178 resultados para LOGISTIC REGRESSION WITH STATE-DEPENDENT SAMPLE SELECTION
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Working conditions are important determinants of health. The aims of this article are to 1) identify working conditions and work characteristics that are associated with workers' perceptions that their work is harmful to their health and 2) identify with what symptoms these working conditions are associated.We used the Swiss dataset from the 2005 edition of the European Working Conditions Survey. The dependent variable was based on the question "Does your work affect your health?". Logistic regression was used to identify a set of variables collectively associated with self-reported work-related adverse health effects.A total of 330 (32%) participants reported having their health affected by work. The most frequent symptoms included backache (17.1%), muscular pains (13.1%), stress (18.3%) and overall fatigue (11.7%). Scores for self-reported exposure to physicochemical risks, postural and physical risks, high work demand, and low social support were all significantly associated with workers' perceptions that their work is harmful to their health, regardless of gender or age. A high level of education was associated with stress symptoms, and reports that health was affected by work was associated with low job satisfaction.Many workers believe that their work affects their health. Health specialists should pay attention to the potential association between work and their patients' health complaints. This is particularly relevant when patients mention symptoms such as muscular pains, backache, overall fatigue, and stress. Specific attention should be given to complaints of stress in highly educated workers.
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BACKGROUND: The objective of this study was to describe educational achievements of childhood cancer survivors in Switzerland compared with the general population. In particular, the authors investigated educational problems during childhood, final educational achievement in adulthood, and its predictors. METHODS: Childhood cancer survivors who were aged <16 years at diagnosis from 1976 to 2003 who had survived for ≥5 years and were currently ages 20 to 40 years received a postal questionnaire during 2007 to 2009. Controls were respondents of the Swiss Health Survey ages 20 to 40 years. Educational achievement included compulsory schooling, vocational training, upper secondary schooling, and university degree. The analysis was weighted to optimize comparability of the populations. The authors analyzed the association between demographic and clinical predictors and educational achievement using multivariable logistic regression. Subgroup analyses focused on survivors aged ≥27 years. RESULTS: One-third of survivors encountered educational problems during schooling (30% repeated 1 year, and 35% received supportive tutoring). In the total sample, more survivors than controls achieved compulsory schooling only (8.7% vs 5.2%) and fewer acquired a university degree (7.3% vs 11%), but more survivors than controls achieved an upper secondary education (36.1 vs 24.1%). In those aged ≥27 years, differences in compulsory schooling and university education largely disappeared. In survivors and controls, sex, nationality, language region, and migration background were strong predictors of achievement. Survivors of central nervous system tumors or those who had a relapse had poorer outcomes (P < .05). CONCLUSIONS: Childhood cancer survivors encountered problems during schooling and completed professional education with some delay. However, with the exception of patients who had central nervous system tumors and those who experienced a relapse, the final educational achievement in survivors of child cancer was comparable to that of the general population.
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A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.
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This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.
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BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.
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AIM: This study examined whether problematic Internet use was associated with substance use among young adolescents and assessed whether this association accounted for the use of tobacco, alcohol, cannabis and other drugs. METHODS: Using the Internet Addiction Test, we divided a representative sample of 3067 adolescents in Switzerland (mean age 14 years) into regular and problematic Internet users. We performed a bivariate analysis and two logistic regression models, to analyse substances separately and simultaneously, and developed a log-linear model to define the associations between significant variables. RESULTS: Problematic Internet users were more likely to be female, to use substances, to come from nonintact families, to report poor emotional well-being and to be below average students. The first model showed significant associations between problematic users and each substance, with adjusted odds ratios of 2.05 for tobacco, 1.72 for alcohol, 1.94 for cannabis and 2.73 for other drugs. Only smoking remained significant in the second model, with an adjusted odds ratio of 1.71. CONCLUSION: Problematic Internet use is associated with other risky behaviours and may be an important early predictor of adolescent substance use. Therefore, it should be included in the psychosocial screening of adolescents.
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BACKGROUND: Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. AIM: To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. METHODS: Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. RESULTS: A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. CONCLUSIONS: Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent.
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BACKGROUND: Healthy lifestyle including sufficient physical activity may mitigate or prevent adverse long-term effects of childhood cancer. We described daily physical activities and sports in childhood cancer survivors and controls, and assessed determinants of both activity patterns. METHODOLOGY/PRINCIPAL FINDINGS: The Swiss Childhood Cancer Survivor Study is a questionnaire survey including all children diagnosed with cancer 1976-2003 at age 0-15 years, registered in the Swiss Childhood Cancer Registry, who survived ≥5 years and reached adulthood (≥20 years). Controls came from the population-based Swiss Health Survey. We compared the two populations and determined risk factors for both outcomes in separate multivariable logistic regression models. The sample included 1058 survivors and 5593 controls (response rates 78% and 66%). Sufficient daily physical activities were reported by 52% (n = 521) of survivors and 37% (n = 2069) of controls (p<0.001). In contrast, 62% (n = 640) of survivors and 65% (n = 3635) of controls reported engaging in sports (p = 0.067). Risk factors for insufficient daily activities in both populations were: older age (OR for ≥35 years: 1.5, 95CI 1.2-2.0), female gender (OR 1.6, 95CI 1.3-1.9), French/Italian Speaking (OR 1.4, 95CI 1.1-1.7), and higher education (OR for university education: 2.0, 95CI 1.5-2.6). Risk factors for no sports were: being a survivor (OR 1.3, 95CI 1.1-1.6), older age (OR for ≥35 years: 1.4, 95CI 1.1-1.8), migration background (OR 1.5, 95CI 1.3-1.8), French/Italian speaking (OR 1.4, 95CI 1.2-1.7), lower education (OR for compulsory schooling only: 1.6, 95CI 1.2-2.2), being married (OR 1.7, 95CI 1.5-2.0), having children (OR 1.3, 95CI 1.4-1.9), obesity (OR 2.4, 95CI 1.7-3.3), and smoking (OR 1.7, 95CI 1.5-2.1). Type of diagnosis was only associated with sports. CONCLUSIONS/SIGNIFICANCE: Physical activity levels in survivors were lower than recommended, but comparable to controls and mainly determined by socio-demographic and cultural factors. Strategies to improve physical activity levels could be similar as for the general population.
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BACKGROUND: Early detection and treatment of colorectal adenomatous polyps (AP) and colorectal cancer (CRC) is associated with decreased mortality for CRC. However, accurate, non-invasive and compliant tests to screen for AP and early stages of CRC are not yet available. A blood-based screening test is highly attractive due to limited invasiveness and high acceptance rate among patients. AIM: To demonstrate whether gene expression signatures in the peripheral blood mononuclear cells (PBMC) were able to detect the presence of AP and early stages CRC. METHODS: A total of 85 PBMC samples derived from colonoscopy-verified subjects without lesion (controls) (n = 41), with AP (n = 21) or with CRC (n = 23) were used as training sets. A 42-gene panel for CRC and AP discrimination, including genes identified by Digital Gene Expression-tag profiling of PBMC, and genes previously characterised and reported in the literature, was validated on the training set by qPCR. Logistic regression analysis followed by bootstrap validation determined CRC- and AP-specific classifiers, which discriminate patients with CRC and AP from controls. RESULTS: The CRC and AP classifiers were able to detect CRC with a sensitivity of 78% and AP with a sensitivity of 46% respectively. Both classifiers had a specificity of 92% with very low false-positive detection when applied on subjects with inflammatory bowel disease (n = 23) or tumours other than CRC (n = 14). CONCLUSION: This pilot study demonstrates the potential of developing a minimally invasive, accurate test to screen patients at average risk for colorectal cancer, based on gene expression analysis of peripheral blood mononuclear cells obtained from a simple blood sample.
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BACKGROUND & AIMS: Hepatitis C virus (HCV) induces chronic infection in 50% to 80% of infected persons; approximately 50% of these do not respond to therapy. We performed a genome-wide association study to screen for host genetic determinants of HCV persistence and response to therapy. METHODS: The analysis included 1362 individuals: 1015 with chronic hepatitis C and 347 who spontaneously cleared the virus (448 were coinfected with human immunodeficiency virus [HIV]). Responses to pegylated interferon alfa and ribavirin were assessed in 465 individuals. Associations between more than 500,000 single nucleotide polymorphisms (SNPs) and outcomes were assessed by multivariate logistic regression. RESULTS: Chronic hepatitis C was associated with SNPs in the IL28B locus, which encodes the antiviral cytokine interferon lambda. The rs8099917 minor allele was associated with progression to chronic HCV infection (odds ratio [OR], 2.31; 95% confidence interval [CI], 1.74-3.06; P = 6.07 x 10(-9)). The association was observed in HCV mono-infected (OR, 2.49; 95% CI, 1.64-3.79; P = 1.96 x 10(-5)) and HCV/HIV coinfected individuals (OR, 2.16; 95% CI, 1.47-3.18; P = 8.24 x 10(-5)). rs8099917 was also associated with failure to respond to therapy (OR, 5.19; 95% CI, 2.90-9.30; P = 3.11 x 10(-8)), with the strongest effects in patients with HCV genotype 1 or 4. This risk allele was identified in 24% of individuals with spontaneous HCV clearance, 32% of chronically infected patients who responded to therapy, and 58% who did not respond (P = 3.2 x 10(-10)). Resequencing of IL28B identified distinct haplotypes that were associated with the clinical phenotype. CONCLUSIONS: The association of the IL28B locus with natural and treatment-associated control of HCV indicates the importance of innate immunity and interferon lambda in the pathogenesis of HCV infection.
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AIM: To confirm the accuracy of sentinel node biopsy (SNB) procedure and its morbidity, and to investigate predictive factors for SN status and prognostic factors for disease-free survival (DFS) and disease-specific survival (DSS). MATERIALS AND METHODS: Between October 1997 and December 2004, 327 consecutive patients in one centre with clinically node-negative primary skin melanoma underwent an SNB by the triple technique, i.e. lymphoscintigraphy, blue-dye and gamma-probe. Multivariate logistic regression analyses as well as the Kaplan-Meier were performed. RESULTS: Twenty-three percent of the patients had at least one metastatic SN, which was significantly associated with Breslow thickness (p<0.001). The success rate of SNB was 99.1% and its morbidity was 7.6%. With a median follow-up of 33 months, the 5-year DFS/DSS were 43%/49% for patients with positive SN and 83.5%/87.4% for patients with negative SN, respectively. The false-negative rate of SNB was 8.6% and sensitivity 91.4%. On multivariate analysis, DFS was significantly worsened by Breslow thickness (RR=5.6, p<0.001), positive SN (RR=5.0, p<0.001) and male sex (RR=2.9, p=0.001). The presence of a metastatic SN (RR=8.4, p<0.001), male sex (RR=6.1, p<0.001), Breslow thickness (RR=3.2, p=0.013) and ulceration (RR=2.6, p=0.015) were significantly associated with a poorer DSS. CONCLUSION: SNB is a reliable procedure with high sensitivity (91.4%) and low morbidity. Breslow thickness was the only statistically significant parameter predictive of SN status. DFS was worsened in decreasing order by Breslow thickness, metastatic SN and male gender. Similarly DSS was significantly worsened by a metastatic SN, male gender, Breslow thickness and ulceration. These data reinforce the SN status as a powerful staging procedure
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INTRODUCTION: Assessing motivation for change is deemed an important step in the treatment process that allows further refinement of the intervention in motivational interviewing (MI) and brief MI (BMI) adaptations. During MI (and BMI) sessions, motivation for change is expressed by the client as "change talk", i.e. all statements inclined toward or away from change. We tested the predictive validity of the Change Questionnaire, a 12-item instrument assessing motivation to change, on hazardous tobacco and alcohol use. METHODS: As part of the baseline measurements for a randomized controlled trial on multi-substance BMI at the Lausanne recruitment center (army conscription is mandatory in Switzerland for males at age 20, and thus provides a unique opportunity to address a non-clinical and largely representative sample of young men), 213 participants completed the questionnaire on tobacco and 95 on alcohol and were followed-up six months later. The overall Change Questionnaire score and its six subscales (Desire, Ability, Reasons, Need, Commitment, and Taking steps) were used as predictors of hazardous tobacco use (defined as daily smoking) and hazardous alcohol use (defined as more than one occasion with six standard drinks or more per month, and/or more than 21 standard drinks per week) in bivariate logistic regression models at follow-up. RESULTS: Higher overall Change scores were significant predictors of decreased risk for hazardous tobacco (odds ratio [OR] = 0.83, p = 0.046) and alcohol (OR = 0.76, p = 0.03) use. Several sub-dimensions were associated with the outcomes in bivariate analyses. Using a principal components analysis to reduce the number of predictors for multivariate models, we obtained two components. 'Ability to change' was strongly related to change in hazardous tobacco use (OR = 0.54, p < 0.001), the second we interpreted as 'Other change language dimensions' and which was significantly related to change in hazardous alcohol use (OR = 0.81, p = 0.05). CONCLUSIONS: The present findings lend initial support for the predictive validity of the Change Questionnaire on hazardous tobacco and alcohol use, making it an interesting and potentially useful tool for assessing motivation to change among young males.
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Background: Sponsoring of physicians meetings by life science companies has led to reduced participation fees but might influence physician's prescription practices. A ban on such sponsoring may increase participation fees. We aimed to evaluate factors associated with physicians' willingness to pay for medical meetings, their position on the sponsoring of medical meetings and their opinion on alternative financing options. Methods: An anonymous web-based questionnaire was sent to 447 general practitioners in one state in Switzerland, identified through their affiliation to a medical association. The questionnaire evaluated physicians' willingness to pay for medical meetings, their perception of a bias in prescription practices induced by commercial support, their opinion on the introduction of a binding legislation and alternative financing options, their frequency of exchange with sales representatives and other relevant socioeconomic factors. We built a multivariate predictor logistic regression model to identify determinants of willingness to pay. Results: Of the 115 physicians who responded (response rate 26%), 48% were willing to pay more than what they currently pay for congresses, 79% disagreed that commercial support introduced a bias in their prescription practices and 61% disagreed that it introduced a bias in their colleagues' prescription practices. Based on the multivariate logistic regression, perception of a bias in peers prescription practices (OR=7.47, 95% CI 1.65-38.18) and group practice structure (OR=4.62, 95% CI 1.34-22.29) were significantly associated with an increase in willingness to pay. Two thirds (76%) of physicians did not support the introduction of a binding legislation and 53% were in favour of creating a general fund administered by an independent body. Conclusion: Our results suggest that almost half of physicians surveyed are willing to pay more than what they currently pay for congresses. Predictors of an increase in physicians' willingness to pay were perception of the influence of bias in peers prescription practices and group practice structure. Most responders did not agree that sponsoring introduced prescribing bias nor did they support the 2 introduction of a binding legislation prohibiting sponsoring but a majority did agree to an independent body that would centrally administer a general fund.
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Although associated with adverse outcomes in other cardiopulmonary diseases, limited evidence exists on the prognostic value of anaemia in patients with acute pulmonary embolism (PE). We sought to examine the associations between anaemia and mortality and length of hospital stay in patients with PE. We evaluated 14,276 patients with a primary diagnosis of PE from 186 hospitals in Pennsylvania, USA. We used random-intercept logistic regression to assess the association between anaemia at the time of presentation and 30-day mortality and discrete-time logistic hazard models to assess the association between anaemia and time to hospital discharge, adjusting for patient (age, gender, race, insurance type, clinical and laboratory variables) and hospital (region, size, teaching status) factors. Anaemia was present in 38.7% of patients at admission. Patients with anaemia had a higher 30-day mortality (13.7% vs. 6.3%; p <0.001) and a longer length of stay (geometric mean, 6.9 vs. 6.6 days; p <0.001) compared to patients without anaemia. In multivariable analyses, anaemia remained associated with an increased odds of death (OR 1.82, 95% CI: 1.60-2.06) and a decreased odds of discharge (OR 0.85, 95% CI: 0.82-0.89). Anaemia is very common in patients presenting with PE and is independently associated with an increased short-term mortality and length of stay.
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Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.