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PubMed1975

[Methodological problems of clinical trials of psychotropic drugs (author's transl)].

Up to now, clinical studies only succeeded in differentiating between great categories of psychotropic drugs, but failed to prove finer differences of effects within these categories of substances. Two points of the testing-method are discussed: 1. problems which arise when rating pathological behaviour and 2. problems of sampling psychiatric patients. A great part of symptoms that clinicians and psychologists used to consider as relevant proved to be extremely rare. Total scores cannot be taken as a measure of the therapeutic effect, because they don't express adequately the degree of severity of the illness before and after treatment, and there is a symptom that is independent from the observer, i.e. the frequency of the symptom in different clinical pictures. The frequency is an inverse ratio to the specificity of the symptom. It is then argued that even in clinical studies, it would be possible to choose among the variety of descriptive symptoms those which fulfil requirements of the probabilistic test-model of Rasch and to take only those symptoms to characterize the degree of severity of psychic disturbance in trials with psychotropic drugs. Conclusions are then drawn from a study including three groups of physicians (specialists for internal diseases, psychiatrists and general practitioners): failure to differentiate between placebo and a Minor-Tranquilizer was not due to the inefficiency of the drug, but ought to be attributed to the lack of sharpness of the observations made by untrained judges. A significant difference between placebo and the Minor-Tranquilizer was yet found, but only in the group of psychiatrists. The comparison of the first 13 and the last 13 cases in the two remaining groups, however, reveals a learning process in the course of the study. The main problems of sampling are discussed, i.e.: the loss of information as a consequence of taking the mean in a group of psychiatric patients, the role of biological rhythms, which was hitherto insufficiently considered, and finally it is demonstrated in connection with two selected cases of depressive patients that enormous difference of psychophysiological responsiveness can be hidden behind very similar clinical pictures. It is pointed out that the existing research strategy is adjusted to great samples, which were composed on the basis of behavioral characteristics, and that it failed to differentiate subtle effects of psychotropic drugs. Only experiments involving a much greater display, which take into account all aspects of observation of the selected single cases and longitudinal studies can answer the question which is the right medicine for the right patient. Psychophysiological and biochemical methods have here priority over other methods.

Drug Evaluation↗
PubMed1986

Consequences of chemosensory phenomena for leukocyte chemotactic orientation.

The stochastic nature of cell surface receptor-ligand binding is known to limit the accuracy of detection of chemoattractant gradients by leukocytes, thus limiting the orientation ability that is crucial to the chemotactic response in host defense. The probabilistic cell orientation model of Lauffenburger is extended here to assess the consequences of recently discovered receptor phenomena: "down-regulation" of total surface receptor number, spatial asymmetry of surface receptors, and existence of a higher-affinity receptor subpopulation. In general, a reduction in orientation accuracy is predicted by inclusion of these phenomena. An orientation signal based on a simple model of chemosensory adaptation (i.e., a spatial difference in relative receptor occupancy) is found to be functionally different from the signal suggested by an experimental correlation (i.e., a spatial difference in absolute receptor occupancy). However, in the context of receptor "signal noise," the signal based on adaptation yields predictions in better qualitative agreement with the experimental orientation data of Zigmond. From this cell orientation model we can estimate the effective time-averaging period required for noise diminution to a level allowing orientation predictions to match observed levels. This time-averaging period presumably reflects the time constant for receptor signal transduction and locomotory response.

Animals↗
PubMed2004

One year outcomes and costs following a vertebral fracture.

Vertebral fractures are believed to be important predictors for future vertebral and other fractures, leading to at least a 4- to 5-fold increase in the risk of subsequent fractures. However, little is known about their associated near-term costs. The purpose of this study was to quantify the subsequent fracture and cost outcomes emanating from patients with an incident vertebral fracture. A probabilistic decision analysis model was developed to estimate the expected cost of all subsequent fractures. We ran Kaplan-Meier time-to-event models on placebo patients in risedronate's pivotal phase III clinical trial data to determine the cumulative incidence or probabilities of all fractures within one year of an incident vertebral fracture. Unit costs for health care payers in the USA and Sweden for vertebral, hip, other, and forearm/wrist fractures were multiplied by fracture probabilities to generate the expected costs of new fractures within one year of incident vertebral fractures. Our analysis found that that 26.1% of vertebral fracture patients with a mean age of 74 years refractured within 1 year (vertebral 17.4%; hip 3.6%; "other" 3.5%; forearm/wrist 1.6%). The calculated medical costs for those patients who refracture within 1 year was $5906 and 3670 euros for the USA and Sweden, respectively, while the weighted average cost across all patients (refracture and non-fracture) within a year of their incident fracture was $1541 (USA) and 958 euros (Sweden). These results suggest that therapies with proven, rapid efficacy may offer important economic value to healthcare payers, providers and patients.

Aged↗
PubMed2005

The context-tree kernel for strings.

We propose a new kernel for strings which borrows ideas and techniques from information theory and data compression. This kernel can be used in combination with any kernel method, in particular Support Vector Machines for string classification, with notable applications in proteomics. By using a Bayesian averaging framework with conjugate priors on a class of Markovian models known as probabilistic suffix trees or context-trees, we compute the value of this kernel in linear time and space while only using the information contained in the spectrum of the considered strings. This is ensured through an adaptation of a compression method known as the context-tree weighting algorithm. Encouraging classification results are reported on a standard protein homology detection experiment, showing that the context-tree kernel performs well with respect to other state-of-the-art methods while using no biological prior knowledge.

Algorithms↗
PubMed2005

Automated brain tissue assessment in the elderly and demented population: construction and validation of a sub-volume probabilistic brain atlas.

OBJECTIVES: To develop an automated imaging assessment tool that accommodates the anatomic variability of the elderly and demented population as well as the registration errors occurring during spatial normalization. METHODS: 20 subjects with Alzheimer's disease (AD), mild cognitive impairment, or normal cognition underwent MRI brain imaging and had their 3D volumetric datasets manually partitioned into 68 regions of interest (ROI) termed sub-volumes. Gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) voxel counts were then made in the subject's native space for comparison against automated volumetric measures within three sub-volume probabilistic atlas (SVPA) models. The three SVPAs were constructed using 12 parameter affine (12 p), 2nd order (2nd), and 6th order (6th) transforms derived from registering the manually partitioned scans into a Talairach compatible AD population-based target. The three SVPA automated measures were compared to the manually derived measures in the 20 subjects' native space with a "jack-knife" procedure in which each subject was assessed by an SVPA they did not contribute toward constructing. RESULTS: The mean left and right GM ratio (GM ratio = [GM + CSF] / CSF) "r values" for the 3 SVPAs compared to the manually derived ratios across the 68 ROIs were 0.85 for the 12p SVPA, 0.88 for the 2nd SVPA, and 0.89 for the 6th SVPA. The mean left and right WM ratio (WM ratio = [WM + CSF] / CSF) "r values" for the 3 SVPAs being 0.84 for the 12p SVPA, 0.86 for the 2nd SVPA, and 0.88 for the 6th SVPA. CONCLUSION: We have constructed, from an elderly and demented cohort, an automated brain volumetric tool that has excellent accuracy compared to a manual gold standard and is capable of regional hypothesis testing and individual patient assessment compared to a population.

Aged↗
PubMed1989

Appendicitis. The computer as a diagnostic tool.

At present there is no definitive test for appendicitis and no clear set of signs and symptoms, so that diagnosis is uncertain and probabilistic. A computer model for analyzing clinical data can improve physician accuracy in diagnosing appendicitis by assessing the outcome probabilities associated with the treatment options. Should a definitive test become available, the computer model will aid clinicians in determining when to test. Once our proposed model has been validated, it will not only improve physician decision-making, but also provide quality assurance feedback, generate reports for documentation, and compile a data base of many cases for study and reference.

Appendicitis↗
PubMed2000

Falsifying serial and parallel parsing models: empirical conundrums and an overlooked paradigm.

When the human parser encounters a local structural ambiguity, are multiple structures pursued (parallel or breadth-first parsing), or just a single preferred structure (serial or depth-first parsing)? This note discusses four important classes of serial and parallel models: simple limited parallel, ranked limited parallel, deterministic serial with reanalysis, and probabilistic serial with reanalysis. It is argued that existing evidence is compatible only with probabilistic serial-reanalysis models, or ranked parallel models augmented with a reanalysis component. A new class of linguistic structures is introduced on which the behavior of serial and parallel parsers diverge the most radically: multiple local ambiguities are stacked to increase the number of viable alternatives in the ambiguous region from two to eight structures. This paradigm may provide the strongest test yet for parallel models.

Humans↗
PubMedDate not supplied

The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants.

Because human activities impact the timing, location, and degree of pollutant exposure, they play a key role in explaining exposure variation. This fact has motivated the collection of activity pattern data for their specific use in exposure assessments. The largest of these recent efforts is the National Human Activity Pattern Survey (NHAPS), a 2-year probability-based telephone survey (n=9386) of exposure-related human activities in the United States (U.S.) sponsored by the U.S. Environmental Protection Agency (EPA). The primary purpose of NHAPS was to provide comprehensive and current exposure information over broad geographical and temporal scales, particularly for use in probabilistic population exposure models. NHAPS was conducted on a virtually daily basis from late September 1992 through September 1994 by the University of Maryland's Survey Research Center using a computer-assisted telephone interview instrument (CATI) to collect 24-h retrospective diaries and answers to a number of personal and exposure-related questions from each respondent. The resulting diary records contain beginning and ending times for each distinct combination of location and activity occurring on the diary day (i.e., each microenvironment). Between 340 and 1713 respondents of all ages were interviewed in each of the 10 EPA regions across the 48 contiguous states. Interviews were completed in 63% of the households contacted. NHAPS respondents reported spending an average of 87% of their time in enclosed buildings and about 6% of their time in enclosed vehicles. These proportions are fairly constant across the various regions of the U.S. and Canada and for the California population between the late 1980s, when the California Air Resources Board (CARB) sponsored a state-wide activity pattern study, and the mid-1990s, when NHAPS was conducted. However, the number of people exposed to environmental tobacco smoke (ETS) in California seems to have decreased over the same time period, where exposure is determined by the reported time spent with a smoker. In both California and the entire nation, the most time spent exposed to ETS was reported to take place in residential locations.

Adolescent↗
PubMedDate not supplied

Quantitative prediction of biodegradability, metabolite distribution and toxicity of stable metabolites.

An evaluation of the capability of organic chemicals to mineralize is an important factor to consider when assessing their fate in the environment. Microbial degradation can convert a toxic chemical into an innocuous one, and vice versa, or alter the toxicity of a chemical. Moreover, primary biodegradation can convert chemicals into stable products that can be difficult to mineralize. In this paper, we present some new results obtained on the basis of a recently developed probabilistic approach to modeling biodegradation based on microbial transformation pathways. The metabolic transformations and their hierarchy were calibrated by making use of the ready biodegradability data from the MITI-I test and expert knowledge for the most probable transformation pathways. A model was developed and integrated into an expert software system named CATABOL that is able to predict the probability of biodegradation of organic chemicals directly from their structure. CATABOL simulates the effects of microbial enzyme systems, generates the most plausible transformation pathways, and quantitatively predicts the persistence and toxicity of the biodegradation products. A subset of 300 organic chemicals were selected from Canada's Domestic Substances List and subjected to CATABOL to compare predicted properties of the parent chemicals with their respective first stable metabolite. The results show that most of the stable metabolites have a lower acute toxicity to fish and a lower bioaccumulation potential compared to the parent chemicals. In contrast, the metabolites appear to be generally more estrogenic than the parent chemicals.

Animals↗
PubMed2003

A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum- likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page: http://www.lirmm.fr/w3ifa/MAAS/.

Algorithms↗
PubMed2026

From genes to trajectories: mapping genetic influences on Huntington's disease progression.

MOTIVATION: There are many diseases with established genetic factors, such as Huntington's disease (HD), that are characterized by variable rates of progression. However, beyond the contribution of the known genetic factors - in this case the Huntingtin (HTT) gene - the impact of the full human genome on the natural progression of such diseases throughout a patient's life remains largely unknown. The increased availability of genome wide association (GWA) data in HD gene expansion carriers (HDGECs), combined with the clinical assessment scores on the same set of patients, has provided a perfect opportunity to assess the potentially broader genetic impact on the natural progression of HD. RESULTS: We present a genetics-driven, probabilistic disease progression model designed to identify and investigate the ways in which a range of genetic factors affect the natural progression of HD. When applied to a clinico-genomic HD dataset, our model identified several single nucleotide polymorphisms (SNPs) with previously unreported effects on disease progression that act at distinct stages and with varying magnitudes. This discovery may shed light on the potential mechanistic impact of previously unidentified genes on HD that may have implications for clinical management. As increasing amounts of GWA data become available more generally, we anticipate that this modeling framework will be broadly applicable to other diseases with strong genetic components. AVAILABILITY AND IMPLEMENTATION: The source code for IHDPM is available at https://github.com/BiomedSciAI/IHDPM.

Huntington Disease↗
PubMed2005

GMAP: a genomic mapping and alignment program for mRNA and EST sequences.

MOTIVATION: We introduce GMAP, a standalone program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing. RESULTS: On a set of human messenger RNAs with random mutations at a 1 and 3% rate, GMAP identified all splice sites accurately in over 99.3% of the sequences, which was one-tenth the error rate of existing programs. On a large set of human expressed sequence tags, GMAP provided higher-quality alignments more often than blat did. On a set of Arabidopsis cDNAs, GMAP performed comparably with GeneSeqer. In these experiments, GMAP demonstrated a several-fold increase in speed over existing programs. AVAILABILITY: Source code for gmap and associated programs is available at http://www.gene.com/share/gmap SUPPLEMENTARY INFORMATION: http://www.gene.com/share/gmap.

Algorithms↗
PubMed2005

A novel approach for clustering proteomics data using Bayesian fast Fourier transform.

MOTIVATION: Bioinformatics clustering tools are useful at all levels of proteomic data analysis. Proteomics studies can provide a wealth of information and rapidly generate large quantities of data from the analysis of biological specimens. The high dimensionality of data generated from these studies requires the development of improved bioinformatics tools for efficient and accurate data analyses. For proteome profiling of a particular system or organism, a number of specialized software tools are needed. Indeed, significant advances in the informatics and software tools necessary to support the analysis and management of these massive amounts of data are needed. Clustering algorithms based on probabilistic and Bayesian models provide an alternative to heuristic algorithms. The number of clusters (diseased and non-diseased groups) is reduced to the choice of the number of components of a mixture of underlying probability. The Bayesian approach is a tool for including information from the data to the analysis. It offers an estimation of the uncertainties of the data and the parameters involved. RESULTS: We present novel algorithms that can organize, cluster and derive meaningful patterns of expression from large-scaled proteomics experiments. We processed raw data using a graphical-based algorithm by transforming it from a real space data-expression to a complex space data-expression using discrete Fourier transformation; then we used a thresholding approach to denoise and reduce the length of each spectrum. Bayesian clustering was applied to the reconstructed data. In comparison with several other algorithms used in this study including K-means, (Kohonen self-organizing map (SOM), and linear discriminant analysis, the Bayesian-Fourier model-based approach displayed superior performances consistently, in selecting the correct model and the number of clusters, thus providing a novel approach for accurate diagnosis of the disease. Using this approach, we were able to successfully denoise proteomic spectra and reach up to a 99% total reduction of the number of peaks compared to the original data. In addition, the Bayesian-based approach generated a better classification rate in comparison with other classification algorithms. This new finding will allow us to apply the Fourier transformation for the selection of the protein profile for each sample, and to develop a novel bioinformatic strategy based on Bayesian clustering for biomarker discovery and optimal diagnosis.

Algorithms↗
PubMed2006

jpHMM at GOBICS: a web server to detect genomic recombinations in HIV-1.

Detecting recombinations in the genome sequence of human immunodeficiency virus (HIV-1) is crucial for epidemiological studies and for vaccine development. Herein, we present a web server for subtyping and localization of phylogenetic breakpoints in HIV-1. Our software is based on a jumping profile Hidden Markov Model (jpHMM), a probabilistic generalization of the jumping-alignment approach proposed by Spang et al. The input data for our server is a partial or complete genome sequence from HIV-1; our tool assigns regions of the input sequence to known subtypes of HIV-1 and predicts phylogenetic breakpoints. jpHMM is available online at http://jphmm.gobics.de/.

Genome, Viral↗
PubMed2004

Cost-effectiveness analysis of HLA B*5701 genotyping in preventing abacavir hypersensitivity.

OBJECTIVE: Abacavir, a human immunodeficiency virus-1 (HIV-1) nucleoside-analogue reverse transcriptase inhibitor, causes severe hypersensitivity in 4-8% of patients. HLA B*5701 is a known genetic risk factor for abacavir hypersensitivity in Caucasians. Our aim was to confirm the presence of this genetic factor in our patients, and to determine whether genotyping for HLA B*5701 would be a cost-effective use of healthcare resources. METHODS: Patients with and without abacavir hypersensitivity were identified from a UK HIV clinic. Patients were genotyped for HLA B*5701, and pooled data used for calculation of test characteristics. The cost-effectiveness analysis incorporated the cost of testing, cost of treating abacavir hypersensitivity, and the cost and selection of alternative antiretroviral regimens. A probabilistic decision analytic model (comparing testing versus no testing) was formulated and Monte Carlo simulations performed. RESULTS: Of the abacavir hypersensitive patients, six (46%) were HLA B*5701 positive, compared to five (10%) of the non-hypersensitive patients (odds ratio 7.9 [95% confidence intervals 1.5-41.4], P = 0.006). Pooling of our data on HLA B*5701 with published data resulted in a pooled odds ratio of 29 (95% CI 6.4-132.3; P < 0.0001). The cost-effectiveness model demonstrated that depending on the choice of comparator, routine testing for HLA B*5701 ranged from being a dominant strategy (less expensive and more beneficial than not testing) to an incremental cost-effectiveness ratio (versus no testing) of Euro 22,811 per hypersensitivity reaction avoided. CONCLUSIONS: Abacavir hypersensitivity is associated with HLA B*5701, and pre-prescription pharmacogenetic testing for this appears to be a cost-effective use of healthcare resources.

Adult↗
PubMed2003

Distribution of arsenic and copper in sediment pore water: an ecological risk assessment case study for offshore drilling waste discharges.

Due to the hydrophobic nature of synthetic based fluids (SBFs), drilling cuttings are not very dispersive in the water column and settle down close to the disposal site. Arsenic and copper are two important toxic heavy metals, among others, found in the drilling waste. In this article, the concentrations of heavy metals are determined using a steady state "aquivalence-based" fate model in a probabilistic mode. Monte Carlo simulations are employed to determine pore water concentrations. A hypothetical case study is used to determine the water quality impacts for two discharge options: 4% and 10% attached SBFs, which correspond to the best available technology option and the current discharge practice in the U.S. offshore. The exposure concentration (CE) is a predicted environmental concentration, which is adjusted for exposure probability and bioavailable fraction of heavy metals. The response of the ecosystem (RE) is defined by developing an empirical distribution function of predicted no-effect concentration. The pollutants' pore water concentrations within the radius of 750 m are estimated and cumulative distributions of risk quotient (RQ=CE/RE) are developed to determine the probability of RQ greater than 1.

Arsenic↗
PubMed2006

Patient-centred and professional-directed implementation strategies for diabetes guidelines: a cluster-randomized trial-based cost-effectiveness analysis.

AIMS: Economic evaluations of diabetes interventions do not usually include analyses on effects and cost of implementation strategies. This leads to optimistic cost-effectiveness estimates. This study reports empirical findings on the cost-effectiveness of two implementation strategies compared with usual hospital outpatient care. It includes both patient-related and intervention-related cost. PATIENTS AND METHODS: In a clustered-randomized controlled trial design, 13 Dutch general hospitals were randomly assigned to a control group, a professional-directed or a patient-centred implementation programme. Professionals received feedback on baseline data, education and reminders. Patients in the patient-centred group received education and diabetes passports. A validated probabilistic Dutch diabetes model and the UKPDS risk engine are used to compute lifetime disease outcomes and cost in the three groups, including uncertainties. RESULTS: Glycated haemoglobin (HbA(1c)) at 1 year (the measure used to predict diabetes outcome changes over a lifetime) decreased by 0.2% in the professional-change group and by 0.3% in the patient-centred group, while it increased by 0.2% in the control group. Costs of primary implementation were < 5 Euro per head in both groups, but average lifetime costs of improved care and longer life expectancy rose by 9389 Euro and 9620 Euro, respectively. Life expectancy improved by 0.34 and 0.63 years, and quality-adjusted life years (QALY) by 0.29 and 0.59. Accordingly, the incremental cost per QALY was 32 218 Euro for professional-change care and 16 353 for patient-centred care compared with control, and 881 Euro for patient-centred vs. professional-change care. Uncertainties are presented in acceptability curves: above 65 Euro per annum the patient-directed strategy is most likely the optimum choice. CONCLUSION: Both guideline implementation strategies in secondary care are cost-effective compared with current care, by Dutch standards, for these patients. Additional annual costs per patient using patient passports are low. This analysis supports patient involvement in diabetes in the Netherlands, and probably also in other Western European settings.

Aged↗
PubMed2006

Interference phenomena in temporal evolution of accident probability in workplaces.

The aim of this article is to investigate some implications of complexity in workplace risk assessment. Workplace is examined as a complex system, and some of its attributes and aspects of its behavior are investigated. Failure probability of various workplace elements is examined as a time variable and interference phenomena of these probabilities are presented. Potential inefficiencies of common perceptions in applying probabilistic risk assessment models are also discussed. This investigation is conducted through mathematical modeling and qualitative examples of workplace situations. A mathematical model for simulation of the evolution of workplace accident probability in time is developed. Its findings are then attempted to be translated in real-world terms and discussed through simple examples of workplace situations. The mathematical model indicates that workplace is more likely to exhibit an unpredictable behavior. Such a behavior raises issues about usual key assumptions for the workplace, such as aggregation. Chaotic phenomena (nonlinear feedback mechanisms) are also investigated for in simple workplace systems cases. The main conclusions are (1) that time is an important variable for risk assessment, since behavior patterns are complex and unpredictable in the long term and (2) that workplace risk identification should take place in a holistic view (not by work post).

Accidents↗