The association of HSV 1 and 2 with atherosclerosis defined by CRP level

A study of the association of Herpes simplex virus 1 and 2 exposure to early atherosclerosis using high C-reactive protein level as a marker was carried out in US born, non-pregnant, 20-49 year olds participating in a national survey between 1999 and 2004. Participants were required to have valid results for Herpes simplex virus 1 and 2 and C-Reactive Protein for inclusion. Cases were those found to have a high C-reactive protein level of 0.3-1 mg/dL, while controls had low to normal values (0.01-0.29 mg/dL). Overall, there were 1211 cases and 2870 controls. Mexican American and non-Hispanic black women were much more likely to fall into the high cardiac risk group than the other sex race groups with proportions of 44% and 39%, respectively. ^ Herpesvirus exposure was categorized such that Herpes simplex virus 1 and 2 exposure could be studied simultaneously within the same individual and models. The HSV 1+, HSV 2- category included the highest percentage (45.63%) of participants, followed by HSV 1-, HSV 2- (30.16%); HSV 1+, HSV 2+ (15.09%); and HSV 1-, HSV 2+ (9.12%) respectively. The proportion of participants in the HSV 1+, HSV 2- category was substantially higher in Mexican Americans (63%-66%). Further, the proportion in the HSV 1+, HSV 2+ category was notably higher in the non-Hispanic black participants (23%-44%). Non-Hispanic black women also had the highest percentage of HSV 1-, HSV 2+ exposure of all the sex race groups at 17%. ^ Overall, the unadjusted odds ratios for atherosclerotic disease defined by C-reactive protein with HSV 1-, HSV 2- as the referent group was 1.62 (95% CI 1.23-2.14) for HSV 1 +, HSV 2+; 1.3 (95% CI 1.10-1.69 for HSV 1+, HSV 2-; and 1.52 (95% CI 1.14-2.01). When the study was stratified into sex-race groups, only HSV 1+, HSV 2- in the Non-Hispanic white men remained significant (OR=1.6; 95% CI 1.06-2.43). Adjustment for selected covariates was made in the multivariate model for both the overall and sex-race stratified studies. High C-reactive protein values were not associated with any of the Herpesvirus exposure levels in either the overall or stratified analyses. ^

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^