Elizabeth H. Slate

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

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

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 µg 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.

Latent Class Models for Joint Analysis of Longitudinal Biomarker and Event Process Data: Application to Longitudinal Prostate-Specific Antigen Readings and Prostate Cancer

A retrospective substudy of the nutritional prevention of cancer (NPC) trials investigated the utility of longitudinally measured prostate-specific antigen (PSA) as a biomarker for subsequent onset of prostate cancer (PCa). Serial PSA levels were determined retrospectively from frozen blood samples that had been collected from all patients at successive clinic visits with the timing and the number of these visits highly variable. Diagnosis dates of all incident cases of PCa were recorded. Heterogeneity in PSA trajectories was observed that could not be fully explained by the usual linear mixed-effects model and measured covariates. Latent class models that incorporate both a longitudinal biomarker process and an event process offer a way to handle additional heterogeneity, to uncover distinct subpopulations, to incorporate correlated nonnormally distributed outcomes, and to classify individuals into risk classes. Our latent class joint model can aid the prediction of PCa probability given the longitudinal biomarker information available on an individual up to any date. The proposed model easily accommodates highly unbalanced longitudinal data and recurrent events. There are two levels of structure in the latent class joint model. First, the uncertainty of latent class membership is specified through a multinomial logistic model. Second, the class-specific marker trajectory and event process are specified parametrically and semiparametrically, under the assumption of conditional independence given the latent class membership. We use a likelihood approach to obtain parameter estimates via the EM algorithm. We fit the latent class joint model to the data from the NPC trials; four distinct subpopulations are identified that differ with regard to their PSA trajectories and risk for prostate cancer. Higher PSA level is significantly associated with increased risk of PCa, but appears to be conditionally independent once the latent classes are taken into account. Among the covariates, selenium supplementation and age at entry are statistically significant for various parts of the model. Assumptions—in particular the conditional independence between the longitudinal PSA biomarker and time to PCa diagnosis—are assessed.

Global Validation of Linear Model Assumptions

An easy-to-implement global procedure for testing the four assumptions of the linear model is proposed. The test can be viewed as a Neyman smooth test and relies only on the standardized residual vector. If the global procedure indicates a violation of at least one of the assumptions, then the components of the global test statistic can be used to gain insight into which assumptions have been violated. The procedure can also be used in conjunction with associated deletion statistics to detect unusual observations. Simulation results are presented indicating the sensitivity of the procedure in detecting model violations under a variety of situations, and its performance is compared with three potential competitors, including a procedure based on the Box–Cox power transformation. The procedure is demonstrated by applying it to a new car mileage dataset and a water salinity dataset that has been used earlier to illustrate model diagnostics.

The Nutritional Prevention of Cancer: 400 Mcg Per Day Selenium Treatment

Nonexperimental studies suggest that individuals with higher selenium (Se) status are at decreased risk of cancer. The Nutritional Prevention of Cancer (NPC) study randomized 1,312 high-risk dermatology patients to 200-mcg/day of Se in selenized yeast or a matched placebo; selenium supplementation decreased the risk of lung, colon, prostate, and total cancers but increased the risk of nonmelanoma skin cancer. In this article, we report on a small substudy in Macon, GA, which began in 1989 and randomized 424 patients to 400-mcg/day of Se or to matched placebo. The subjects from both arms had similar baseline Se levels to those treated by 200 mcg, and those treated with 400-mcg attained plasma Se levels much higher than subjects treated with 200 mcg. The 200-mcg/day Se treatment decreased total cancer incidence by a statistically significant 25%; however, 400-mcg/day of Se had no effect on total cancer incidence.

Flap thickness accuracy ☆ ☆☆ ★ ★★: Comparison of 6 microkeratome models

Purpose: To determine the flap thickness accuracy of 6 microkeratome models and determine factors that might affect flap thickness. Setting: Magill Research Center for Vision Correction, Storm Eye Institute, Medical University of South Carolina, Charleston, South Carolina, USA. Methods: This multicenter prospective study involved 18 surgeons. Six microkeratomes were evaluated: AMO Amadeus, Bausch & Lomb Hansatome®, Moria Carriazo‐Barraquer, Moria M2, Nidek MK2000, and Alcon Summit Krumeich‐Barraquer. Eyes of 1061 consecutive patients who had laser in situ keratomileusis were included. Age, sex, surgical order (first or second cut), keratometry (flattest, steepest, and mean), white‐to‐white measurement, laser used, plate thickness, head serial number, blade lot number, and occurrence of epithelial defects were recorded. Intraoperative pachymetry was obtained just before the microkeratome was placed on the eye. Residual bed pachymetry was measured after the microkeratome cut had been created and the flap lifted. The estimated flap thickness was determined by subtraction (ie, mean preoperative pachymetry measurement minus mean residual bed pachymetry). Results: A total of 1634 eyes were reviewed. Sex distribution was 54.3% women and 45.7% men, and the mean age was 39.4 years ± 10.6 (SD). In addition, 54.5% of the procedures were in first eyes and 45.5%, in second eyes. The mean preoperative pachymetry measurement was 547 ± 34 &mgr;m. The mean keratometry was 43.6 ± 1.6 diopters (D) in the flattest axis and 44.6 ±1.5 D in the steepest axis. The mean white‐to‐white measurement was 11.7 ± 0.4 mm. The mean flap thickness created by the devices varied between head designs, and microkeratome heads had significant differences (P<.05). Factors that explained 78.4% of the variability included microkeratome model, plate thickness, mean preoperative pachymetry, Kmin, surgery order, head serial number, blade lot number, and surgeon. Factors such as age, sex, Kmax, Kaverage, white to white, and laser had no significant correlation to flap thickness. Conclusions: The results demonstrated variability between the 6 microkeratome models. Device labeling did not necessarily represent the mean flap thickness obtained, nor was it uniform or consistent. Thinner corneas were associated with thinner flaps and thicker corneas with thicker flaps. In addition, first cuts were generally associated with thicker flaps when compared to second cuts in bilateral procedures.

A Statistical Model for iTRAQ Data Analysis

We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change. We demonstrate the models utility based on an analysis of iTRAQ data derived from a spike-in study.

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.

Phase 3 clinical trial investigating the effect of selenium supplementation in men at high‐risk for prostate cancer

This study was conducted to investigate the effect of Se supplementation on prostate cancer incidence in men at high risk for prostate cancer.