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Biomedical subjects

David B Dunson

Publications and source records attributed to David B Dunson.

At least 19 recordsLinked to original sources
PubMed2006

Association of physical activity with development of uterine leiomyoma.

The relation between physical activity and uterine leiomyomata (fibroids) has received little study, but exercise is protective for breast cancer, another hormonally mediated tumor. Participants in this study were randomly selected members of a health plan based in Washington, DC, aged 35-49 years (734 African Americans, 455 Whites) enrolled between 1996 and 1999. Fibroid status was based on ultrasound screening. Physical activity was based on detailed interview questions. Logistic regression with adjustment for body mass index and other risk factors showed that women in the highest category of physical activity were significantly less likely to have fibroids (odds ratio = 0.6, 95% confidence interval = 0.4, 0.9 for the highest vs. the lowest category (equivalent to approximately > or =7 hours/week vs <2 hours/week)). There was a dose-response pattern; a significant trend was seen for both African-American and White women. A multistate Bayesian analysis indicated that exercise was associated with tumor onset more strongly than with tumor growth. When data for women who reported major fibroid-related symptoms were excluded, results remained essentially unchanged, suggesting that the observed association could not be attributed to reverse causation (fibroids preventing exercise). The authors concluded that regular exercise might help women prevent fibroids.

Adolescent↗
PubMed2006

Bayesian dynamic modeling of latent trait distributions.

Studies of latent traits often collect data for multiple items measuring different aspects of the trait. For such data, it is common to consider models in which the different items are manifestations of a normal latent variable, which depends on covariates through a linear regression model. This article proposes a flexible Bayesian alternative in which the unknown latent variable density can change dynamically in location and shape across levels of a predictor. Scale mixtures of underlying normals are used in order to model flexibly the measurement errors and allow mixed categorical and continuous scales. A dynamic mixture of Dirichlet processes is used to characterize the latent response distributions. Posterior computation proceeds via a Markov chain Monte Carlo algorithm, with predictive densities used as a basis for inferences and evaluation of model fit. The methods are illustrated using data from a study of DNA damage in response to oxidative stress.

Algorithms↗
PubMed2006

Luteinizing hormone in premenopausal women may stimulate uterine leiomyomata development.

OBJECTIVE: Human chorionic gonadotropin (hCG) has proliferative effects on uterine smooth muscle and leiomyoma tissue in vitro. We hypothesized that luteinizing hormone (LH) would have the same effect by activating the LH/hCG receptor, and it would follow that premenopausal women with higher basal LH levels would be more likely to have leiomyomata. METHODS: Randomly selected women, aged 35 to 49 years, from a prepaid health plan were screened for leiomyomata with pelvic ultrasound. Urine samples collected during the first or last 5 days of the menstrual cycle were analyzed for LH by immunofluorometric assay, and concentrations were corrected for creatinine (n = 523). Logistic regression and Bayes analyses were used to evaluate the association of LH with presence and size of leiomyomata, adjusting for age, and other risk factors. RESULTS: Women with higher LH were more likely to have leiomyomata (adjusted odds ratios for second and third tertiles were 1.7 and 2.0 compared with lower tertile; 95% confidence intervals, 1.0 to 2.7 and 1.2 to 3.4, respectively). The association was stronger for large leiomyomata. Bayes analyses designed to estimate LH effects on tumor onset separately from tumor growth showed significantly accelerated tumor onset but little evidence of effects on tumor growth. Age, an independent risk factor for leiomyomata, was not affected by inclusion of LH in the logistic models. CONCLUSIONS: As hypothesized, women with higher LH were more likely to have leiomyomata, but this did not explain the age-related increase in leiomyomata during perimenopausal ages. Determining whether LH is causal or a marker for susceptibility will require further research.

Adult↗
PubMed2006

Bayesian selection of predictors of conception probabilities across the menstrual cycle.

There is increasing interest in identifying predictors of human fertility, including environmental exposures, behavioural factors, and biomarkers, such as mucus or reproductive hormones. Epidemiological studies typically measure fecundability, the per menstrual cycle probability of conception, using time to pregnancy data. A critical predictor, which is often ignored in the design or analysis, is the timing of non-contracepting intercourse in the menstrual cycle. In order to limit confounding by behavioural differences between exposure groups, it may be preferable to base inferences on day-specific conception probabilities in relation to intercourse timing. This article proposes Bayesian methods for selection of predictors of day-specific conception probabilities. A particular focus is the case in which data on ovulation timing are not available. We focus on the selection of fertile days in the cycle during which conception probabilities are non-negligible and predictors may play a role. Data from recent European and Italian prospective studies of daily fecundability are presented, and the proposed approach is used to estimate cervical mucus effects within a mid-cycle potentially fertile window using data from the Italian study.

Bayes Theorem↗
PubMed2006

Bayesian covariance selection in generalized linear mixed models.

The generalized linear mixed model (GLMM), which extends the generalized linear model (GLM) to incorporate random effects characterizing heterogeneity among subjects, is widely used in analyzing correlated and longitudinal data. Although there is often interest in identifying the subset of predictors that have random effects, random effects selection can be challenging, particularly when outcome distributions are nonnormal. This article proposes a fully Bayesian approach to the problem of simultaneous selection of fixed and random effects in GLMMs. Integrating out the random effects induces a covariance structure on the multivariate outcome data, and an important problem that we also consider is that of covariance selection. Our approach relies on variable selection-type mixture priors for the components in a special Cholesky decomposition of the random effects covariance. A stochastic search MCMC algorithm is developed, which relies on Gibbs sampling, with Taylor series expansions used to approximate intractable integrals. Simulated data examples are presented for different exponential family distributions, and the approach is applied to discrete survival data from a time-to-pregnancy study.

Adult↗
PubMed2006

Bayesian semiparametric dynamic frailty models for multiple event time data.

Many biomedical studies collect data on times of occurrence for a health event that can occur repeatedly, such as infection, hospitalization, recurrence of disease, or tumor onset. To analyze such data, it is necessary to account for within-subject dependency in the multiple event times. Motivated by data from studies of palpable tumors, this article proposes a dynamic frailty model and Bayesian semiparametric approach to inference. The widely used shared frailty proportional hazards model is generalized to allow subject-specific frailties to change dynamically with age while also accommodating nonproportional hazards. Parametric assumptions on the frailty distribution are avoided by using Dirichlet process priors for a shared frailty and for multiplicative innovations on this frailty. By centering the semiparametric model on a conditionally conjugate dynamic gamma model, we facilitate posterior computation and lack-of-fit assessments of the parametric model. Our proposed method is demonstrated using data from a cancer chemoprevention study.

Algorithms↗
PubMed2005

Cervical mucus secretions on the day of intercourse: an accurate marker of highly fertile days.

OBJECTIVE: To provide estimates of the probabilities of conception according to vulvar mucus observations classified by the woman on the day of intercourse. STUDY DESIGN: Prospective cohort study of 193 outwardly healthy Italian women using the Billings Ovulation Method. Outcome measures include 161 conception cycles and 2594 non-conception cycles with daily records of the type of mucus and the occurrences of sexual intercourse. RESULTS: The probability of conception ranged from 0.003 for days with no noticeable secretions to 0.29 for days with most fertile-type mucus detected by the woman. The probability of most fertile type mucus by day of the menstrual cycle increased from values <20% outside of days 10-17 to a peak of 59% on day 13. CONCLUSION: Regardless of the timing of intercourse in the menstrual cycle, the probability of conception is essentially 0 on days with no secretions. This probability increases dramatically to near 30% on days with most fertile-type mucus, an association that accurately predicts both the timing of the fertile interval and the day-specific conception probabilities across the menstrual cycle.

Cervix Mucus↗
PubMed2005

Maternal serum levels of polychlorinated biphenyls and 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) and time to pregnancy.

Polychlorinated biphenyls (PCBs), once used widely in transformers and other applications, and 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE), the main metabolite of the pesticide 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (DDT), are hormonally active agents. Changes in menstrual cycle functioning associated with PCBs and DDE, and increased odds of spontaneous abortion associated with DDE, suggest that these compounds could affect fertility. The authors investigated the association between PCB and DDE exposure and time to pregnancy by using serum levels measured in 390 pregnant women in the Collaborative Perinatal Project enrolled at 12 study centers in the United States from 1959 to 1965. They estimated adjusted fecundability odds ratios by using Cox proportional hazards modeling for discrete time data. Compared with time to pregnancy for women in the lowest exposure category (PCBs < 1.24 microg/liter, DDE < 14 microg/liter), time to pregnancy increased for women in the highest exposure category in terms of both PCBs (fecundability odds ratio for PCBs > or = 5.00 microg/liter = 0.65, 95% confidence interval: 0.36, 1.18) and DDE (fecundability odds ratio for DDE > or = 60 microg/liter = 0.65, 95% confidence interval: 0.32, 1.31). Overall, time to pregnancy increased with increasing serum PCB levels but was less suggestive of an association with DDE. Both trends were imprecise and attenuated when expressed on a lipid basis. Overall, evidence of an association between PCB or DDE exposure and time to pregnancy was weak and inconclusive.

Adult↗
PubMed2005

A transformation approach for incorporating monotone or unimodal constraints.

Samples of curves are collected in many applications, including studies of reproductive hormone levels in the menstrual cycle. Many approaches have been proposed for correlated functional data of this type, including smoothing spline methods and other flexible parametric modeling strategies. In many cases, the underlying biological processes involved restrict the curve to follow a particular shape. For example, progesterone levels in healthy women increase during the menstrual cycle to a peak achieved at random location with decreases thereafter. Reproductive epidemiologists are interested in studying the distribution of the peak and the trajectory for women in different groups. Motivated by this application, we propose a simple approach for restricting each woman's mean trajectory to follow an umbrella shape. An unconstrained hierarchical Bayesian model is used to characterize the data, and draws from the posterior distribution obtained using a Gibbs sampler are then mapped to the constrained space. Inferences are based on the resulting quasi-posterior distribution for the peak and individual woman trajectories. The methods are applied to a study comparing progesterone trajectories for conception and nonconception cycles.

Bayes Theorem↗
PubMed2005

Bayesian model selection and averaging in additive and proportional hazards models.

Although Cox proportional hazards regression is the default analysis for time to event data, there is typically uncertainty about whether the effects of a predictor are more appropriately characterized by a multiplicative or additive model. To accommodate this uncertainty, we place a model selection prior on the coefficients in an additive-multiplicative hazards model. This prior assigns positive probability, not only to the model that has both additive and multiplicative effects for each predictor, but also to sub-models corresponding to no association, to only additive effects, and to only proportional effects. The additive component of the model is constrained to ensure non-negative hazards, a condition often violated by current methods. After augmenting the data with Poisson latent variables, the prior is conditionally conjugate, and posterior computation can proceed via an efficient Gibbs sampling algorithm. Simulation study results are presented, and the methodology is illustrated using data from the Framingham heart study.

Age of Onset↗
PubMed2005

Maternal serum level of the DDT metabolite DDE in relation to fetal loss in previous pregnancies.

Use of 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (DDT) continues in about 25 countries. This use has been justified partly by the belief that it has no adverse consequences on human health. Evidence has been increasing, however, for adverse reproductive effects of DDT, but additional data are needed. Pregnant women who enrolled in the Collaborative Perinatal Project (United States, 1959-1965) were asked about their previous pregnancy history; blood samples were drawn and the serum frozen. In 1997-1999, the sera of 1717 of these women who had previous pregnancies were analyzed for 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE), the major breakdown product of DDT. The odds of previous fetal loss was examined in relation to DDE level in logistic regression models. Compared with women whose DDE level was <15 microg/L, the adjusted odds ratios of fetal loss according to category of DDE were as follows: 15-29 microg/L, 1.1; 30-44 microg/L, 1.4; 45-59 microg/L, 1.6; and 60+ microg/L, 1.2. The adjusted odds ratio per 60 microg/L increase was 1.4 (95% confidence interval 1.1-1.6). The results were consistent with an adverse effect of DDE on fetal loss, but were inconclusive owing to the possibility that previous pregnancies ending in fetal loss decreased serum DDE levels less than did those carried to term.

Abortion, Spontaneous↗
PubMed2005

Bayesian latent variable models for mixed discrete outcomes.

In studies of complex health conditions, mixtures of discrete outcomes (event time, count, binary, ordered categorical) are commonly collected. For example, studies of skin tumorigenesis record latency time prior to the first tumor, increases in the number of tumors at each week, and the occurrence of internal tumors at the time of death. Motivated by this application, we propose a general underlying Poisson variable framework for mixed discrete outcomes, accommodating dependency through an additive gamma frailty model for the Poisson means. The model has log-linear, complementary log-log, and proportional hazards forms for count, binary and discrete event time outcomes, respectively. Simple closed form expressions can be derived for the marginal expectations, variances, and correlations. Following a Bayesian approach to inference, conditionally-conjugate prior distributions are chosen that facilitate posterior computation via an MCMC algorithm. The methods are illustrated using data from a Tg.AC mouse bioassay study.

Acrylates↗
PubMed2005

Reduced fertilization rates in older men when cervical mucus is suboptimal.

OBJECTIVE: Cervical mucus is vital in the regulation of sperm survival and transport through the reproductive tract. The goal of this study is to assess whether the lowered fertility for men in their late 30s and early 40s is related to the nature of cervical mucus on the day of intercourse. METHODS: In a prospective study of 7 European family planning centers, 782 couples not using birth control recorded daily observations of intercourse and the nature of cervical mucus. Using data from 1,459 menstrual cycles, 342 ending in pregnancy, we estimate day-specific conception probabilities in relation to mucus and male and female age. RESULTS: On days where cervical mucus was not evident, intercourse for men in their late 30s and early 40s was 50% less likely to result in a clinical pregnancy, adjusting for intercourse timing and female age. As secretions become more conducive to sperm transport, the effect of male age diminishes steadily from 21% on days with damp secretions, to 11% on days with thick mucus, to only 4% on days with most fertile-type mucus. CONCLUSION: The effect of male age on fecundability can be minimized by timing intercourse on days with optimal secretions. LEVEL OF EVIDENCE: II-2.

Adult↗
PubMed2005

Bayesian inferences on predictors of conception probabilities.

Reproductive scientists and couples attempting pregnancy are interested in identifying predictors of the day-specific probabilities of conception in relation to the timing of a single intercourse act. Because most menstrual cycles have multiple days of intercourse, the occurrence of conception represents the aggregation across Bernoulli trials for each intercourse day. Because of this data structure and dependency among the multiple cycles from a woman, implementing analyses has proven challenging. This article proposes a Bayesian approach based on a generalization of the Barrett and Marshall model to incorporate a woman-specific frailty and day-specific covariates. The model results in a simple closed form expression for the marginal probability of conception, and has an auxiliary variables formulation that facilitates efficient posterior computation. Although motivated by fecundability studies, the approach can be used for efficient variable selection and model averaging in general applications with categorical or discrete event time data.

Adult↗
PubMed2005

Bayesian inferences on umbrella orderings.

In regression applications with categorical predictors, interest often focuses on comparing the null hypothesis of homogeneity to an ordered alternative. This article proposes a Bayesian approach for addressing this problem in the setting of normal linear and probit regression models. The regression coefficients are assigned a conditionally conjugate prior density consisting of mixtures of point masses at 0 and truncated normal densities, with a (possibly unknown) changepoint parameter included to accommodate umbrella ordering. Two strategies of prior elicitation are considered: (1) a Bayesian Bonferroni approach in which the probability of the global null hypothesis is specified and local hypotheses are considered independent; and (2) an approach which treats these probabilities as random. A single Gibbs sampling chain can be used to obtain posterior probabilities for the different hypotheses and to estimate regression coefficients and predictive quantities either by model averaging or under the preferred hypothesis. The methods are applied to data from a carcinogenesis study.

Adenoma, Liver Cell↗
PubMed2004

On the frequency of intercourse around ovulation: evidence for biological influences.

BACKGROUND: Intercourse in mammals is often coordinated with ovulation, for example through fluctuations in libido or by the acceleration of ovulation with intercourse. Such coordination has not been established in humans. We explored this possibility by examining patterns of sexual intercourse in relation to ovulation. METHODS: Sixty-eight sexually active North Carolina women with either an intrauterine device or tubal ligation provided data for up to three menstrual cycles. These women collected daily urine specimens and kept daily diaries of intercourse and menstrual bleeding. Major estrogen and progesterone metabolites excreted in urine were used to identify the day of ovulation. The fertile days of the cycle were defined as the 6 consecutive days ending with ovulation. Women contributed a total of 171 ovulatory cycles. Menstrual bleeding days were excluded from analysis. RESULTS: The frequency of intercourse rose during the follicular phase, peaking at ovulation and declining abruptly thereafter. The 6 consecutive days with most frequent intercourse corresponded with the 6 fertile days of the menstrual cycle. Intercourse was 24% more frequent during the 6 fertile days than during the remaining non-bleeding days (P < 0.001). CONCLUSIONS: There apparently are biological factors that promote intercourse during a woman's 6 fertile days.

Adult↗
PubMed2004

Mucus observations in the fertile window: a better predictor of conception than timing of intercourse.

BACKGROUND: Intercourse results in a pregnancy essentially only if it occurs during the 6-day fertile interval ending on the day of ovulation. The strong association between timing of intercourse within this interval and the probability of conception typically is attributed to limited sperm and egg life times. METHODS: A total of 782 women recruited from natural family planning centres in Europe contributed prospective data on 7288 menstrual cycles. Daily records of intercourse, basal body temperature and vaginal discharge of cervical mucus were collected. Probabilities of conception were estimated according to the timing of intercourse relative to ovulation and a 1-4 score of mucus quality. RESULTS: There was a strong increasing trend in the day-specific probabilities of pregnancy with increases in the mucus score. Adjusting for the mucus score, the day-specific probabilities had limited variability across the fertile interval. CONCLUSIONS: Changes in mucus quality across the fertile interval predict the observed pattern in the day-specific probabilities of conception. To maximize the likelihood of conception, intercourse should occur on days with optimal mucus quality, as observed in vaginal discharge, regardless of the exact timing relative to ovulation.

Adult↗