Biomedical subjects

R H Lyles

Publications and source records attributed to R H Lyles.

25 records · Page 2Linked to original sources

PubMed1999

Plasma viral load and CD4 lymphocytes predict HIV-associated dementia and sensory neuropathy.

OBJECTIVE: To determine the predictive value of plasma HIV RNA and CD4 lymphocytes for HIV-associated dementia and sensory neuropathy. METHODS: A total of 1,604 AIDS-free HIV seropositive men from the Multicenter AIDS Cohort Study were followed over a 10-year period (1985 to 1995). HIV-associated dementia and sensory neuropathy were diagnosed according to standard definitions. Baseline samples were used to measure plasma HIV RNA levels with a branched DNA assay and levels of beta2-microglobulin, CD4 lymphocyte counts, and hemoglobin levels. RESULTS: Seventy-seven patients with HIV-associated dementia and 213 patients with sensory neuropathy were identified. Baseline HIV RNA levels above 3,000 copies/mL and CD4 counts below 500 cells/mm3 were predictive of both neurologic outcomes, but neither hemoglobin, body mass index, nor beta2-microglobulin were independently predictive. After adjusting for age and level of education, individuals with baseline plasma HIV RNA >30,000 copies/mL had a relative hazard for dementia 8.5 times (p < 0.001) that of those with <3,000 copies/mL, and those with CD4 counts <200 cells/mm3 had a 3.5-fold (p = 0.003) greater hazard relative to those with CD4 counts >500 cells/mm3. Individuals with HIV RNA >10,000 copies/mL had a 2.3-fold (p = 0.008) greater hazard of sensory neuropathy than those with <500 copies/mL, and men with <750 CD4 cells/mm3 had a 1.4-fold (p = 0.03) greater hazard than those with >750 CD4 cells/mm3. CONCLUSIONS: High levels of systemic HIV replication may "drive" the initiation of neurologic disease; effective suppression of HIV may reduce the incidence of dementia and neuropathy. Levels of plasma HIV RNA and CD4 counts, determined before the initiation of antiretroviral therapy, were predictive of HIV-associated dementia and sensory neuropathy.

AIDS Dementia Complex↗

PubMed1997

A lognormal distribution-based exposure assessment method for unbalanced data.

We present a generalization of existing statistical methodology for assessing occupational exposures while explicitly accounting for between- and within-worker sources of variability. The approach relies upon an intuitively reasonable model for shift-long exposures, and requires repeated exposure measurements on at least some members of a random sample of workers from a job group. We make the methodology more readily applicable by providing the necessary details for its use when the exposure data are unbalanced (that is, when there are varying numbers of measurements per worker). The hypothesis testing strategy focuses on the probability that an arbitrary worker in a job group experiences a long-term mean exposure above the occupational exposure limit (OEL). We also provide a statistical approach to aid in the determination of an appropriate intervention strategy in the event that exposure levels are deemed unacceptable for a group of workers. We discuss important practical considerations associated with the methodology, and we provide several examples using unbalanced sets of shift-long exposure data-taken on workers in various sectors of the nickel-producing industry. We conclude that the statistical methods discussed afford sizable practical advantages, while maintaining similar overall performance to that of existing methods appropriate for balanced data only.

Air Pollutants, Occupational↗

PubMed1997

Predicting clinical progression or death in subjects with early-stage human immunodeficiency virus (HIV) infection: a comparative analysis of quantification of HIV RNA, soluble tumor necrosis factor type II receptors, neopterin, and beta2-microglobulin. Multicenter AIDS Cohort Study.

Quantification of human immunodeficiency virus (HIV) RNA by branched-chain DNA signal amplification, measurement of soluble tumor necrosis factor type II receptors (sTNFR-II), neopterin, beta2-microglobulin, or CD4 cell counts can be used to predict the risk of clinical progression or death in HIV infection but have not been compared in the same study. Ninety subjects were categorized into progression groups by their rate of CD4 cell decline and matched into triplets by initial CD4 cell count, age, race, and calendar time. By matched logistic regression, only the sTNFR-II and HIV RNA values were predictive of outcome across the progression groups. Categorization of baseline HIV RNA and sTNFR-II resulted in differences in progression to several clinical outcomes. sTNFR-II concentrations were the only immune marker examined that increased the prognostic utility of HIV RNA determination in early-stage subjects. Further studies in later stages of disease or after therapy are indicated.

CD4 Lymphocyte Count↗

PubMed1997

A detailed evaluation of adjustment methods for multiplicative measurement error in linear regression with applications in occupational epidemiology.

It is often appropriately assumed, based on both theoretical and empirical considerations, that airborne exposures in the workplace are lognormally distributed, and that a worker's mean exposure over a reference time period is a key predictor of subsequent adverse health effects for that worker. Unfortunately, it is generally impossible to accurately measure a worker's true mean exposure. We begin by introducing a familiar model for exposure that views this true mean, as well as logical surrogates for it, as lognormal random variables. In a more general context, we then consider the linear regression of a continuous health outcome on a lognormal predictor measured with multiplicative error. We discuss several candidate methods of adjusting for the measurement error to obtain consistent estimators of the true regression parameters. These methods include a simple correction of the ordinary least squares estimator based on the surrogate regression, the regression of the outcome on the covariates and on the conditional expectation of the true predictor given the observed surrogate, and a quasi-likelihood approach. By means of a simulation study, we compare the various methods for practical sample sizes and discuss important issues relevant to both estimation and inference. Finally, we illustrate promising adjustment strategies using actual lung function and dust exposure data on workers in the Dutch animal feed industry.

Analysis of Variance↗

PubMed1996

On strategies for comparing occupational exposure data to limits.

Parametric statistical approaches to assessing workplace exposure levels have typically focused either on the probability that a single measurement exceeds a limit or on whether the mean exposure for a population of workers exceeds a limit. This article reviews and clarifies some methods that have been proposed for each of these two approaches, on the assumption that the exposure data represent a random sample from a lognormal distribution. For tests concerning the mean exposure level, the authors developed a potentially useful new procedure based on a bound for noncentral t critical values. Appropriate sample size calculations are emphasized, and computer simulation is used to compare competing methods for assessing mean exposure. The authors conclude that the new proposed method offers an appealing alternative to existing methods in many cases. The importance of employing an exposure assessment strategy that is in concert with underlying etiologic considerations is stressed.

Humans↗

PubMed1995

Effects of model misspecification in the estimation of variance components and intraclass correlation for paired data.

Paired data occur in many experimental situations. When one views the subjects as a random sample from some large population, it may seem reasonable to model the data according to the typical one-way random effects analysis of variance (ANOVA). It is then usually of interest to estimate variance components and intraclass correlation. These estimators can be biased if key assumptions are violated, leading to erroneous interpretations and conclusions. We focus upon assumptions about the equality or inequality of means and/or variances of the two measures on each subject. In the framework of the one-way random effects ANOVA model, and three generalizations of it, we document estimators obtained as solutions to the likelihood equations. We consider the potentially serious effects of mistaken assumptions. Our findings suggest that the most general model considered is most desirable if consistent and efficient estimation of the between-subject variance component and intraclass correlation is the main goal. We also briefly connect our exposition to the study of reliability or agreement.

Analysis of Variance↗

PubMed1995

An exposure-assessments strategy accounting for within- and between-worker sources of variability.

A strategy is presented for comparing exposures to an occupational exposure limit (OEL) and for suggesting appropriate interventions when exposures are unacceptable. The major departure from previous approaches is the explicit recognition that exposures vary both within and between workers in a given occupational group. The primary goal is to determine whether the probability of overexposure is acceptably small (a value of 0.10 or less is recommended), with overexposure being defined as the likelihood that a randomly selected worker's true mean exposure exceeds the OEL. The exposure-assessment protocol contains five levels. It is suggested that at least two shift-long measurements be randomly collected from each of 10 workers for preliminary analysis. If the logged exposure data appear to be appropriate for testing (Level 1), the probability of overexposure is compared to the pre-determined value via a rigorous test of statistical significance (Level 2). Based upon published data, this test is likely to classify exposures as acceptable with 20 measurements when the group mean exposure is less than one-fifth of the OEL. However, if exposure is found to be unacceptable, re-sampling can be considered to increase the power of the test (Level 3). Otherwise, it is necessary to reduce exposures and then to re-apply the protocol. If it appears that all persons in the group have essentially the same predicted mean exposures (Level 4), then engineering or administrative controls are recommended. If, on the other hand, substantial differences appear to exist amongst these predicted mean values, regrouping and/or modifications of tasks and work practices should be considered (Level 5). Application of the protocol is illustrated with samples of data from four groups of workers exposed to inorganic nickel in the nickel-producing industry.

Analysis of Variance↗