Biomedical subjects

D B Dunson

Publications and source records attributed to D B Dunson.

At least 19 recordsLinked to original sources

PubMed2004

Bayesian modeling of multiple lesion onset and growth from interval-censored data.

In studying rates of occurrence and progression of lesions (or tumors), it is typically not possible to obtain exact onset times for each lesion. Instead, data consist of the number of lesions that reach a detectable size between screening examinations, along with measures of the size/severity of individual lesions at each exam time. This interval-censored data structure makes it difficult to properly adjust for the onset time distribution in assessing covariate effects on rates of lesion progression. This article proposes a joint model for the multiple lesion onset and progression process, motivated by cross-sectional data from a study of uterine leiomyoma tumors. By using a joint model, one can potentially obtain more precise inferences on rates of onset, while also performing onset time-adjusted inferences on lesion severity. Following a Bayesian approach, we propose a data augmentation Markov chain Monte Carlo algorithm for posterior computation.

Adult↗

PubMed2001

Antiretroviral therapy effects on genetic and morphologic end points in lymphocytes and sperm of men with human immunodeficiency virus infection.

Many human immunodeficiency virus (HIV)-infected persons receive prolonged treatment with DNA-reactive antiretroviral drugs. A prospective study was conducted of 26 HIV-infected men who provided samples before treatment and at multiple times after beginning treatment, to investigate effects of antiretrovirals on lymphocyte and sperm chromosomes and semen quality. Several antiretroviral regimens, all including a nucleoside component, were used. Lymphocyte metaphase analysis and sperm fluorescence in situ hybridization were used for cytogenetic studies. Semen analyses included conventional parameters (volume, concentration, viability, motility, and morphology). No significant effects on cytogenetic parameters, semen volume, or sperm concentration were detected. However, there were significant improvements in sperm motility for men with study entry CD4 cell counts >200 cells/mm(3), sperm morphology for men with entry CD4 cell counts < or =200 cells/mm(3), and the percentage of viable sperm in both groups. These findings suggest that nucleoside-containing antiretrovirals administered via recommended protocols do not induce chromosomal changes in lymphocytes or sperm but may produce improvements in semen quality.

Adult↗

PubMed2001

Commentary: practical advantages of Bayesian analysis of epidemiologic data.

In the past decade, there have been enormous advances in the use of Bayesian methodology for analysis of epidemiologic data, and there are now many practical advantages to the Bayesian approach. Bayesian models can easily accommodate unobserved variables such as an individual's true disease status in the presence of diagnostic error. The use of prior probability distributions represents a powerful mechanism for incorporating information from previous studies and for controlling confounding. Posterior probabilities can be used as easily interpretable alternatives to p values. Recent developments in Markov chain Monte Carlo methodology facilitate the implementation of Bayesian analyses of complex data sets containing missing observations and multidimensional outcomes. Tools are now available that allow epidemiologists to take advantage of this powerful approach to assessment of exposure-disease relations.

Bayes Theorem↗

PubMed2001

Topical and oral administration of the natural water-soluble antioxidant from spinach reduces the multiplicity of papillomas in the Tg.AC mouse model.

The Tg.AC mouse carrying the v-Ha-ras structural gene is a useful model for the study of chemical carcinogens, especially those acting via non-genotoxic mechanisms. This study evaluated the efficacy of the non-toxic, water-soluble antioxidant from spinach, natural antioxidant (NAO), in reducing skin papilloma induction in female hemizygous Tg.AC mice treated dermally five times over 2.5 weeks with 2.5 microg 12-O-tetradecanoylphorbol-13-acetate (TPA). The TPA-only group was considered as a control; the other two groups received, additionally, NAO topically (2 mg) or orally (100 mg/kg), 5 days/week for 5 weeks. Papilloma counts made macroscopically during the clinical observations showed a significant decrease in multiplicity (P<0.01) in the NAO topically treated group. According to histological criteria, papilloma multiplicity were lower in both topical-NAO and oral-NAO groups, but significantly so only in the oral-NAO mice (P<0.01). The beneficial effect of NAO in the Tg.AC mouse is reported.

Administration, Cutaneous↗

PubMed2001

Assessing human fertility using several markers of ovulation.

In modelling human fertility one ideally accounts for timing of intercourse relative to ovulation. Measurement error in identifying the day of ovulation can bias estimates of fecundability parameters and attenuate estimates of covariate effects. In the absence of a single perfect marker of ovulation, several error prone markers are sometimes obtained. In this paper we propose a semi-parametric mixture model that uses multiple independent markers of ovulation to account for measurement error. The model assigns each method of assessing ovulation a distinct non-parametric error distribution, and corrects bias in estimates of day-specific fecundability. We use a Monte Carlo EM algorithm for joint estimation of (i) the error distribution for the markers, (ii) the error-corrected fertility parameters, and (iii) the couple-specific random effects. We apply the methods to data from a North Carolina fertility study to assess the magnitude of error in measures of ovulation based on urinary luteinizing hormone and metabolites of ovarian hormones, and estimate the corrected day-specific probabilities of clinical pregnancy. Published in 2001 by John Wiley & Sons, Ltd.

Algorithms↗

PubMed2001

Likelihood of conception with a single act of intercourse: providing benchmark rates for assessment of post-coital contraceptives.

Emergency post-coital contraceptives effectively reduce the risk of pregnancy, but their degree of efficacy remains uncertain. Measurement of efficacy depends on the pregnancy rate without treatment, which cannot be measured directly. We provide indirect estimates of such pregnancy rates, using data from a prospective study of 221 women who were attempting to conceive. We previously estimated the probability of pregnancy with an act of intercourse relative to ovulation. In this article, we extend these data to estimate the probability of pregnancy relative to intercourse on a given cycle day (counting from onset of previous menses). In assessing the efficacy of post-coital contraceptives, other approaches have not incorporated accurate information on the variability of ovulation. We find that the possibility of late ovulation produces a persistent risk of pregnancy even into the sixth week of the cycle. Post-coital contraceptives may be indicated even when intercourse has occurred late in the cycle.

Coitus↗

PubMed2001

Modelling multiple ovulation, fertilization, and embryo loss in human fertility studies.

Models of human fertility that incorporate information on timing of intercourse have assumed that a single ovum is released each menstrual cycle. These models are misspecified if two or more viable ova are sometimes released in a single cycle, which is known to occur in dizygotic twin pregnancies. In this paper, we propose a model for multiple ovulation in humans. We assume that the unobservable number of viable ova in each cycle follows a multinomial distribution. Successful fertilization of each ovum depends on the ability of the cycle to support a pregnancy and on the aggregate of a set of unobservable Bernoulli trials representing the fertilizing effects of intercourse on various days. Our model accommodates general covariate effects, allows for heterogeneity among couples, and accounts for a sterile subpopulation of couples. Information on early detection of pregnancy can be incorporated to estimate the probability of embryo loss. We outline a Markov chain Monte Carlo algorithm for estimation of the posterior distributions of the parameters. The methods are applied to data from a North Carolina pregnancy study, and applications to studies of assisted reproduction are described.

Journal Article↗

PubMed2001

The relationship between cervical secretions and the daily probabilities of pregnancy: effectiveness of the TwoDay Algorithm.

BACKGROUND: The TwoDay Algorithm is a simple method for identifying the fertile window. It classifies a day as fertile if cervical secretions are present on that day or were present on the day before. This approach may be an effective alternative to the ovulation and symptothermal methods for populations and programmes that find current natural family planning methods difficult to implement. METHODS: We used data on secretions from a large multinational European fecundability study to assess the relationship between the days predicted to be potentially fertile by the TwoDay Algorithm and the day-specific probabilities of pregnancy based on intercourse patterns in 434 conception cycles from the study. RESULTS: The days around ovulation that had the highest fecundability were the days most likely to be classified as fertile by the TwoDay Algorithm. In addition, intercourse on a particular day in the fertile interval was twice as likely to result in a pregnancy if cervical secretions were present on that day or the day before. CONCLUSIONS: The TwoDay Algorithm is effective, both in identifying the fertile days of the cycle and in predicting days within the fertile interval that have a high pregnancy rate. Our data provide the first direct evidence that cervical secretions are associated with higher fecundability within the fertile window.

Algorithms↗

PubMed2001

Factor analytic models of clustered multivariate data with informative censoring.

This article describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censoring process, and we account for dependency between these latent variables through a hierarchical model. A linear model is used to relate covariates and latent variables to the primary outcomes for each subunit. A generalized linear model accounts for covariate and latent variable effects on the probability of censoring for subunits within each cluster. The model accounts for correlation within clusters and within subunits through a flexible factor analytic framework that allows multiple latent variables and covariate effects on the latent variables. The structure of the model facilitates implementation of Markov chain Monte Carlo methods for posterior estimation. Data from a spermatotoxicity study are analyzed to illustrate the proposed approach.

Animals↗

PubMed2001

A flexible parametric model for combining current status and age at first diagnosis data.

In some cross-sectional studies of chronic disease, data consist of the age at examination, whether the disease was present at the exam, and recall of the age at first diagnosis. This article describes a flexible parametric approach for combining current status and age at first diagnosis data. We assume that the log odds of onset by a given age and of detection by a given age conditional on onset by that age are nondecreasing functions of time plus linear combinations of covariates. Piecewise linear models are used to characterize changes across time in the baseline odds. Methods are described for accommodating informatively missing current status data and inferences based on the age-specific incidence of disease prior to a landmark event (e.g., puberty, menopause). Our formulation enables straightforward maximum likelihood estimation without requiring restrictive parametric or Markov assumptions. The methods are applied to data from a study of uterine fibroids.

Adult↗

PubMed2001

Bayesian modeling of the level and duration of fertility in the menstrual cycle.

Time to pregnancy studies that identify ovulation days and collect daily intercourse data can be used to estimate the day-specific probabilities of conception given intercourse on a single day relative to ovulation. In this article, a Bayesian semiparametric model is described for flexibly characterizing covariate effects and heterogeneity among couples in daily fecundability. The proposed model is characterized by the timing of the most fertile day of the cycle relative to ovulation, by the probability of conception due to intercourse on the most fertile day, and by the ratios of the daily conception probabilities for other days of the cycle relative to this peak probability. The ratios are assumed to be increasing in time to the peak and decreasing thereafter. Generalized linear mixed models are used to incorporate covariate and couple-specific effects on the peak probability and on the day-specific ratios. A Markov chain Monte Carlo algorithm is described for posterior estimation, and the methods are illustrated through application to caffeine data from a North Carolina pregnancy study.

Algorithms↗

PubMed2000

Accounting for unreported and missing intercourse in human fertility studies.

In prospective studies of human fertility that attempt to identify days of ovulation, couples record each day whether they had intercourse. Depending on the design of the study, couples either (I) mark the dates of intercourse on a chart or (II) mark 'yes' or 'no' for each day of the menstrual cycle. If protocol I is used, intercourse dates that couples fail to record are indistinguishable from dates of no intercourse. Consequently, estimates of day-specific fecundability are biased upwards. If protocol II is used, data from menstrual cycles with missing intercourse information must be discarded in order to fit current fertility models. We propose methods to account for unreported and missing intercourse under the assumption that the missingness mechanism is independent of time conditional on the unobservable true intercourse status. We use probit mixture models to allow for heterogeneity among couples, both in fecundability and in the missingness and non-reporting mechanisms. Markov chain Monte Carlo (MCMC) techniques are used for Bayesian estimation. The methods are generally applicable to the analysis of aggregated Bernoulli outcomes when there is uncertainty in whether a given trial, out of a series of trials, was completed. We illustrate the methods by application to two prospective fertility studies. Published in 2000 by John Wiley & Sons, Ltd.

Algorithms↗

PubMed2000

Bayesian analysis of mutational spectra.

Studies that examine both the frequency of gene mutation and the pattern or spectrum of mutational changes can be used to identify chemical mutagens and to explore the molecular mechanisms of mutagenesis. In this article, we propose a Bayesian hierarchical modeling approach for the analysis of mutational spectra. We assume that the total number of independent mutations and the numbers of mutations falling into different response categories, defined by location within a gene and/or type of alteration, follow binomial and multinomial sampling distributions, respectively. We use prior distributions to summarize past information about the overall mutation frequency and the probabilities corresponding to the different mutational categories. These priors can be chosen on the basis of data from previous studies using an approach that accounts for heterogeneity among studies. Inferences about the overall mutation frequency, the proportions of mutations in each response category, and the category-specific mutation frequencies can be based on posterior distributions, which incorporate past and current data on the mutant frequency and on DNA sequence alterations. Methods are described for comparing groups and for assessing dose-related trends. We illustrate our approach using data from the literature.

Animals↗

PubMed2000

Statistical analysis of skin tumor data from Tg.AC mouse bioassays.

New strategies for identifying chemical carcinogens and assessing risk have been proposed based on the Tg.AC (zetaglobin promoted v-Ha-ras) transgenic mouse. Preliminary studies suggest that the Tg. AC mouse bioassay may be an effective means of quickly evaluating the carcinogenic potential of a test agent. The skin of the Tg.AC mouse is genetically initiated, and the induction of epidermal papillomas in response to dermal or oral exposure to a chemical agent acts as a reporter phenotype of the activity of the test chemical. In Tg.AC mouse bioassays, the test agent is typically applied topically for up to 26 weeks, and the number of papillomas in the treated area is counted weekly. Statistical analyses are complicated by within-animal and serial dependency in the papilloma counts, survival differences between animals, and missing data. In this paper, we describe a statistical model for the analysis of skin tumor data from a Tg.AC mouse bioassay. The model separates effects on papilloma latency and multiplicity and accommodates important features of the data, including variability in expression of the transgene and dependency in the tumor counts. Methods are described for carcinogenicity testing and risk assessment. We illustrate our approach using data from a study of the effect of 2,3,7, 8-tetrachlorodibenzo-p-dioxin (TCDD) exposure on tumorigenesis.

Administration, Topical↗

PubMed2000

Assessing overall risk in reproductive experiments.

Toxicologists are often interested in assessing the joint effect of an exposure on multiple reproductive endpoints, including early loss, fetal death, and malformation. Exposures that occur prior to mating or extremely early in development can adversely affect the number of implantation sites or fetuses that form within each dam and may even prevent pregnancy. A simple approach for assessing overall adverse effects in such studies is to consider fetuses or implants that fail to develop due to exposure as missing data. The missing data can be imputed, and standard methods for the analysis of quantal response data can then be used for quantitative risk assessment or testing. In this article, a new bias-corrected imputation procedure is proposed and evaluated. The procedure is straightforward to implement in standard statistical packages and has excellent operating characteristics when used in combination with a marginal model fit with generalized estimating equations. The methods are applied to data from a reproductive toxicity study of Nitrofurazone conducted by the National Toxicology Program.

Abnormalities, Drug-Induced↗

PubMed2000

Modeling human fertility in the presence of measurement error.

The probability of conception in a given menstrual cycle is closely related to the timing of intercourse relative to ovulation. Although commonly used markers of time of ovulation are known to be error prone, most fertility models assume the day of ovulation is measured without error. We develop a mixture model that allows the day to be misspecified. We assume that the measurement errors are i.i.d. across menstrual cycles. Heterogeneity among couples in the per cycle likelihood of conception is accounted for using a beta mixture model. Bayesian estimation is straightforward using Markov chain Monte Carlo techniques. The methods are applied to a prospective study of couples at risk of pregnancy. In the absence of validation data or multiple independent markers of ovulation, the identifiability of the measurement error distribution depends on the assumed model. Thus, the results of studies relating the timing of intercourse to the probability of conception should be interpreted cautiously.

Algorithms↗

PubMed2000

Distinguishing effects on tumor multiplicity and growth rate in chemoprevention experiments.

In some types of cancer chemoprevention experiments and short-term carcinogenicity bioassays, the data consist of the number of observed tumors per animal and the times at which these tumors were first detected. In such studies, there is interest in distinguishing between treatment effects on the number of tumors induced by a known carcinogen and treatment effects on the tumor growth rate. Since animals may die before all induced tumors reach a detectable size, separation of these effects can be difficult. This paper describes a flexible parametric model for data of this type. Under our model, the tumor detection times are realizations of a delayed Poisson process that is characterized by the age-specific tumor induction rate and a random latency interval between tumor induction and detection. The model accommodates distinct treatment and animal-specific effects on the number of induced tumors (multiplicity) and the time to tumor detection (growth rate). A Gibbs sampler is developed for estimation of the posterior distributions of the parameters. The methods are illustrated through application to data from a breast cancer chemoprevention experiment.

9,10-Dimethyl-1,2-benzanthracene↗

PubMed1999

Day-specific probabilities of clinical pregnancy based on two studies with imperfect measures of ovulation.

Two studies have related the timing of sexual intercourse (relative to ovulation) to day-specific fecundability. The first was a study of Catholic couples practising natural family planning in London in the 1950s and 1960s and the second was of North Carolina couples attempting to become pregnant in the early 1980s. The former identified ovulation based on the ovulatory shift in the basal body temperature, while the latter used urinary assays of hormones. We use a statistical model to correct for error in identifying ovulation and to re-estimate the length of the fertile window and day-specific fecundabilities. We estimate the same 6-day fertile interval in both studies after controlling for error. After adjusting for error both data sets showed the highest estimate of the probability of pregnancy on the day prior to ovulation and both fell close to zero after ovulation. Given that the fertile interval is before ovulation, methods that anticipate ovulation by several days (such as the assessment of cervical mucus) would be particularly useful for couples who want to time their intercourse either to avoid or facilitate conception.

Adult↗