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Results for “Bayesian modelling”

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At least 433 records · Page 24Linked to original sources

PubMed2005

Statistical modelling of the spatial distribution of prevalence of Calicophoron daubneyi infection in sheep from central Italy.

Statistical modelling for Disease Mapping and Ecological Analysis is of particular importance in veterinary parasitology because environmental characteristics can affect parasite distribution. However, the main difficulties relate to the concentration of animal populations within farms, which contrasts to the study of wild animal populations. In the present paper we report the results of a cross-sectional coprological survey designed to study the presence and distribution of the rumen fluke Calicophoron daubneyi--which causes paramphistomosis, a snail borne disease--in pastured sheep living in the Latina province of central Italy. We show how techniques derived from human epidemiology can be used to study the spatial distribution of parasite infection in animals. We proposed a hierarchical Bayesian model with random terms for unstructured variability (heterogeneity) to account for local farm characteristics and spatially structure terms (clustering) to cope with medium-large scale environmental characteristics.

Animal Husbandry↗

PubMed2006

Calcium:magnesium ratio in local groundwater and incidence of acute myocardial infarction among males in rural Finland.

Several epidemiologic studies have shown an association between calcium and magnesium and coronary heart disease mortality and morbidity. In this small-area study, we examined the relationship between acute myocardial infarction (AMI) risk and content of Ca, Mg, and chromium in local groundwater in Finnish rural areas using Bayesian modeling and geospatial data aggregated into 10 km times symbol 10 km grid cells. Data on 14,495 men 35-74 years of age with their first AMI in the years 1983, 1988, or 1993 were pooled. Geochemical data consisted of 4,300 measurements of each element in local groundwater. The median concentrations of Mg, Ca, and Cr and the Ca:Mg ratio in well water were 2.61 mg/L, 12.23 mg/L, 0.27 microg/L, and 5.39, respectively. Each 1 mg/L increment in Mg level decreased the AMI risk by 4.9%, whereas a one unit increment in the Ca:Mg ratio increased the risk by 3.1%. Ca and Cr did not show any statistically significant effect on the incidence and spatial variation of AMI. Results of this study with specific Bayesian statistical analysis support earlier findings of a protective role of Mg and low Ca:Mg ratio against coronary heart disease but do not support the earlier hypothesis of a protective role of Ca.

Adult↗

PubMed2001

Colour categorization by domestic chicks.

Spectral stimuli form a physical continuum, which humans divide into discrete non-overlapping regions or categories that are designated by colour names. Little is known about whether non-verbal animals form categories on stimulus continua, but work in psychology and artificial intelligence provides models for stimulus generalization and categorization. We compare predictions of such models to the way poultry chicks (Gallus gallus) generalize to novel stimuli following appetitive training to either one or two colours. If the two training colours are (to human eyes) red and greenish-yellow or green and blue, chicks prefer intermediates, i.e. orange rather than red or yellow and turquoise rather than green or blue. The level of preference for intermediate colours implies that the chicks interpolate between the training stimuli. However, they do not extrapolate beyond the limits set by the training stimuli, at least for red and yellow training colours. Similarly, chicks trained to red and blue generalize to purple, but they do not generalize across grey after training to the complementary colours yellow and blue. These results are consistent with a modified version of a Bayesian model of generalization from multiple examples that was proposed by Shepard and show similarities to human colour categorization.

Animals↗

PubMed2004

Geochemistry of ground water and the incidence of acute myocardial infarction in Finland.

STUDY OBJECTIVE: To examine the association of spatial variation in acute myocardial infarction (AMI) incidence and its putative environmental determinants in ground water such as total water hardness, the concentration of calcium, magnesium, fluoride, iron, copper, zinc, nitrate, and aluminium. DESIGN: Small area study using Bayesian modelling and the geo-referenced data aggregated into 10 km x 10 km cells. SETTING: The population data were obtained from Statistics Finland, AMI case data from the National Death Register and the Hospital Discharge Register, and the geochemical data from hydrogeochemical database of Geological Survey of Finland. PARTICIPANTS: A total of 18 946 men aged 35-74 years with the first AMI attack in the years 1983, 1988, and 1993. MAIN RESULTS: One unit (in German degree degrees dH) increment in water hardness decreased the risk of AMI by 1%. Geochemical elements in ground water included in this study did not show a statistically significant effect on the incidence and spatial variation of AMI, even though suggestive findings were detected for fluoride (protective), iron and copper (increasing). CONCLUSIONS: The results of this study with more specific Bayesian statistical analysis confirm findings from earlier observations of the inverse relation between water hardness and coronary heart disease. The role of environmental geochemistry in the geographical variation of the AMI incidence should be studied further in more detail incorporating the individual intake of both food borne and water borne nutrients. Geochemical-spatial analysis provides a basis for the selection of areas suitable for such research.

Adult↗

PubMed2002

Predicting time to prostate cancer recurrence based on joint models for non-linear longitudinal biomarkers and event time outcomes.

Biological markers that are both sensitive and specific for tumour regrowth or metastasis are increasingly becoming available and routinely monitored during the regular follow-up of patients treated for cancer. Obtained by a simple blood test, these markers provide an inexpensive non-invasive means for the early detection of recurrence (or progression). Currently, the longitudinal behaviour of the marker is viewed as an indicator of early disease progression, and is applied by a physician in making clinical decisions. One marker that has been studied for use in both population screening for early disease and for detection of recurrence in prostate cancer patients is PSA. The elevation of PSA levels is known to precede clinically detectable recurrence by 2 to 5 years, and current clinical practice often relies partially on multiple recent rises in PSA to trigger a change in treatment. However, the longitudinal trajectory for individual markers is often non-linear; in many cases there is a decline immediately following radiation therapy or surgery, a plateau during remission, followed by an exponential rise following the recurrence of the cancer. The aim of this article is to determine the multiple aspects of the longitudinal PSA biomarker trajectory that can be most sensitive for predicting time to clinical recurrence. Joint Bayesian models for the longitudinal measures and event times are utilized based on non-linear hierarchical models, implied by unknown change-points, for the longitudinal trajectories, and a Cox proportional hazard model for progression times, with functionals of the longitudinal parameters as covariates in the Cox model. Using Markov chain Monte Carlo sampling schemes, the joint model is fit to longitudinal PSA measures from 676 patients treated at Massachusetts General Hospital between the years 1988 and 1995 with follow-up to 1999. Based on these data, predictive schemes for detecting cancer recurrence in new patients based on their longitudinal trajectory are derived.

Bayes Theorem↗

PubMed2005

Acupuncture for tinnitus: a series of six n = 1 controlled trials.

OBJECTIVE: To explore patient perceived benefits of acupuncture for tinnitus. DESIGN: Controlled n=1 trials, with two phases A and B. SUBJECTS: Six patients with tinnitus. OUTCOME MEASURES: Primary outcome was Daily Diary records related to four tinnitus symptoms: loudness of tinnitus; pitch of tinnitus; waking hours affected with tinnitus; quality of sleep. Secondary outcomes were the Tinnitus Handicap Inventory (THI) and Measure Your Medical Outcome Profile (MYMOP). METHODS: Patients received a course of 10 acupuncture treatments over a 2-week period. Daily Diary entries related to the four tinnitus symptoms were recorded by patients for 14 days pre-treatment (phase A) and 14 days post-treatment (phase B). A hierarchical Bayesian model was used to combine the results from the individual patients to obtain estimates of the population and individual patient treatment effects, incorporating random variations at both levels (between patients and within patient). Tinnitus Handicap Inventory (THI) and Measure Your Medical Outcome Profile (MYMOP) were recorded at assessment points pre-treatment and post-treatment. RESULTS: Six patients participated in the trials, each receiving 10 treatments and completing all Daily Diary entries and outcome measures. For the of symptoms of loudness and pitch, there were variable treatment effects between patients, with a trend for the median overall reduction for loudness of -2.49 (-5.04, 0.02) and for pitch -1.39 (-3.74, 0.89), 95% credibility intervals being shown in brackets. For the other two symptoms, the waking hours affected and quality of sleep, patients' responses were more consistent, with amore credible overall median reduction for affected waking hours of -2.76 (-3.94, -1.63) and for quality of sleep -2.72 (-3.45, -2.03). The THI and MYMOP measures showed a trend of improvement after treatment. CONCLUSION: The n=1 trial methodology, with an AB design and Bayesian analysis, can be considered of value in exploring treatment effects for small numbers of patients receiving individualised treatments, as is common within complementary medicine. When the treatment effects from six patients were synthesized, the results of this study suggest that acupuncture may have a beneficial role in the treatment of tinnitus.

Acupuncture Therapy↗

PubMed2001

A new approach to dose escalation in non-small-cell lung cancer.

PURPOSE: To describe the radiobiological rationale for dose-per-fraction escalation in non-small-cell lung cancer (NSCLC) and to devise a novel Phase I scheme to implement this strategy using advanced radiotherapy delivery technologies. METHODS AND MATERIALS: The data from previous dose escalation trials in NSCLC are reanalyzed to establish a dose-response relationship in this disease. We also use data relating prolongation in treatment time to survival to compute the potential doubling time for lung tumors. On the basis of these results, and using a Bayesian model to determine the probability of pneumonitis as a function of mean normalized lung dose, a dose-per-fraction escalation strategy is developed. RESULTS: Standard approaches to dose escalation using 2 Gy per fraction, five fractions per week, require doses in excess of 85 Gy to achieve 50% long-term control rate. This is partly because NSCLCs repopulate rapidly, with a 1.6% per day loss in survival from prolongation in overall treatment time beyond 6 weeks, and a cell doubling time of only 2.5 to 3.3 days. A dose-per-fraction escalation strategy, with a constant number of fractions, 25, and overall time, 5 weeks, is projected to produce tumor control rates predicted to be 10%-15% better than 2 Gy per fraction dose escalation, with equivalent late effects. This Phase I clinical study is divided into three parts. Step 1 examines the feasibility of the maximum breath-holding technique and junctioning of tomotherapy slices. Step 2 treats 10 patients with 30 fractions of 2 Gy over 6 weeks and then reduces duration to 5 weeks using fewer but larger fractions in 10 patients. Step 3 will consist of a dose-per-fraction escalation study on roughly 50 patients, maintaining 25 fractions in 5 weeks. Bayesian methodology (a modification of the Continual Reassessment Method) will be used in Step 3 to allow consistent and efficient escalation within five volume bins. CONCLUSION: A dose-per-fraction escalation approach in NSCLC should yield superior outcomes, compared to standard dose escalation approaches using a fixed dose per fraction, for a given level of pneumonitis and late toxicity. Highly conformal radiotherapy techniques, such as intensity modulated radiotherapy (IMRT) and helical tomotherapy with its adaptive capabilities, will be necessary to achieve significant dose-per-fraction escalation without unacceptable lung and esophageal morbidity.

Carcinoma, Non-Small-Cell Lung↗

PubMed1999

Pharmacokinetics and milk discard times of pirlimycin after intramammary infusion: a population approach.

A population pharmacokinetic approach was used to analyse milk concentration data to determine whether milk discard times and the clearance of intramammary infusions of pirlimycin could be adequately predicted by readily available demographic variables. Milk samples were collected at 12 hourly milking intervals after dosing with pirlimycin during product development from both normal cows (primary data) and cows with naturally occurring mastitis (validation data) and pirlimycin concentration was determined by microbial inhibition assay. The data were analysed by the conditional estimation/ maximum likelihood population approach within the computer program PPharm and fitted a two compartment open model. Bayesian estimates of individual parameters allowed solutions for each cow, predicting the time after last dosing by which milk concentration reached the target safe concentration. From this population of times, the 95% confidence interval of the 99th percentile was defined as the milk discard time. After elimination of one very low producing outlier, the calculated discard time agreed with the label recommendation of 36 h (3 milkings, USA) after the last dose. Milk pirlimycin clearance was strongly and positively correlated to the logarithm of the kilograms of milk produced in 24 h at time of dosing (r2=0.939). Agreement was strong at most time points between predicted and measured pirlimycin concentrations in milk from cows with mastitis. This alternative method for determining milk discard times was compared to existing recommendations.

Animals↗

PubMed2001

A Bayesian method for finding regulatory segments in DNA.

A goal of the human genome project is to determine the entire sequence of DNA (3 x 10(9) base pairs) found in chromosomes. The massive amounts of data produced by this project require interpretation. A Bayesian model is developed for locating regulatory regions in a DNA sequence. Regulatory regions are areas of DNA to which specific proteins bind and control whether or not a gene is transcribed to produce templates for protein synthesis. Each human cell contains the same DNA sequence. Thus the particular function of different cells is determined by the genes that are transcribed in that cell. A Hidden Markov chain is used to model whether a small interval of the DNA is in a regulatory region or not. This can be regarded as a changepoint problem where the changepoints are the start of a regulatory or nonregulatory region. The data consists of protein-binding elements, which are short subsequences, or "words," in the DNA sequence. Although these words can occur anywhere in the sequence, a larger number are expected in regulatory regions. Therefore, regulatory regions are detected by locating clusters of words. For a particular DNA sequence, the model automatically selects those words that best predict regions of interest. Markov chain Monte Carlo methods are used to explore the posterior distribution of the Hidden Markov chain. The model is tested by means of simulations, and applied to several DNA sequences.

Bayes Theorem↗

PubMed2002

Empirical bayes methods and false discovery rates for microarrays.

In a classic two-sample problem, one might use Wilcoxon's statistic to test for a difference between treatment and control subjects. The analogous microarray experiment yields thousands of Wilcoxon statistics, one for each gene on the array, and confronts the statistician with a difficult simultaneous inference situation. We will discuss two inferential approaches to this problem: an empirical Bayes method that requires very little a priori Bayesian modeling, and the frequentist method of "false discovery rates" proposed by Benjamini and Hochberg in 1995. It turns out that the two methods are closely related and can be used together to produce sensible simultaneous inferences.

Bayes Theorem↗

PubMed2004

Algorithms for inferring haplotypes.

Haplotype phase information in diploid organisms provides valuable information on human evolutionary history and may lead to the development of more efficient strategies to identify genetic variants that increase susceptibility to human diseases. Molecular haplotyping methods are labor-intensive, low-throughput, and very costly. Therefore, algorithms based on formal statistical theories were shown to be very effective and cost-efficient for haplotype reconstruction. This review covers 1) population-based haplotype inference methods: Clark's algorithm, expectation-maximization (EM) algorithm, coalescence-based algorithms (pseudo-Gibbs sampler and perfect/imperfect phylogeny), and partition-ligation algorithm implemented by a fully Bayesian model (Haplotyper) or by EM (PLEM); 2) family-based haplotype inference methods; 3) the handling of genotype scoring uncertainties (i.e., genotyping errors and raw two-dimensional genotype scatterplots) in inferring haplotypes; and 4) haplotype inference methods for pooled DNA samples. The advantages and limitations of each algorithm are discussed. By using simulations based on empirical data on the G6PD gene and TNFRSF5 gene, I demonstrate that different algorithms have different degrees of sensitivity to various extents of population diversities and genotyping error rates. Future development of statistical algorithms for addressing haplotype reconstruction will resort more and more to ideas based on combinatorial mathematics, graphical models, and machine learning, and they will have profound impacts on population genetics and genetic epidemiology with the advent of the human HapMap.

Algorithms↗

PubMed2026

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Over 75 Alzheimer's disease (AD) and dementia-associated variants have been identified through genome-wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations remains unclear. We compared how PRS approaches differing in p-value thresholds, variant weights, and source ancestry perform in predicting dementia in 6338 African American, Chinese, Hispanic, and White individuals from the Multi-Ethnic Study of Atherosclerosis. We tested clumping and thresholding (C+T) methods with varying parameters against Bayesian approaches (PRS-CS, PRS-CSx). We compared the ability of each method to predict incident dementia in all participants and in groups stratified by self-reported race/ethnicity. We additionally analyzed performance across groups stratified by estimated proportion of non-Finnish European (NFE)-like ancestry. Including more variants does not improve performance. We found comparable associations between dementia and PRS when comparing a C+T method with only 15 SNPs and PRS derived from Bayesian models that include > 800,000 SNPs (HR5e-08 = 1.18, 95% CI: 1.08-1.28; HRCSx = 1.17, 95% CI: 1.07-1.27). The p < 5e-08 C+T method was more strongly associated with incident dementia in populations genetically dissimilar from the source data (HRlowNFE_5e-08 = 1.27, 95% CI: 1.08-1.50; HRlowNFE_CSx = 1.12, 95% CI: 0.94-1.33). More selective PRS models using genome-wide significant SNPs may be preferable for dementia prediction in diverse populations.

Aged↗

PubMed2003

The analysis of profile data--revisited.

We revisit a former problem that led to much commentary regarding a proposed use of testing whether profiles for several groups in a repeated measurement scenario were parallel. Here we review previous approaches and propose Bayesian model selection to indicate whether the profiles can be considered parallel and if so support an estimation procedure for the profile differences.

Analysis of Variance↗

PubMed2005

A hierarchical Bayesian birth cohort analysis from incomplete registry data: evaluating the trends in the age of onset of insulin-dependent diabetes mellitus (T1DM).

Childhood diabetes is one of the major non-communicable diseases in children under 15 years of age. It requires a life-long insulin treatment and may lead to serious complications. Along with the worldwide increase in the incidence several countries have recently reported a decreasing trend in the age of onset of the disease. The aim of this study is to analyse long-term data on the incidence of the childhood diabetes in Finland from the birth cohorts perspective. The annual incidence data were available for the period 1965--1996 which translates into 1951--1996 birth cohorts. Hence the data consist of completely and partially observed cohorts. Bayesian modelling was employed in the analysis. Several different priors and cohort combinations were tried in order to determine the sensitivity of the results. The cumulative birth cohort incidence of diabetes was determined to have an increasing average annual trend of 2.5 per cent. Although the average birth cohort-specific age of onset was estimated to have decreased slightly over the years of observation, the trend could be a result of random variation.

Adolescent↗

PubMedDate not supplied

Assessing tumour markers.

This paper explores the factors involved in assessing the value of a medical test in a given clinical situation. It examines the problems involved in designing studies to investigate the role for a tumour marker in differential diagnosis and patient monitoring. An overview is given, including a critical evaluation of the preliminary research, the laboratory assay technique and potential clinical problems. Some examples are given. Specific approaches to the analysis of monitoring data are outlined, including the application of a sequential Bayesian model. This is illustrated using data from patients in the Medical Research Council's series of studies on the tumour marker Carcinoembryonic antigen.

Carcinoembryonic Antigen↗

PubMedDate not supplied

Bayesian analysis of space-time variation in disease risk.

The analysis of variation of risk for a given disease in space and time is a key issue in descriptive epidemiology. When the data are scarce, maximum likelihood estimates of the area-specific risk and of its linear time-trend can be seriously affected by random variation. In this paper, we propose a Bayesian model in which both area-specific intercept and trend are modelled as random effects and correlation between them is allowed for. This model is an extension of that originally proposed for disease mapping. It is illustrated by the analysis of the cumulative prevalence of insulin dependent diabetes mellitus as observed at the military examination of 18-year-old conscripts born in Sardinia during the period 1936-1971. Data concerning the genetic differentiation of the Sardinian population are used to interpret the results.

Adolescent↗

PubMedDate not supplied

Spatial variation of natural radiation and childhood leukaemia incidence in Great Britain.

This paper describes an analysis of the geographical variation of childhood leukaemia incidence in Great Britain over a 15 year period in relation to natural radiation (gamma and radon). Data at the level of the 459 district level local authorities in England, Wales and regional districts in Scotland are analysed in two complementary ways: first, by Poisson regressions with the inclusion of environmental covariates and a smooth spatial structure; secondly, by a hierarchical Bayesian model in which extra-Poisson variability is modelled explicitly in terms of spatial and non-spatial components. From this analysis, we deduce a strong indication that a main part of the variability is accounted for by a local neighbourhood 'clustering' structure. This structure is furthermore relatively stable over the 15 year period for the lymphocytic leukaemias which make up the majority of observed cases. We found no evidence of a positive association of childhood leukaemia incidence with outdoor or indoor gamma radiation levels. There is no consistent evidence of any association with radon levels. Indeed, in the Poisson regressions, a significant positive association was only observed for one 5-year period, a result which is not compatible with a stable environmental effect. Moreover, this positive association became clearly non-significant when over-dispersion relative to the Poisson distribution was taken into account.

Air Pollution, Indoor↗

PubMed2005

Uncertainty in white matter fiber tractography.

In this work we address the uncertainty associated with fiber paths obtained in white matter fiber tractography. This uncertainty, which arises for example from noise and partial volume effects, is quantified using a Bayesian modeling framework. The theory for estimating the probability of a connection between two areas in the brain is presented, and a new model of the local water diffusion profile is introduced. We also provide a theorem that facilitates the estimation of the parameters in this diffusion model, making the presented method simple to implement.

Algorithms↗