A SEMI-PARAMETRIC BAYESIAN MODEL OF INTER- AND INTRA-EXAMINER AGREEMENT FOR PERIODONTAL PROBING DEPTH.

Periodontal probing depth is a measure of periodontitis severity. We develop a Bayesian hierarchical model linking true pocket depth to both observed and recorded values of periodontal probing depth, while permitting correlation among measures obtained from the same mouth and between duplicate examiners' measures obtained at the same periodontal site. Periodontal site-specific examiner effects are modeled as arising from a Dirichlet process mixture, facilitating identification of classes of sites that are measured with similar bias. Using simulated data, we demonstrate the model's ability to recover examiner site-specific bias and variance heterogeneity and to provide cluster-adjusted point and interval agreement estimates. We conclude with an analysis of data from a probing depth calibration training exercise.

Effect of mechanical loading on electrical conductivity in porcine TMJ discs.

The objective of this study was to examine the impact of mechanical loading on solute transport in porcine temporomandibular joint (TMJ) discs using the electrical conductivity method. The electrical conductivity, as well as ion diffusivity, of TMJ discs was determined under confined compression with 3 strains in 5 disc regions. The average electrical conductivity over the 5 regions (mean ± SD) at 0% strain was 3.10 ± 0.68 mS/cm, decreased to 2.76 ± 0.58 mS/cm (-11.0%) at 10% strain, and 2.38 ± 0.55 mS/cm (-22.2%) at 20% compressive strain. Correspondingly, the average relative ion diffusivity (mean ± SD) at 0% strain was 0.273 ± 0.055, decreased to 0.253 ± 0.048 (-7.3%) at 10% strain, and 0.231 ± 0.048 (-15.4%) at 20% compressive strain. These results indicated that compressive strain impeded solute transport in the TMJ disc. Furthermore, our results showed that the transport properties of TMJ discs were region-dependent. The electrical conductivity and ion diffusivity in the anterior region were significantly higher than in the posterior region. This regional difference is likely due to the significant differences of tissue hydration between these 2 regions. This study provides important insight into the electrical and solute transport behaviors in TMJ discs under mechanical loading and aids in the understanding of TMJ pathophysiology related to tissue nutrition.

Expression of periodontal interleukin-6 protein is increased across patients with neither periodontal disease nor diabetes, patients with periodontal disease alone and patients with both diseases.

BACKGROUND AND OBJECTIVE: Epidemiological studies have established that patients with diabetes have an increased prevalence and severity of periodontal disease. Interleukin (IL)-6, a multifunctional cytokine, plays a role in the tissue inflammation that characterizes periodontal disease. Our recent study has shown a trend of increase in periodontal IL-6 expression at the mRNA level across patients with neither periodontal disease nor diabetes, patients with periodontal disease alone and patients with both diseases. However, the periodontal IL-6 expression at the protein level in these patients has not been investigated. MATERIAL AND METHODS: Periodontal tissue specimens were collected from eight patients without periodontal disease and diabetes (group 1), from 17 patients with periodontal disease alone (group 2) and from 10 patients with both periodontal disease and diabetes (group 3). The frozen sections were prepared from these tissue specimens and IL-6 protein expression was detected and quantified. RESULTS: The nonparametric Kruskal-Wallis test showed that the difference in IL-6 protein levels among the three groups was statistically significant (p = 0.035). Nonparametric analysis using the Jonckheere-Terpstra test showed a tendency of increase in periodontal IL-6 protein levels across group 1 to group 2 to group 3 (p = 0.006). Parametric analysis of variance (ANOVA) on IL-6 protein levels showed that neither age nor gender significantly affected the difference of IL-6 levels among the groups. CONCLUSION: Periodontal IL-6 expression at the protein level is increased across patients with neither periodontal disease nor diabetes, patients with periodontal disease alone and patients with both diseases.

A trend of increase in periodontal interleukin-6 expression across patients with neither diabetes nor periodontal disease, patients with periodontal disease alone, and patients with both diseases.

BACKGROUND AND OBJECTIVE: Epidemiological studies have established that patients with diabetes have increased prevalence and severity of periodontal disease. However, the periodontal expression of inflammatory cytokines and matrix metalloproteinases (MMPs) in diabetic patients has not been well characterized. The objective of this study was to determine the difference in the periodontal expression of MMP-1, MMP-8, interleukin-6, tumor necrosis factor-alpha and interleukin-1beta between diabetic and nondiabetic patients. MATERIAL AND METHODS: Periodontal tissue specimens were collected from nine nondiabetic patients without periodontal disease (group 1), from 11 nondiabetic patients with periodontal disease (group 2) and from seven diabetic patients with periodontal disease (group 3). The expression of MMP-1, MMP-8, interleukin-6, tumor necrosis factor-alpha and interleukin-1beta was quantified using real-time polymerase chain reaction. RESULTS: The nonparametric Kruskal-Wallis test showed that the difference in interleukin-6 expression among the groups was statistically significant (p = 0.04). Furthermore, the generalized Kruskal-Wallis nonparametric linear-by-linear association test showed a statistically significant trend of increase in the expression of interleukin-6 from group 1 to group 2 to group 3 (p = 0.02) and a suggestion of such a trend for MMP-1 (p = 0.05). No increase in MMP-8 expression was observed in patients in group 3 compared to patients in groups 1 and 2. Although the average expression levels of MMP-1, interleukin-1beta and tumor necrosis factor-alpha were increased from group 1 to group 3, the differences were not statistically significant. CONCLUSION: A trend of increased interleukin-6 expression in periodontal tissues was observed across patients with neither diabetes nor periodontal disease, patients with periodontal disease alone, and patients with both diseases.

High glucose-boosted inflammatory responses to lipopolysaccharide are suppressed by statin.

BACKGROUND AND OBJECTIVE: It has been established that periodontal diseases are more prevalent and of greater severity in diabetic patients than in nondiabetic patients. Recent studies have underscored the role of monocytes and macrophages in periodontal tissue inflammation and destruction in diabetic patients. Although it has been shown that monocytes isolated from diabetic patients produce more inflammatory cytokines and that gingival crevicular fluid collected from diabetic patients contains higher levels of inflammatory cytokines than that obtained from nondiabetic patients, the underlying mechanisms are not well understood. MATERIAL AND METHODS: U937 histiocytes cultured in medium containing either normal (5 mM) or high (25 mM) glucose were treated with 100 ng/ml of lipopolysaccharide for 24h. After the treatment, cytokines in the medium and cytokine mRNA in the cells were quantified using enzyme-linked immunosorbet assay and real-time polymerase chain reaction, respectively. RESULTS: In this study, we demonstrated that the pre-exposure of U937 histiocytes to high glucose concentrations markedly increased the lipopolysaccharide-induced secretion of pro-inflammatory cytokines and chemokines and the cellular inducible nitric oxide level compared with pre-exposure to normal glucose. Our data also showed that the increased secretion of cytokines was a result of increased mRNA expression. Furthermore, the effects of statin and peroxisome proliferators-activated receptor agonists on high glucose-enhanced secretion of cytokines were determined. The results showed that simvastatin, but not fenofibrate or pioglitazone, inhibited high glucose-enhanced cytokine release. CONCLUSION: This study has shown that high glucose concentrations and lipopolysaccharide act synergistically to stimulate the secretion of inflammatory mediators, and that statin is capable of suppressing the high glucose-boosted proinflammatory response. This study therefore delineates a novel mechanism by which hyperglycemia enhances the inflammatory responses of macrophages and suggests that statin may be useful in the treatment of periodontal disease in diabetic patients.

Selenium supplementation, baseline plasma selenium status and incidence of prostate cancer: an analysis of the complete treatment period of the Nutritional Prevention of Cancer Trial.

OBJECTIVE: To present the results (to January 1996, the end of blinded treatment) of the Nutritional Prevention of Cancer (NPC) Trial, a randomized trial of selenium (200 micro g daily) designed to test the hypothesis that selenium supplementation (SS) could reduce the risk of recurrent nonmelanoma skin cancer among 1312 residents of the Eastern USA. MATERIALS AND METHODS: Original secondary analyses of the NPC to 1993 showed striking inverse associations between SS and prostate cancer incidence. A subsequent report revealed that this effect was accentuated among men with the lowest baseline plasma selenium concentrations. The effects of treatment overall and within subgroups of baseline prostate-specific antigen (PSA) and plasma selenium concentrations were examined using incidence rate ratios and Cox proportional hazards models. RESULTS: SS continued to significantly reduce the overall incidence (relative risk and 95% confidence interval) of prostate cancer (0.51, 0.29-0.87). The protective effect of SS appeared to be confined to those with a baseline PSA level of

Discovering subpopulation structure with latent class mixed models.

The linear mixed model is a well-known method for incorporating heterogeneity (for example, subject-to-subject variation) into a statistical analysis for continuous responses. However heterogeneity cannot always be fully captured by the usual assumptions of normally distributed random effects. Latent class mixed models offer a way of incorporating additional heterogeneity which can be used to uncover distinct subpopulations, to incorporate correlated non-normally distributed outcomes and to classify individuals. The methodology is motivated with examples in health care studies and a detailed illustration is drawn from the Nutritional Prevention of Cancer trials. Latent class models are used with longitudinal data on prostate specific antigen (PSA) as well as incidence of prostate cancer. The models are extended to accommodate prostate cancer as a survival endpoint; this is compared to treating it as a binary endpoint. Four subpopulations are identified which differ both with regard to their PSA trajectories and their incidence rates of prostate cancer.

A latent class mixed model for analysing biomarker trajectories with irregularly scheduled observations.

This paper considers a latent class model to uncover subpopulation structure for both biomarker trajectories and the probability of disease outcome in highly unbalanced longitudinal data. A specific pattern of trajectories can be viewed as a latent class in a finite mixture where membership in latent classes is modelled with a polychotomous logistic regression. The biomarker trajectories within a latent class are described by a linear mixed model with possibly time-dependent covariates and the probabilities of disease outcome are estimated via a class specific model. Thus the method characterizes biomarker trajectory patterns to unveil the relationship between trajectories and outcomes of disease. The coefficients for the model are estimated via a generalized EM (GEM) algorithm, a natural tool to use when latent classes and random coefficients are present. Standard errors of the coefficients are calculated using a parametric bootstrap. The model fitting procedure is illustrated with data from the Nutritional Prevention of Cancer trials; we use prostate specific antigen (PSA) as the biomarker for prostate cancer and the goal is to examine trajectories of PSA serial readings in individual subjects in connection with incidence of prostate cancer.

Statistical models for longitudinal biomarkers of disease onset.

We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data.

Decreased incidence of prostate cancer with selenium supplementation: results of a double-blind cancer prevention trial.

OBJECTIVE: To test if supplemental dietary selenium is associated with changes in the incidence of prostate cancer. PATIENTS AND METHOD: A total of 974 men with a history of either a basal cell or squamous cell carcinoma were randomized to either a daily supplement of 200 microg of selenium or a placebo. Patients were treated for a mean of 4.5 years and followed for a mean of 6.5 years. RESULTS: Selenium treatment was associated with a significant (63%) reduction in the secondary endpoint of prostate cancer incidence during 1983-93. There were 13 prostate cancer cases in the selenium-treated group and 35 cases in the placebo group (relative risk, RR=0.37, P=0.002). Restricting the analysis to the 843 patients with initially normal levels of prostate-specific antigen (< or = 4 ng/mL), only four cases were diagnosed in the selenium-treated group and 16 cases were diagnosed in the placebo group after a 2 year treatment lag, (RR=0.26 P=0.009). There were significant health benefits also for the other secondary endpoints of total cancer mortality, and the incidence of total, lung and colorectal cancer. There was no significant change in incidence for the primary endpoints of basal and squamous cell carcinoma of the skin. In light of these results, the 'blinded' phase of this trial was stopped early. CONCLUSIONS: Although selenium shows no protective effects against the primary endpoint of squamous and basal cell carcinomas of the skin, the selenium-treated group had substantial reductions in the incidence of prostate cancer, and total cancer incidence and mortality that demand further evaluation in well-controlled prevention trials.

Effects of selenium supplementation for cancer prevention in patients with carcinoma of the skin. A randomized controlled trial. Nutritional Prevention of Cancer Study Group.

OBJECTIVE: To determine whether a nutritional supplement of selenium will decrease the incidence of cancer. DESIGN: A multicenter, double-blind, randomized, placebo-controlled cancer prevention trial. SETTING: Seven dermatology clinics in the eastern United States. PATIENTS: A total of 1312 patients (mean age, 63 years; range, 18-80 years) with a history of basal cell or squamous cell carcinomas of the skin were randomized from 1983 through 1991. Patients were treated for a mean (SD) of 4.5 (2.8) years and had a total follow-up of 6.4 (2.0) years. INTERVENTIONS: Oral administration of 200 microg of selenium per day or placebo. MAIN OUTCOME MEASURES: The primary end points for the trial were the incidences of basal and squamous cell carcinomas of the skin. The secondary end points, established in 1990, were all-cause mortality and total cancer mortality, total cancer incidence, and the incidences of lung, prostate, and colorectal cancers. RESULTS: After a total follow-up of 8271 person-years, selenium treatment did not significantly affect the incidence of basal cell or squamous cell skin cancer. There were 377 new cases of basal cell skin cancer among patients in the selenium group and 350 cases among the control group (relative risk [RR], 1.10; 95% confidence interval [CI], 0.95-1.28), and 218 new squamous cell skin cancers in the selenium group and 190 cases among the controls (RR, 1.14; 95% CI, 0.93-1.39). Analysis of secondary end points revealed that, compared with controls, patients treated with selenium had a nonsignificant reduction in all-cause mortality (108 deaths in the selenium group and 129 deaths in the control group [RR; 0.83; 95% CI, 0.63-1.08]) and significant reductions in total cancer mortality (29 deaths in the selenium treatment group and 57 deaths in controls [RR, 0.50; 95% CI, 0.31-0.80]), total cancer incidence (77 cancers in the selenium group and 119 in controls [RR, 0.63; 95% CI, 0.47-0.85]), and incidences of lung, colorectal, and prostate cancers. Primarily because of the apparent reductions in total cancer mortality and total cancer incidence in the selenium group, the blinded phase of the trial was stopped early. No cases of selenium toxicity occurred. CONCLUSIONS: Selenium treatment did not protect against development of basal or squamous cell carcinomas of the skin. However, results from secondary end-point analyses support the hypothesis that supplemental selenium may reduce the incidence of, and mortality from, carcinomas of several sites. These effects of selenium require confirmation in an independent trial of appropriate design before new public health recommendations regarding selenium supplementation can be made

A computer program for sample size and power calculations in the design of multi-arm and factorial clinical trials with survival time endpoints.

This paper presents a computer program for use in the design of long-term clinical trials with multiple treatment arms in which the primary outcome variables are censored survival times. The treatment arms may be structured as a one-way or multi-way factorial design. It is assumed that patients are entered and randomized to a treatment arm during an accrual period. The patients are then followed for a fixed period during which there may be dropouts. Various distributional assumptions can be used to model the survival times. These include an option in which there is an effect of treatment duly after a lag or delay time. The program then computes the power of various statistical tests of hypotheses concerning treatment differences, interactions and trends. The power computations are "exact" in that they use the Monte Carlo method to obtain Type I and II error probabilities. However the program also outputs the normal approximations for comparison, although they are typically not accurate in these situations. Fisher's LSD method is used to adjust for the multiple comparisons. By comparing the power for various sets of design parameters, such as sample size, numbers of factor levels, patient accrual rate, and length of follow-up, an appropriate design can be constructed. Two examples are provided. The first is a simple one-way layout with multiple treatment arms; the second a two-way factorial design for a proposed large scale cancer chemoprevention trial.

A computer program for the statistical analysis of repeated event data using a mixed effects regression model.

This paper presents a computer program for fitting mixed effects regression models to repeated events data. The method has been described by Abu-Libdeh, Turnbull and Clark (Biometrics 46 (1990) 1017-1034). Such data can occur in longitudinal studies where subjects experience repeated events over time. The program allows the stepwise construction of a series of regression models which can be used to examine and test the influence of the various measured covariates upon the event rates. Two examples are provided. The first is a simple example involving the incidence of mammary tumors in rats. The second involves a very large complex data set from a clinical trial for the prevention of recurrent skin tumors.