Correlation between dental care utilization and oral cavity cancer in a large sample of community-based United States residents

Cancer of the oral cavity and pharynx remains one of the ten leading causes of cancer death in the United States (US). Besides smoking and alcohol consumption, there are no well established risk factors. While poor dental care had been implicated, it is unknown if the lack of dental care, implying poor dental hygiene predisposes to oral cavity cancer. This study aimed to assess the relationship between dental care utilization during the past twelve months and the prevalence of oral cavity cancer. A cross-sectional design of the National Health Interview Survey of adult, non-institutionalized US residents (n=30,475) was used to assess the association between dental care utilization and self reported diagnosis of oral cavity cancer. Chi square statistic was used to examine the crude association between the predictor variable, dental care utilization and other covariates, while unconditional logistic regression was used to assess the relationship between oral cavity cancer and dental care utilization. There were statistically significant differences between those who utilized dental care during the past twelve months and those who did not with respect to education, income, age, marital status, and gender (p < 0.05), but not health insurance coverage (p = 0.53). Also, those who utilized dental care relative to those who did not were 65% less likely to present with oral cavity cancer, prevalence odds ratio (POR), 0.35, 95% Confidence Interval (CI), 0.12–0.98. Further, higher income advanced age, people of African heritage, and unmarried status were statistically significantly associated with oral cavity cancer, (p < 0.05), but health insurance coverage, alcohol use and smoking were not, p > 0.05. However, after simultaneously controlling for the relevant covariates, the association between dental care and oral cavity cancer did not attenuate nor persist. Thus, compared with those who did not use dental care, those who did wee 62% less likely to present with oral cavity cancer adjusted POR, 0.38, 95% CI, 0.13-1.10. Among US adults residing in community settings, use of dental care during the past twelve months did not significantly reduce the predisposition to oral cavity cancer. However, due to the nature of the data used in this study, which restricts temporal sequence, a large sample prospective study that may identify modifiable factors associated with oral cancer development namely poor dental care, is needed. ^

The Role of Cell Sterilization in Population Based Studies of Radiogenic Second Cancers Following Radiation Therapy

Advances in radiotherapy have generated increased interest in comparative studies of treatment techniques and their effectiveness. In this respect, pediatric patients are of specific interest because of their sensitivity to radiation induced second cancers. However, due to the rarity of childhood cancers and the long latency of second cancers, large sample sizes are unavailable for the epidemiological study of contemporary radiotherapy treatments. Additionally, when specific treatments are considered, such as proton therapy, sample sizes are further reduced due to the rareness of such treatments. We propose a method to improve statistical power in micro clinical trials. Specifically, we use a more biologically relevant quantity, cancer equivalent dose (DCE), to estimate risk instead of mean absorbed dose (DMA). Our objective was to demonstrate that when DCE is used fewer subjects are needed for clinical trials. Thus, we compared the impact of DCE vs. DMA on sample size in a virtual clinical trial that estimated risk for second cancer (SC) in the thyroid following craniospinal irradiation (CSI) of pediatric patients using protons vs. photons. Dose reconstruction, risk models, and statistical analysis were used to evaluate SC risk from therapeutic and stray radiation from CSI for 18 patients. Absorbed dose was calculated in two ways: with (1) traditional DMA and (2) with DCE. DCE and DMA values were used to estimate relative risk of SC incidence (RRCE and RRMA, respectively) after proton vs. photon CSI. Ratios of RR for proton vs. photon CSI (RRRCE and RRRMA) were then used in comparative estimations of sample size to determine the minimal number of patients needed to maintain 80% statistical power when using DCE vs. DMA. For all patients, we found that protons substantially reduced the risk of developing a second thyroid cancer when compared to photon therapy. Mean RRR values were 0.052±0.014 and 0.087±0.021 for RRRMA and RRRCE, respectively. However, we did not find that use of DCE reduced the number of patents needed for acceptable statistical power (i.e, 80%). In fact, when considerations were made for RRR values that met equipoise requirements and the need for descriptive statistics, the minimum number of patients needed for a micro-clinical trial increased from 17 using DMA to 37 using DCE. Subsequent analyses revealed that for our sample, the most influential factor in determining variations in sample size was the experimental standard deviation of estimates for RRR across the patient sample. Additionally, because the relative uncertainty in dose from proton CSI was so much larger (on the order of 2000 times larger) than the other uncertainty terms, it dominated the uncertainty in RRR. Thus, we found that use of corrections for cell sterilization, in the form of DCE, may be an important and underappreciated consideration in the design of clinical trials and radio-epidemiological studies. In addition, the accurate application of cell sterilization to thyroid dose was sensitive to variations in absorbed dose, especially for proton CSI, which may stem from errors in patient positioning, range calculation, and other aspects of treatment planning and delivery.

Food availability in the home and dietary intake of the Harris County Department of Education Head Start population

Background. The prevalence of obesity and overweight children has been an ongoing health epidemic in the US for the last several decades. The problem has consistently worsened and has disproportionately been the most prevalent among low socioeconomic status (SES) populations. Food availability in the home has been suggested to be a potential factor related to overweight and obesity, as availability is likely associated with intake. Food availability of low SES preschool aged children has not been well examined. The purpose of this study was to explore the food environment of the Harris County Department of Education (HCDE) Head Start population, and describe reported frequency of intake of particular food groups. The effect of food availability on reported intake was also examined.^ Methods. This was a cross-sectional study of secondary data analysis. Data obtained from 17 HCDE Head Start Centers was analyzed using PASW 18 Statistical Software. Demographic analyses included population, age, gender, race, parent occupation, type of home, and language spoken in the home. Descriptive statistics included reported availability of foods in the home as well as frequency of intake.^ Regression analysis examined the relationship of availability of foods on intake. The food categories included were: dark leafy green and orange vegetables, other vegetables, fruits, soda, salty snacks, and sweet snacks. For both vegetable categories reported intake of fresh, frozen, and canned vegetables were included. For the fruit category, intake of fresh, frozen, canned, and dried fruits were reported.^ Results. Results showed that 90-95% of parents reported having vegetables and fruits available in the home. However, the only significant relationship between availability and intake was for fresh fruit and dried fruit. No associations were seen among the vegetable groups. Other vegetables (bell peppers, eggplant, tomatoes, onions, iceberg lettuce, asparagus) that were frozen, approached significance for availability on intake, however once adjusted for confounders the relationship was no longer present. Among soda, salty snacks, and sweet snacks the only significant relationship was seen for soda availability and intake. Salty snacks and sweet snacks presence in the home was not a predictor of increased frequency of intake.^ Conclusions. This research supported the hypothesis that availability of foods has an impact on intake for fresh fruits, dried fruits and soda. No associations were seen for vegetables, salty snacks and sweet snacks. Additionally, most of the parents reported having fruits and vegetables in the home, but reported intakes were not meeting the Dietary Guidelines for Americans recommendations. Strengths of the study included the large sample size taken from numerous HCDE Head Start Centers. Limitations included questionable reliability of participant’s responses, ability to generalize to other populations, and the use of secondary data rather than prospectively collected data.^

Bayesian inference and its application to meta-analysis of epidemiologic data

In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

FACTORS INFLUENCING THE PATTERNS OF PHYSICIAN VISITS TO NURSING HOME RESIDENTS

This study was designed to identify some of the factors related to patterns of physician visits to nursing home residents. The relationship of ten resident and organizational characteristics to patterns of physician visits was investigated through secondary analysis of data abstracted from the 1973-74 National Nursing Home Survey of the National Center for Health Statistics. The study sample was composed of 11,135 of the 19,013 nursing home residents who participated in the survey.^ The analytic results revealed that all ten variables had a statistically significant relationship to patterns of physician visits, mainly due to the large sample size. The degrees of association between the variables, measured by the Cramer's V statistic, ranged from moderate to very weak.^ Certification status of the nursing home under Medicare and/or Medicaid was shown to be most strongly related to patterns of physician visits, followed by primary source of payment for nursing home care, and residence prior to nursing home admission. Several variables thought to be related to patterns of physician visits were found to have a very weak relationship: age of the resident, marital status, length of stay, primary diagnosis, number of chronic conditions, activities of daily living status, and levels of care.^ In order to get a more precise picture of the relative influence of certification status and primary source of payment when the other variables were statistically controlled, these two variables were combined into a single variable. The results revealed that the combined effects of certification status and primary source of payment were sustained, regardless of differences in the residents' personal, utilization, and health status characteristics, and the levels of care that they received. The results also indicated that the five groups created by combining the two variables differed in patterns of physician visits. For example, private pay residents in intermediate care facilities (ICF's) and non-certified facilities were more likely to receive unscheduled visits than private pay residents in skilled nursing homes (SNH's), residents in SNH's supported by Medicare or Medicaid, and residents in ICF's supported by Medicaid. ^

The response of Texas public health agencies and workers to the emergency preparedness initiatives after 9/11

The purpose of this research was to better understand the impact of the terrorist attacks in 2001 on public health, particularly for Texas public health. This study employed mixed methods to examine changes to public health culture within Texas local public health agencies, important attitudes of public health workers toward responding to a disaster, and the funding policies that might ensure our investment in public health emergency preparedness is protected. ^ A qualitative analysis of interviews conducted with a large sample of public health officials in Texas found that all the constituent parts of a peculiar culture for public health preparedness existed that spanned the state's local health departments regardless of size, or funding level. The new preparedness culture in Texas had the hallmarks necessary for a robust public health preparedness and emergency response system. ^ The willingness of public health workers, necessary to make these kinds of changes and mount a disaster response was examined in one of Texas' most experienced disaster response teams—the public health workers for the City of Houston. A hypothesized latent variable model showed that willingness mediated all other factors in the model (self-efficacy, knowledge, barriers, and risk perception) for self-reported likelihood of reporting to work for a disaster. The RMSEA for the final model was 0.042 with a confidence interval of 0.036—0.049 and the chi-squared difference test was P=0.08, indicating a well-fitted model that suggests willingness is an important factor for consideration by preparedness planners and researchers alike. ^ Finally, with disasters on the rise and federal funding for preparedness dwindling, a review of states' policies for the distribution of these funds and their advantages and disadvantages were examined through a review of current literature and public documents, and a survey of state-level public health officials, emergency management professionals and researchers. Although the base plus per-capita method is the most common, it is not necessarily perceived to be the most effective. No clear "optimal" method emerged from the study, but recommendations for a strategic combination of three methods were made that has the potential to maximize the benefits of each method, while minimizing the weaknesses.^

Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Estimating the mean and standard deviation of concentration distributions using censored samples

Environmental data sets of pollutant concentrations in air, water, and soil frequently include unquantified sample values reported only as being below the analytical method detection limit. These values, referred to as censored values, should be considered in the estimation of distribution parameters as each represents some value of pollutant concentration between zero and the detection limit. Most of the currently accepted methods for estimating the population parameters of environmental data sets containing censored values rely upon the assumption of an underlying normal (or transformed normal) distribution. This assumption can result in unacceptable levels of error in parameter estimation due to the unbounded left tail of the normal distribution. With the beta distribution, which is bounded by the same range of a distribution of concentrations, $\rm\lbrack0\le x\le1\rbrack,$ parameter estimation errors resulting from improper distribution bounds are avoided. This work developed a method that uses the beta distribution to estimate population parameters from censored environmental data sets and evaluated its performance in comparison to currently accepted methods that rely upon an underlying normal (or transformed normal) distribution. Data sets were generated assuming typical values encountered in environmental pollutant evaluation for mean, standard deviation, and number of variates. For each set of model values, data sets were generated assuming that the data was distributed either normally, lognormally, or according to a beta distribution. For varying levels of censoring, two established methods of parameter estimation, regression on normal ordered statistics, and regression on lognormal ordered statistics, were used to estimate the known mean and standard deviation of each data set. The method developed for this study, employing a beta distribution assumption, was also used to estimate parameters and the relative accuracy of all three methods were compared. For data sets of all three distribution types, and for censoring levels up to 50%, the performance of the new method equaled, if not exceeded, the performance of the two established methods. Because of its robustness in parameter estimation regardless of distribution type or censoring level, the method employing the beta distribution should be considered for full development in estimating parameters for censored environmental data sets. ^

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. ^

Dielectrophoretic approaches to sample preparation and analysis

Dielectrophoresis (DEP) has been used to manipulate cells in low-conductivity suspending media using AC electrical fields generated on micro-fabricated electrode arrays. This has created the possibility of performing automatically on a micro-scale more sophisticated cell processing than that currently requiring substantial laboratory equipment, reagent volumes, time, and human intervention. In this research the manipulation of aqueous droplets in an immiscible, low-permittivity suspending medium is described to complement previous work on dielectrophoretic cell manipulation. Such droplets can be used as carriers not only for air- and water-borne samples, contaminants, chemical reagents, viral and gene products, and cells, but also the reagents to process and characterize these samples. A long-term goal of this area of research is to perform chemical and biological assays on automated, micro-scaled devices at or near the point-of-care, which will increase the availability of modern medicine to people who do not have ready access to large medical institutions and decrease the cost and delays associated with that lack of access. In this research I present proofs-of-concept for droplet manipulation and droplet-based biochemical analysis using dielectrophoresis as the motive force. Proofs-of-concept developed for the first time in this research include: (1) showing droplet movement on a two-dimensional array of electrodes, (2) achieving controlled dielectric droplet injection, (3) fusing and reacting droplets, and (4) demonstrating a protein fluorescence assay using micro-droplets. ^

Gender differences in colorectal cancer screening and incidence in large nationwide, population-based cohorts

Background. A few studies have reported gender differences along the colorectal cancer (CRC) continuum but none has done so longitudinally to compare a cancer and a non-cancer populations.^ Objectives and Methods. To examine gender differences in colorectal cancer screening (CRCS); to examine trends in gender differences in CRC screening among two groups of patients (Medicare beneficiaries with and without cancer); to examine gender differences in CRC incidence; and to examine for any differences over time. In Paper 1, the study population consisted of men and women, ages 67–89 years, with CRC (73,666) or without any cancer (39,006), residing in 12 U.S. Surveillance Epidemiology and End-Results (SEER) regions. Crude and age-adjusted percentages and odds ratios of receiving fecal occult blood test (FOBT), sigmoidoscopy (SIG), or colonoscopy (COL) were calculated. Multivariable logistic regression was used to assess gender on the odds of receiving CRC screening over time.^ In Paper 2, age-adjusted incidence rates and proportions over time were reported across race, CRC subsite, CRC stage and SEER region for 373,956 patients, ages 40+ years, residing in 9 SEER regions and diagnosed with malignant CRC. ^ Results. Overall, women had higher CRC screening rates than men and screening rates in general were higher in the SEER sample of persons with CRC diagnosis. Significant temporal divergence in FOBT screening was observed between men and women in both cohorts. Although the largest temporal increases in screening rates were found for COL, especially among the cohort with CRC, little change in the gender gap was observed over time. Receipt of FOBT was significantly associated with female gender especially in the period of full Medicare coverage. Receipt of COL was also significantly associated with male gender, especially in the period of limited Medicare coverage.^ Overall, approximately equal numbers of men (187,973) and women (185,983) were diagnosed with malignant CRC. Men had significantly higher age-adjusted CRC incidence rates than women across all categories of age, race, subsite, stage and SEER region even though rates declined in all categories over time. Significant moderate increases in rate difference occurred among 40-59 year olds; significant reductions occurred among patients age 70+, within subsite rectum, unstaged and distant stage CRC, and eastern and western SEER regions. ^ Conclusions. Persistent gender differences in CRC incidence across time may have implications for gender-based interventions that take age into consideration. A shift toward proximal cancer was observed over time for both genders, but the high proportion of men who develop rectal cancer suggests that a greater proportion of men may need to be targeted with newer screening methods such as fecal DNA or COL. Although previous reports have documented higher CRC screening among men, higher incidence of CRC observed among men suggests that higher risk categories of men are probably not being reached. FOBT utilization rates among women have increased over time and the gender gap has widened between 1998 and 2005. COL utilization is associated with male gender but the differences over time are small.^

A SIMULATION STUDY OF THE SIZE AND POWER OF SOME TWO-SAMPLE TESTS FOR UNEQUALLY CENSORED SURVIVAL DATA (RANK TESTS, LOGRANK, PROPORTIONAL HAZARDS, WILCOXON TESTS, EXPONENTIAL DISTRIBUTION)

Sizes and power of selected two-sample tests of the equality of survival distributions are compared by simulation for small samples from unequally, randomly-censored exponential distributions. The tests investigated include parametric tests (F, Score, Likelihood, Asymptotic), logrank tests (Mantel, Peto-Peto), and Wilcoxon-Type tests (Gehan, Prentice). Equal sized samples, n = 18, 16, 32 with 1000 (size) and 500 (power) simulation trials, are compared for 16 combinations of the censoring proportions 0%, 20%, 40%, and 60%. For n = 8 and 16, the Asymptotic, Peto-Peto, and Wilcoxon tests perform at nominal 5% size expectations, but the F, Score and Mantel tests exceeded 5% size confidence limits for 1/3 of the censoring combinations. For n = 32, all tests showed proper size, with the Peto-Peto test most conservative in the presence of unequal censoring. Powers of all tests are compared for exponential hazard ratios of 1.4 and 2.0. There is little difference in power characteristics of the tests within the classes of tests considered. The Mantel test showed 90% to 95% power efficiency relative to parametric tests. Wilcoxon-type tests have the lowest relative power but are robust to differential censoring patterns. A modified Peto-Peto test shows power comparable to the Mantel test. For n = 32, a specific Weibull-exponential comparison of crossing survival curves suggests that the relative powers of logrank and Wilcoxon-type tests are dependent on the scale parameter of the Weibull distribution. Wilcoxon-type tests appear more powerful than logrank tests in the case of late-crossing and less powerful for early-crossing survival curves. Guidelines for the appropriate selection of two-sample tests are given. ^

A PROPOSED SAMPLE-BASED TECHNIQUE TO ESTIMATE THE STANDARDIZED MORTALITY RATIO

Evaluation of a series of deaths due to a particular disease is a frequently requested task in occupational epidemiology. There are several techniques available to determine whether a series represents an occupational health problem. Each of these techniques, however, is subject to certain limitations including cost, applicability to a given situation, feasibility relative to available resources, or potential for bias. In light of these problems, a technique was developed to estimate the standardized mortality ratio at a greatly reduced cost. The technique is demonstrated by its application in the investigation of brain cancer among employees of a large chemical company. ^

Association of ALLHAT investigator characteristics with participant recruitment

Clinical trials are often not successful because of the inability to recruit a sufficient number of patients. The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), the largest antihypertensive trial ever conducted, provided highly generalized results and successful recruitment of over 42,000 participants. The overall purpose of this study was to examine the association of investigator characteristics with anti-hypertensive (AHT) participant recruitment in ALLHAT. This secondary data analyses collected data from the ALLHAT investigator profile survey and related investigator characteristics to recruitment success. The sample size was 502 investigators, with recruitment data from 37,947AHT participants. Recruitment was dichotomized by categorizing all sites with recruitment numbers at or above the overall median recruitment number of 46 as "Successful Recruitment". Frequency distributions and univariate and multivariate logistic regression were conducted. When adjusting for all other factors, Hispanic ethnicity, suburban setting, Department of Veterans Affairs Medical Centers (VAMC) site type, number of clinical site staff working on the trial, study coordinator hours per week, medical conference sessions attended, the investigator's primary goal and the likelihood that a physician will convince a patient to continue on randomized treatment, have significant impacts on the recruitment success of ALLHAT investigators. Most of the ALLHAT investigators described their primary commitment as being towards their patients and not to scientific knowledge alone. However, investigators that distinguished themselves as leaders in research had greater recruitment success than investigators who were leaders in clinical practice. ALLHAT was a highly successful trial that proved that community based cardiovascular trials can be implemented on a large scale. Exploring characteristics of ALLHAT investigators provides data that can be generalized to sponsors, sites, and others interested in maximizing clinical trial recruitment numbers. Future studies should further evaluate investigator and study coordinator factors that impact cardiovascular clinical trial recruitment success.^