomplete datasets. GI complications were observed in 127 patients (62 %). Gastro-esophageal reflux disease was the most commonly observed complication (22.9 %), followed by inflammatory or infectious colitis (20.5 %) and gastroparesis (10.7 %). Major GI complications (Dindo/Clavien III-V) were observed in 83 (40.5 %) patients and were fatal in 4 patients (2.0 %). Multivariate analysis identified double-lung transplantation (p = 0.012) and early (1993-1998) transplantation period (p = 0.008) as independent risk factors for developing major GI complications. Forty-three (21 %) patients required surgery such as colectomy, cholecystectomy, and fundoplication in 6.8, 6.3, and 3.9 % of the patients, respectively. Multivariate analysis identified Charlson comorbidity index of ≥3 as an independent risk factor for developing GI complications requiring surgery (p = 0.015). CONCLUSION: GI complications after lung transplantation are common. Outcome was rather encouraging in the setting of our transplant center.

Comparative effectiveness of gemcitabine plus cisplatin versus methotrexate, vinblastine, doxorubicin, plus cisplatin as neoadjuvant therapy for muscle-invasive bladder cancer.

BACKGROUND: Gemcitabine plus cisplatin (GC) has been adopted as a neoadjuvant regimen for muscle-invasive bladder cancer despite the lack of Level I evidence in this setting. METHODS: Data were collected using an electronic data-capture platform from 28 international centers. Eligible patients had clinical T-classification 2 (cT2) through cT4aN0M0 urothelial cancer of the bladder and received neoadjuvant GC or methotrexate, vinblastine, doxorubicin, plus cisplatin (MVAC) before undergoing cystectomy. Logistic regression was used to compute propensity scores as the predicted probabilities of patients being assigned to MVAC versus GC given their baseline characteristics. These propensity scores were then included in a new logistic regression model to estimate an adjusted odds ratio comparing the odds of attaining a pathologic complete response (pCR) between patients who received MVAC and those who received GC. RESULTS: In total, 212 patients (146 patients in the GC cohort and 66 patients in the MVAC cohort) met criteria for inclusion in the analysis. The majority of patients in the MVAC cohort (77%) received dose-dense MVAC. The median age of patients was 63 years, they were predominantly men (74%), and they received a median of 3 cycles of neoadjuvant chemotherapy. The pCR rate was 29% in the MVAC cohort and 31% in the GC cohort. There was no significant difference in the pCR rate when adjusted for propensity scores between the 2 regimens (odds ratio, 0.91; 95% confidence interval, 0.48-1.72; P = .77). In an exploratory analysis evaluating survival, the hazard ratio comparing hazard rates for MVAC versus GC adjusted for propensity scores was not statistically significant (hazard ratio, 0.78; 95% confidence interval, 0.40-1.54; P = .48). CONCLUSIONS: Patients who received neoadjuvant GC and MVAC achieved comparable pCR rates in the current analysis, providing evidence to support what has become routine practice. Cancer 2015;121:2586-2593. © 2015 American Cancer Society.

Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

Model development for capercaillie (Tetrao urogallus) habitat in the Jura Mountains (Western Switzerland)

Capercaillie, Tetrao urogallus, is a threatened species in central Europe, and Swiss populations declined 40 to 50 % between 1970 and 1985. Capercaillie are sensitive to forest structure, and loss of habitat is a major cause of their decline. Knowledge of habitat characteristics is therefore essential for capercaillie conservation. Here, we present models predicting capercaillie probability of occurrence, based on relevant structural habitat variables. Models were built using multiple logistic regression analyses on capercaillie presence/absence data. Vegetation survey was carried out in July 1999 in a 170-km2 forested area (Jura mountains, canton de Vaud, western Switzerland) inhabited by capercaillie and presence/absence of the species was assessed according to dropping presence/absence. The survey was based on 10-m-radius sample plots each in a 1-km2 forest patch (n = 76 with capercaillie droppings, n = 80 without). A first model included seven out of 27 measured habitat variables and a second model only four. The latter model best represents practical needs. It includes three variables which had a negative impact on capercaillie presence: tree and shrub covers and spruce, Picea excelsa, shrub cover, and one which had a positive effect: bilberry, Vaccinium myrtillus, cover, highlighting that capaercaillie selected open forest with high bilberry abundance. The model can be used to map potential capercaillie habitat distribution and to manage the habitat in favour of capercaillie (protection and adapted forestry practices) in the Swiss Jura mountains.

Derivation and validation of a prognostic model for pulmonary embolism.

RATIONALE: An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment. OBJECTIVES: To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes. METHODS: We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France. MEASUREMENTS: We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. MAIN RESULTS: The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were <or= 1.1% among patients in class I and <or= 1.9% among patients in class II. CONCLUSIONS: Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

Relationships between imatinib plasma levels and efficacy

Purpose: While imatinib has revolutionized the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumors (GIST), its pharmacokinetic-pharmacodynamic relationships have been poorly studied. This study aimed to explore the issue in oncologic patients, and to evaluate the specific influence of the target genotype in a GIST subpopulation. Patients and methods: Data from 59 patients (321 plasma samples) were collected during a previous pharmacokinetic study. Based on a population model purposely developed, individual post-hoc Bayesian estimates of pharmacokinetic parameters were derived, and used to estimate drug exposure (AUC; area under curve). Free fraction parameters were deduced from a model incorporating plasma alpha1-acid glycoprotein levels. Associations between AUC (or clearance) and therapeutic response (coded on a 3-point scale), or tolerability (4-point scale), were explored by ordered logistic regression. Influence of KIT genotype on response was also assessed in GIST patients. Results: Total and free drug exposure correlated with the number of side effects (p < 0.005). A relationship with response was not evident in the whole patient set (with good-responders tending to receive lower doses and bad-responders higher doses). In GIST patients however, higher free drug exposure predicted better responses. A strong association was notably observed in patients harboring an exon 9 mutation or a wild type KIT, known to decrease tumor sensitivity towards imatinib (p < 0.005). Conclusions: Our results are arguments to further evaluate the potential benefit of a therapeutic monitoring program for imatinib. Our data also suggest that stratification by genotype will be important in future trials.

A general model to predict individual exposure to solar UV by using ambient irradiance data

Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.

Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study.

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

Probability of achieving optimal molecular response to imatinib in chronic myeloid leukemia (CML) patients: Pharmacokinetic/Pharmacodynamic (PK/PD) relationships observed under field-conditions

Objectives: Imatinib has been increasingly proposed for therapeutic drug monitoring (TDM), as trough concentrations (Cmin) correlate with response rates in CML patients. This analysis aimed to evaluate the impact of imatinib exposure on optimal molecular response rates in a large European cohort of patients followed by centralized TDM.¦Methods: Sequential PK/PD analysis was performed in NONMEM 7 on 2230 plasma (PK) samples obtained along with molecular response (PD) data from 1299 CML patients. Model-based individual Bayesian estimates of exposure, parameterized as to initial dose adjusted and log-normalized Cmin (log-Cmin) or clearance (CL), were investigated as potential predictors of optimal molecular response, while accounting for time under treatment (stratified at 3 years), gender, CML phase, age, potentially interacting comedication, and TDM frequency. PK/PD analysis used mixed-effect logistic regression (iterative two-stage method) to account for intra-patient correlation.¦Results: In univariate analyses, CL, log-Cmin, time under treatment, TDM frequency, gender (all p<0.01) and CML phase (p=0.02) were significant predictors of the outcome. In multivariate analyses, all but log-Cmin remained significant (p<0.05). Our model estimates a 54.1% probability of optimal molecular response in a female patient with a median CL of 14.4 L/h, increasing by 4.7% with a 35% decrease in CL (percentile 10 of CL distribution), and decreasing by 6% with a 45% increased CL (percentile 90), respectively. Male patients were less likely than female to be in optimal response (odds ratio: 0.62, p<0.001), with an estimated probability of 42.3%.¦Conclusions: Beyond CML phase and time on treatment, expectedly correlated to the outcome, an effect of initial imatinib exposure on the probability of achieving optimal molecular response was confirmed in field-conditions by this multivariate analysis. Interestingly, male patients had a higher risk of suboptimal response, which might not exclusively derive from their 18.5% higher CL, but also from reported lower adherence to the treatment. A prospective longitudinal study would be desirable to confirm the clinical importance of identified covariates and to exclude biases possibly affecting this observational survey.

Predictors of HIV-protection behaviour in HIV-positive men who have sex with casual male partners: a test of the explanatory power of an extended Information-Motivation-Behavioural Skills model.

This prospective study applies an extended Information-Motivation-Behavioural Skills (IMB) model to establish predictors of HIV-protection behaviour among HIV-positive men who have sex with men (MSM) during sex with casual partners. Data have been collected from anonymous, self-administered questionnaires and analysed by using descriptive and backward elimination regression analyses. In a sample of 165 HIV-positive MSM, 82 participants between the ages of 23 and 78 (M=46.4, SD=9.0) had sex with casual partners during the three-month period under investigation. About 62% (n=51) have always used a condom when having sex with casual partners. From the original IMB model, only subjective norm predicted condom use. More important predictors that increased condom use were low consumption of psychotropics, high satisfaction with sexuality, numerous changes in sexual behaviour after diagnosis, low social support from friends, alcohol use before sex and habitualised condom use with casual partner(s). The explanatory power of the calculated regression model was 49% (p<0.001). The study reveals the importance of personal and social resources and of routines for condom use, and provides information for the research-based conceptualisation of prevention offers addressing especially people living with HIV ("positive prevention").

Swallowed topical corticosteroids reduce the risk for long-lasting bolus impactions in eosinophilic esophagitis.

BACKGROUND: Long-lasting food impactions requiring endoscopic bolus removal occur frequently in patients with eosinophilic esophagitis (EoE) and harbor a risk for severe esophageal injuries. We evaluated whether treatment with swallowed topical corticosteroids is able to reduce the risk of occurrence of this complication. METHODS: We analyzed data from the Swiss EoE Cohort Study. Patients with yearly clinic visits, during which standardized assessment of symptoms, endoscopic, histologic, and laboratory findings was carried out, were included. RESULTS: A total of 206 patients (157 males) were analyzed. The median follow-up time was 5 years with a total of 703 visits (mean 3.41 visits/patient). During the follow-up period, 33 patients (16 % of the cohort) experienced 42 impactions requiring endoscopic bolus removal. We evaluated the following factors regarding the outcome 'bolus impaction' by univariate logistic regression modeling: swallowed topical corticosteroid therapy (OR 0.503, 95%-CI 0.255-0.993, P = 0.048), presence of EoE symptoms (OR 1.150, 95%-CI 0.4668-2.835, P = 0.761), esophageal stricture (OR 2.832, 95%-CI 1.508-5.321, P = 0.001), peak eosinophil count >10 eosinophils/HPF (OR 0.724, 95%-CI 0.324-1.621, P = 0.433), blood eosinophilia (OR 1.532, 95%-CI 0.569-4.118, P = 0.398), and esophageal dilation (OR 1.852, 95%-CI 1.034-3.755, P = 0.017). In the multivariate model, the following factors were significantly associated with bolus impaction: swallowed topical corticosteroid therapy (OR 0.411, 95%-CI 0.203-0.835, P = 0.014) and esophageal stricture (OR 2.666, 95%-CI 1.259-5.645, P = 0.01). Increasing frequency of use of swallowed topical steroids was associated with a lower risk for bolus impactions. CONCLUSIONS: Treatment of EoE with swallowed topical corticosteroids significantly reduces the risk for long-lasting bolus impactions.

Predicting outcome after acute basilar artery occlusion based on admission characteristics.

OBJECTIVE: To develop a simple prognostic model to predict outcome at 1 month after acute basilar artery occlusion (BAO) with readily available predictors. METHODS: The Basilar Artery International Cooperation Study (BASICS) is a prospective, observational, international registry of consecutive patients who presented with an acute symptomatic and radiologically confirmed BAO. We considered predictors available at hospital admission in multivariable logistic regression models to predict poor outcome (modified Rankin Scale [mRS] score 4-5 or death) at 1 month. We used receiver operator characteristic curves to assess the discriminatory performance of the models. RESULTS: Of the 619 patients, 429 (69%) had a poor outcome at 1 month: 74 (12%) had a mRS score of 4, 115 (19%) had a mRS score of 5, and 240 (39%) had died. The main predictors of poor outcome were older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIH Stroke Scale (NIHSS) score, and longer time to treatment. A prognostic model that combined demographic data and stroke risk factors had an area under the receiver operating characteristic curve (AUC) of 0.64. This performance improved by including findings from the neurologic examination (AUC 0.79) and CT imaging (AUC 0.80). A risk chart showed predictions of poor outcome at 1 month varying from 25 to 96%. CONCLUSION: Poor outcome after BAO can be reliably predicted by a simple model that includes older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIHSS score, and longer time to treatment.