Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

Smooth transition or permanent exit? Evidence on job prospects of displaced industrial workers

This article examines the job prospects of displaced industrial workers in Switzerland. Based on a survey of 1,203 workers who were dismissed after their manufacturing plants closed down, we analyse the determinants of re-employment, the sector of re-employment and the change in wages. Two years after displacement, a majority of workers were back in employment: 69% were re-employed, 17% un-employed and 11% retired. Amongst re-employed workers, two thirds found a job in manufacturing and one third in services. Contrary to a common belief, low-end services are not the collecting vessel of redundant industrial workers. Displaced workers aged 55 and older seem particularly vulnerable after a plant closes down: over 30% were long-term unemployed, and those older workers who found a new job suffered disproportionate wage losses. Advanced age-and not low education-appears as the primary handicap after mass redundancy.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

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.

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").

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.

La transition des soins pédiatriques aux soins adultes des adolescents souffrant d'affections chroniques. [The transition from pediatric to adult care of chronically ill adolescents]

Bien que la transition des soins pédiatriques aux soins adultes soit extrêmement importante pour les adolescents souffrant de maladies chroniques, celle-ci se limite le plus souvent à un simple transfert. L'objectif de cet article est de décrire les barrières au bon déroulement de la transition du point de vue du patient et de sa famille, des professionnels de la santé et du système de soins; de détailler les éléments clés pour que la transition soit la moins traumatique possible; et d'énoncer les différentes approches proposées dans la littérature. [Abstract] The transition from pediatric to adult care of chronically ill adolescents Even though the transition from pediatric to adult health care is extremely important for chronically ill adolescents, most of the times it is limited to a simple transfer The objective of this paper is to describe the barriers to a smooth transition from the point of view of the patient and his/her family, the health professionals and the health system, to review the key elements for a smooth transition, and to address the different approaches proposed in the literature.

Evaluating thermal treeline indicators based on air and soil temperature using an air-to-soil temperature transfer model

In recent research, both soil (root-zone) and air temperature have been used as predictors for the treeline position worldwide. In this study, we intended to (a) test the proposed temperature limitation at the treeline, and (b) investigate effects of season length for both heat sum and mean temperature variables in the Swiss Alps. As soil temperature data are available for a limited number of sites only, we developed an air-to-soil transfer model (ASTRAMO). The air-to-soil transfer model predicts daily mean root-zone temperatures (10cm below the surface) at the treeline exclusively from daily mean air temperatures. The model using calibrated air and root-zone temperature measurements at nine treeline sites in the Swiss Alps incorporates time lags to account for the damping effect between air and soil temperatures as well as the temporal autocorrelations typical for such chronological data sets. Based on the measured and modeled root-zone temperatures we analyzed. the suitability of the thermal treeline indicators seasonal mean and degree-days to describe the Alpine treeline position. The root-zone indicators were then compared to the respective indicators based on measured air temperatures, with all indicators calculated for two different indicator period lengths. For both temperature types (root-zone and air) and both indicator periods, seasonal mean temperature was the indicator with the lowest variation across all treeline sites. The resulting indicator values were 7.0 degrees C +/- 0.4 SD (short indicator period), respectively 7.1 degrees C +/- 0.5 SD (long indicator period) for root-zone temperature, and 8.0 degrees C +/- 0.6 SD (short indicator period), respectively 8.8 degrees C +/- 0.8 SD (long indicator period) for air temperature. Generally, a higher variation was found for all air based treeline indicators when compared to the root-zone temperature indicators. Despite this, we showed that treeline indicators calculated from both air and root-zone temperatures can be used to describe the Alpine treeline position.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

General Practitioners' willingness to pay for continuing medical education in a fee-for-service universal coverage health care system

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.

Detecting epistasis with restricted response patterns in pairs of biallelic loci.

Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.

Risk factors for positive tuberculin skin tests among migrant and resident children in Lausanne, Switzerland.

SETTING: Ambulatory paediatric clinic in Lausanne, Switzerland, a country with a significant proportion of tuberculosis (TB) among immigrants. AIM: To assess the factors associated with positive tuberculin skin tests (TST) among children examined during a health check-up or during TB contact tracing, notably the influence of BCG vaccination (Bacille Calmette Guérin) and history of TB contact. METHOD: A descriptive study of children who had a TST (2 Units RT23) between November 2002 and April 2004. Age, sex, history of TB contact, BCG vaccination status, country of origin and birth outside Switzerland were recorded. RESULTS: Of 234 children, 176 (75%) had a reaction equal to zero and 31 (13%) tested positive (>10 mm). In a linear regression model, the size of the TST varied significantly according to the history of TB contact, age, TB incidence in the country of origin and BCG vaccination status but not according to sex or birth in or outside Switzerland. In a logistic regression model including all the recorded variables, age (Odds Ratio = 1.21, 95% CI 1.08; 1.35), a history of TB contact (OR = 7.31, 95% CI 2.23; 24) and the incidence of TB in the country of origin (OR = 1.01, 95% CI 1.00; 1.02) were significantly associated with a positive TST but sex (OR = 1.18, 95% CI 0.50; 2.78) and BCG vaccination status (OR = 2.97, 95% CI 0.91; 9.72) were not associated. CONCLUSIONS: TB incidence in the country of origin, BCG vaccination and age influence the TSTreaction (size or proportion of TST > or = 10 mm). However the most obvious risk factor for a positive TST is a history of contact with TB.

Treatment of severe infectious purpura in children with human plasma from donors immunized with Escherichia coli J5: a prospective double-blind study. J5 study Group.

To evaluate the efficacy of anti-J5 serum in the treatment of severe infectious purpura, 73 children were randomized to receive either anti-J5 (40) or control (33) plasma. Age, blood pressure, and biologic risk factors were similar in both groups. At admission, however, tumor necrosis factor serum concentrations were 974 +/- 173 pg/ml compared with 473 +/- 85 pg/ml (P = .023) and interleukin-6 serum concentrations were 129 +/- 45 compared with 19 +/- 5 ng/ml (P = .005) in the control and treated groups, respectively. The duration of shock and the occurrence of complications were similar in both groups. The mortality rate was 36% in the control group and 25% in the treated group (P = .317; odds ratio, 0.76; 95% confidence interval, 0.46-1.26). This trend disappeared after correction for unbalances in risk factors at randomization using a logistic regression model. These results suggest that anti-j5 plasma did not affect the course or mortality of severe infectious purpura in children.