Heterogeneity and event dependence in the analysis of sickness absence

Sickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultaneous analysis of event dependence and heterogeneity due to unknown, unmeasured, or unmeasurable factors. However, its use may encounter computational limitations when applied to very large data sets, as may frequently occur in the analysis of SA duration. To overcome the computational issue, we propose a Poisson-based conditional frailty model (CFPM) for repeated SA events that accounts for both event dependence and heterogeneity. To demonstrate the usefulness of the model proposed in the SA duration context, we used data from all non-work-related SA episodes that occurred in Catalonia (Spain) in 2007, initiated by either a diagnosis of neoplasm or mental and behavioral disorders. As expected, the CFPM results were very similar to those of the CFM for both diagnosis groups. The CPU time for the CFPM was substantially shorter than the CFM. The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events,especially with large databases.

Modelling Bone Mineral Density in Swiss Breast Cancer Patients Treated with Letrozole, Tamoxifen and Sequences of Letrozole and Tamoxifen in the BIG 1-98 Study (SAKK 21/07).

Background: Bone health is a concern when treating early stage breast cancer patients with adjuvant aromatase inhibitors. Early detection of patients (pts) at risk of osteoporosis and fractures may be helpful for starting preventive therapies and selecting the most appropriate endocrine therapy schedule. We present statistical models describing the evolution of lumbar and hip bone mineral density (BMD) in pts treated with tamoxifen (T), letrozole (L) and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1-98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years, B) L for 5 years, C) 2 years of T followed by 3 years of L and, D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection biases. Patients randomized to arm A were subsequently allowed an unplanned switch from T to L. Allowing for variations between DXA machines and centres, two repeated measures models, using a covariance structure that allow for different times between DXA, were used to estimate changes in hip and lumbar BMD (g/cm2) from trial randomization. Prospectively defined covariates, considered as fixed effects in the multivariable models in an intention to treat analysis, at the time of trial randomization were: age, height, weight, hysterectomy, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Similarly, the T-scores for lumbar and hip BMD measurements were modeled using a per-protocol approach (allowing for treatment switch in arm A), specifically studying the effect of each therapy upon T-score percentage. Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Number of DXA measurements per arm were; arm A 133, B 137, C 141 and D 135. The median follow-up time was 5.8 years. Significant factors positively correlated with lumbar and hip BMD in the multivariate analysis were weight, previous HRT use, neo-/adjuvant ChT, hysterectomy and height. Significant negatively correlated factors in the models were osteoporosis, treatment arm (B/C/D vs. A), time since endocrine therapy start, age and smoking (current vs. never).Modeling the T-score percentage, differences from T to L were -4.199% (p = 0.036) and -4.907% (p = 0.025) for the hip and lumbar measurements respectively, before any treatment switch occurred. Conclusions: Our statistical models describe the lumbar and hip BMD evolution for pts treated with L and/or T. The results of both localisations confirm that, contrary to expectation, the sequential schedules do not seem less detrimental for the BMD than L monotherapy. The estimated difference in BMD T-score percent is at least 4% from T to L.

Safety and Mobility Impacts of Winter Weather --Phase 3, SPR RB01-012, 2014

Highway agencies spend millions of dollars to ensure safe and efficient winter travel. However, the effectiveness of winter-weather maintenance practices on safety and mobility are somewhat difficult to quantify. Safety and Mobility Impacts of Winter Weather - Phase 1 investigated opportunities for improving traffic safety on state-maintained roads in Iowa during winter-weather conditions. In Phase 2, three Iowa Department of Transportation (DOT) high-priority sites were evaluated and realistic maintenance and operations mitigation strategies were also identified. In this project, site prioritization techniques for identifying roadway segments with the potential for safety improvements related to winter-weather crashes, were developed through traditional naïve statistical methods by using raw crash data for seven winter seasons and previously developed metrics. Additionally, crash frequency models were developed using integrated crash data for four winter seasons, with the objective of identifying factors that affect crash frequency during winter seasons and screening roadway segments using the empirical Bayes technique. Based on these prioritization techniques, 11 sites were identified and analyzed in conjunction with input from Iowa DOT district maintenance managers and snowplow operators and the Iowa DOT Road Weather Information System (RWIS) coordinator.

Outcome evaluation of ankle osteoarthritis treatments using spatio-temporal gait parameters and plantar pressure during unconstrained long distance walking : P25

Introduction: Ankle arthrodesis (AD) and total ankle replacement (TAR) are typical treatments for ankle osteoarthritis (AO). Despite clinical interest, there is a lack of their outcome evaluation using objective criteria. Gait analysis and plantar pressure assessment are appropriate to detect pathologies in orthopaedics but they are mostly used in lab with few gait cycles. In this study, we propose an ambulatory device based on inertial and plantar pressure sensors to compare the gait during long-distance trials between healthy subjects (H) and patients with AO or treated by AD and TAR. Methods: Our study included four groups: 11 patients with AO, 9 treated by TAR, 7 treated by AD and 6 control subjects. An ambulatory system (Physilog®, CH) was used for gait analysis; plantar pressure measurements were done using a portable insole (Pedar®-X, DE). The subjects were asked to walk 50 meters in two trials. Mean value and coefficient of variation of spatio-temporal gait parameters were calculated for each trial. Pressure distribution was analyzed in ten subregions of foot. All parameters were compared among the four groups using multi-level model-based statistical analysis. Results: Significant difference (p <0.05) with control was noticed for AO patients in maximum force in medial hindfoot and forefoot and in central forefoot. These differences were no longer significant in TAR and AD groups. Cadence and speed of all pathologic groups showed significant difference with control. Both treatments showed a significant improvement in double support and stance. TAR decreased variability in speed, stride length and knee ROM. Conclusions: In spite of a small sample size, this study showed that ankle function after AO treatments can be evaluated objectively based on plantar pressure and spatio-temporal gait parameters measured during unconstrained walking outside the lab. The combination of these two ambulatory techniques provides a promising way to evaluate foot function in clinics.

Protocol for a systematic review on the extent of non-publication of research studies and associated study characteristics.

BACKGROUND: Methodological research has found that non-published studies often have different results than those that are published, a phenomenon known as publication bias. When results are not published, or are published selectively based on the direction or the strength of the findings, healthcare professionals and consumers of healthcare cannot base their decision-making on the full body of current evidence. METHODS: As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:1. To determine the proportion and/or rate of non-publication of studies by systematically reviewing methodological research projects that followed up a cohort of studies that a. received research ethics committee (REC) approval,b. were registered in trial registries, orc. were presented as abstracts at conferences.2. To assess the association of study characteristics (for example, direction and/or strength of findings) with likelihood of full publication.To identify reports of relevant methodological research projects we will conduct electronic database searches, check reference lists, and contact experts. Published and unpublished projects will be included. The inclusion criteria are as follows:a. RECs: methodological research projects that examined the subsequent proportion and/or rate of publication of studies that received approval from RECs;b. Trial registries: methodological research projects that examine the subsequent proportion and/or rate of publication of studies registered in trial registries;c. Conference abstracts: methodological research projects that examine the subsequent proportion and/or rate of full publication of studies which were initially presented at conferences as abstracts.Primary outcomes: Proportion/rate of published studies; time to full publication (mean/median; cumulative publication rate by time).Secondary outcomes: Association of study characteristics with full publication.The different questions (a, b, and c) will be investigated separately. Data synthesis will involve a combination of descriptive and statistical summaries of the included methodological research projects. DISCUSSION: Results are expected to be publicly available in mid 2013.

A protocol for a systematic review on the impact of unpublished studies and studies published in the gray literature in meta-analyses.

BACKGROUND: Meta-analyses are particularly vulnerable to the effects of publication bias. Despite methodologists' best efforts to locate all evidence for a given topic the most comprehensive searches are likely to miss unpublished studies and studies that are published in the gray literature only. If the results of the missing studies differ systematically from the published ones, a meta-analysis will be biased with an inaccurate assessment of the intervention's effects.As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:â-ª To assess the impact of studies that are not published or published in the gray literature on pooled effect estimates in meta-analyses (quantitative measure).â-ª To assess whether the inclusion of unpublished studies or studies published in the gray literature leads to different conclusions in meta-analyses (qualitative measure). METHODS/DESIGN: Inclusion criteria: Methodological research projects of a cohort of meta-analyses which compare the effect of the inclusion or exclusion of unpublished studies or studies published in the gray literature.Literature search: To identify relevant research projects we will conduct electronic searches in Medline, Embase and The Cochrane Library; check reference lists; and contact experts.Outcomes: 1) The extent to which the effect estimate in a meta-analyses changes with the inclusion or exclusion of studies that were not published or published in the gray literature; and 2) the extent to which the inclusion of unpublished studies impacts the meta-analyses' conclusions.Data collection: Information will be collected on the area of health care; the number of meta-analyses included in the methodological research project; the number of studies included in the meta-analyses; the number of study participants; the number and type of unpublished studies; studies published in the gray literature and published studies; the sources used to retrieve studies that are unpublished, published in the gray literature, or commercially published; and the validity of the methodological research project.Data synthesis: Data synthesis will involve descriptive and statistical summaries of the findings of the included methodological research projects. DISCUSSION: Results are expected to be publicly available in the middle of 2013.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

Genetic variants influencing circulating lipid levels and risk of coronary artery disease.

OBJECTIVE: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). CONCLUSIONS: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.

Taxometric analysis of DSM-IV and DSM-5 alcohol use disorders.

BACKGROUND: With preparations currently being made for the Diagnostic and Statistical Manual of Mental Disorders-5th Edition (DSM-5), one prominent issue to resolve is whether alcohol use disorders are better represented as discrete categorical entities or as a dimensional construct. The purpose of this study was to investigate the latent structure of DSM-4th edition (DSM-IV) and proposed DSM-5 alcohol use disorders. METHODS: The study used the Wave 2 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) to conduct taxometric analyses of DSM-IV and DSM-5 alcohol use disorders defined by different thresholds to determine the taxonic or dimensional structure underlying the disorders. RESULTS: DSM-IV and DSM-5 alcohol abuse and dependence criteria with 3+ thresholds demonstrated a dimensional structure. Corresponding thresholds with 4+ criteria were clearly taxonic, as were thresholds defined by cut-offs of 5+ and 6+ criteria. CONCLUSIONS: DSM-IV and DSM-5 alcohol use disorders demonstrated a hybrid taxonic-dimensional structure. That is, DSM-IV and DSM-5 alcohol use disorders may be taxonically distinct compared to no disorder if defined by a threshold of 4 or more criteria. However, there may be dimensional variation remaining among non-problematic to subclinical cases. A careful and systematic program of structural research using taxometric and psychometric procedures is warranted.

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

The Alcohol Use Disorders Identification Test (AUDIT) as a screening tool for excessive drinking in primary care: reliability and validity of a French version.

BACKGROUND: Excessive drinking is a major problem in Western countries. AUDIT (Alcohol Use Disorders Identification Test) is a 10-item questionnaire developed as a transcultural screening tool to detect excessive alcohol consumption and dependence in primary health care settings. OBJECTIVES: The aim of the study is to validate a French version of the Alcohol Use Disorders Identification Test (AUDIT). METHODS: We conducted a validation cross-sectional study in three French-speaking areas (Paris, Geneva and Lausanne). We examined psychometric properties of AUDIT as its internal consistency, and its capacity to correctly diagnose alcohol abuse or dependence as defined by DSM-IV and to detect hazardous drinking (defined as alcohol intake >30 g pure ethanol per day for men and >20 g of pure ethanol per day for women). We calculated sensitivity, specificity, positive and negative predictive values and Receiver Operator Characteristic curves. Finally, we compared the ability of AUDIT to accurately detect "alcohol abuse/dependence" with that of CAGE and MAST. RESULTS: 1207 patients presenting to outpatient clinics (Switzerland, n = 580) or general practitioners' (France, n = 627) successively completed CAGE, MAST and AUDIT self-administered questionnaires, and were independently interviewed by a trained addiction specialist. AUDIT showed a good capacity to discriminate dependent patients (with AUDIT > or =13 for males, sensitivity 70.1%, specificity 95.2%, PPV 85.7%, NPV 94.7% and for females sensitivity 94.7%, specificity 98.2%, PPV 100%, NPV 99.8%); and hazardous drinkers (with AUDIT > or =7, for males sensitivity 83.5%, specificity 79.9%, PPV 55.0%, NPV 82.7% and with AUDIT > or =6 for females, sensitivity 81.2%, specificity 93.7%, PPV 64.0%, NPV 72.0%). AUDIT gives better results than MAST and CAGE for detecting "Alcohol abuse/dependence" as showed on the comparative ROC curves. CONCLUSIONS: The AUDIT questionnaire remains a good screening instrument for French-speaking primary care.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

In conspectu prope totius urbis: an application of different visual methods at the ager Tarraconensis landscape

We present in this paper the results of the application of several visual methods on a group of locations, dated between VI and I centuries BC, of the ager Tarraconensis (Tarragona, Spain) a Hinterland of the roman colony of Tarraco. The difficulty in interpreting the diverse results in a combined way has been resolved by means of the use of statistical methods, such as Principal Components Analysis (PCA) and K-means clustering analysis. These methods have allowed us to carry out site classifications in function of the landscape's visual structure that contains them and of the visual relationships that could be given among them.

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Oops! Another medication error : a literature review of contributing factors and methods to prevent medication errors

The purpose of this bachelor's thesis was to chart scientific research articles to present contributing factors to medication errors done by nurses in a hospital setting, and introduce methods to prevent medication errors. Additionally, international and Finnish research was combined and findings were reflected in relation to the Finnish health care system. Literature review was conducted out of 23 scientific articles. Data was searched systematically from CINAHL, MEDIC and MEDLINE databases, and also manually. Literature was analysed and the findings combined using inductive content analysis. Findings revealed that both organisational and individual factors contributed to medication errors. High workload, communication breakdowns, unsuitable working environment, distractions and interruptions, and similar medication products were identified as organisational factors. Individual factors included nurses' inability to follow protocol, inadequate knowledge of medications and personal qualities of the nurse. Developing and improving the physical environment, error reporting, and medication management protocols were emphasised as methods to prevent medication errors. Investing to the staff's competence and well-being was also identified as a prevention method. The number of Finnish articles was small, and therefore the applicability of the findings to Finland is difficult to assess. However, the findings seem to fit to the Finnish health care system relatively well. Further research is needed to identify those factors that contribute to medication errors in Finland. This is a necessity for the development of methods to prevent medication errors that fit in to the Finnish health care system.