964 resultados para statistic
Resumo:
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. ^
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Critically ill and injured patients require pain relief and sedation to reduce the body's stress response and to facilitate painful diagnostic and therapeutic procedures. Presently, the level of sedation and analgesia is guided by the use of clinical scores which can be unreliable. There is therefore, a need for an objective measure of sedation and analgesia. The Bispectral Index (BIS) and Patient State Index (PSI) were recently introduced into clinical practice as objective measures of the depth of analgesia and sedation. ^ Aim. To compare the different measures of sedation and analgesia (BIS and PSI) to the standard and commonly used modified Ramsay Score (MRS) and determine if the monitors can be used interchangeably. ^ Methods. MRS, BIS and PSI values were obtained in 50 postoperative cardiac surgery patients requiring analgesia and sedation from June to December 2004. The MRS, BIS and PSI values were assessed hourly for up to 6-h by a single observer. ^ The relationship between BIS and PSI values were explored using scatter plots and correlation between MRS, BIS and PSI was determined using Spearman's correlation coefficient. Intra-class correlation (ICC) was used to determine the inter-rater reliability of MRS, BIS and PSI. Kappa statistics was used to further evaluate the agreement between BIS and PSI at light, moderate and deep levels of sedation. ^ Results. There was a positive correlation between BIS and PSI values (Rho = 0.731, p<0.001). Intra-class correlation between BIS and PSI was 0.58, MRS and BIS 0.43 and MRS and PSI 0.27. Using Kappa statistics, agreement between MRS and BIS was 0.35 (95% CI: 0.27–0.43) and for MRS and PSI was 0.21 (95% CI: 0.15–0.28). The kappa statistic for BIS and PSI was 0.45 (95% CI: 0.37–0.52). Receiver operating characteristics (ROC) curves constructed to detect undersedation indicated an area under the curve (AUC) of 0.91 (95% CI = 0.87 to 0.94) for the BIS and 0.84 (95% CI = 0.79 to 0.88) for the PSI. For detection of oversedation, AUC for the BIS was 0.89 (95% CI = 0.84 to 0.92) and 0.80 (95% CI = 0.75 to 0.85) for the PSI. ^ Conclusions. There is a statistically significant positive correlation between the BIS and PSI but poor correlation and poor test agreement between the MRS and BIS as well as MRS and PSI. Both the BIS and PSI demonstrated a high level of prediction for undersedation and oversedation; however, the BIS and PSI can not be considered interchangeable monitors of sedation. ^
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Background. Liver cancer mortality continues to be a significant factor in deaths worldwide and in the U.S., yet there remains a lack of studies on how mortality burden is impacted by racial groups or by heavy alcohol use. This study evaluated the geographic distribution of liver cancer mortality across population groups in Texas and the U.S. over a 24-year period, as well as determining whether alcohol dependence or abuse correlates with mortality rates. ^ Methods. The Spatial Scan Statistic was used to identify regions of excess liver cancer mortality in Texas counties and the U.S. from 1980 to 2003. The statistic was conducted with a spatial cluster size of 50% of the population at risk, and all analyses used publicly available data. Alcohol abuse data by state and ethnicity were extracted from SAMHSA datasets for the study period 2000–2004. ^ Results. The results of the geographic analysis of liver cancer mortality in both Texas and the U.S. indicate that there were four and seven regions, respectively, that were identified as having statistically significant excess mortality rates with elevated relative risks ranging from 1.38–2.07 and 1.05–1.623 (p = 0.001), respectively. ^ Conclusion. This study revealed seven regions of excess mortality of liver cancer mortality across the U.S. and four regions of excess mortality in Texas between 1980–2003, as well as demonstrated a correlation between elevated liver cancer mortality rates and reporting of alcohol dependence among Hispanics and Other populations. ^
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In epidemiology literature, it is often required to investigate the relationships between means where the levels of experiment are actually monotone sets forming a partition on the range of sampling values. With this need, the analysis of these group means is generally performed using classical analysis of variance (ANOVA). However, this method has never been challenged. In this dissertation, we will formulate and present our examination of its validity. First, the classical assumptions of normality and constant variance are not always true. Second, under the null hypothesis of equal means, the test statistic for the classical ANOVA technique is still valid. Third, when the hypothesis of equal means is rejected, the classical analysis techniques for hypotheses of contrasts are not valid. Fourth, under the alternative hypothesis, we can show that the monotone property of levels leads to the conclusion that the means are monotone. Fifth, we propose an appropriate method for handing the data in this situation. ^
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Two studies among college students were conducted to evaluate appropriate measurement methods for etiological research on computing-related upper extremity musculoskeletal disorders (UEMSDs). ^ A cross-sectional study among 100 graduate students evaluated the utility of symptoms surveys (a VAS scale and 5-point Likert scale) compared with two UEMSD clinical classification systems (Gerr and Moore protocols). The two symptom measures were highly concordant (Lin's rho = 0.54; Spearman's r = 0.72); the two clinical protocols were moderately concordant (Cohen's kappa = 0.50). Sensitivity and specificity, endorsed by Youden's J statistic, did not reveal much agreement between the symptoms surveys and clinical examinations. It cannot be concluded self-report symptoms surveys can be used as surrogate for clinical examinations. ^ A pilot repeated measures study conducted among 30 undergraduate students evaluated computing exposure measurement methods. Key findings are: temporal variations in symptoms, the odds of experiencing symptoms increased with every hour of computer use (adjOR = 1.1, p < .10) and every stretch break taken (adjOR = 1.3, p < .10). When measuring posture using the Computer Use Checklist, a positive association with symptoms was observed (adjOR = 1.3, p < 0.10), while measuring posture using a modified Rapid Upper Limb Assessment produced unexpected and inconsistent associations. The findings were inconclusive in identifying an appropriate posture assessment or superior conceptualization of computer use exposure. ^ A cross-sectional study of 166 graduate students evaluated the comparability of graduate students to College Computing & Health surveys administered to undergraduate students. Fifty-five percent reported computing-related pain and functional limitations. Years of computer use in graduate school and number of years in school where weekly computer use was ≥ 10 hours were associated with pain within an hour of computing in logistic regression analyses. The findings are consistent with current literature on both undergraduate and graduate students. ^
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Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^
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Background. Poor nutrition is an important factor in the onset of obesity which is a growing problem in the United States that disproportionately affects Mexican-Americans. In order to form recommendations and effectively target nutrition in interventions it is necessary to have valid epidemiological tools to better understand dietary trends. Purpose. The purpose of this study is to evaluate the validity of the nutritional intake questions from the Tu Salud, ¡Sí Cuenta! Questionnaire in an adult Mexican-American population. Methods. Fifty participants in the Cameron County Hispanic Cohort were recruited into the validity study, which consisted of completing the Tu Salud, ¡Sí Cuenta! questionnaire and the 24-hour recall with a 2 hour time period between administrations. Responses were analyzed to determine the percent agreement, kappa statistic and Spearman rank order correlation. Results: Five items had good validity (>0.6), three items had fair validity (>0.4), and three items had poor validity (<0.4). In general, items that had low validity were those that were reported in low frequencies by study subjects. Overall, the Tu Salud, ¡Sí Cuenta! questionnaire showed good validity, making this questionnaire a valuable tool to assess the dietary intake patterns of this Mexican-American adult population. ^
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In order to better take advantage of the abundant results from large-scale genomic association studies, investigators are turning to a genetic risk score (GRS) method in order to combine the information from common modest-effect risk alleles into an efficient risk assessment statistic. The statistical properties of these GRSs are poorly understood. As a first step toward a better understanding of GRSs, a systematic analysis of recent investigations using a GRS was undertaken. GRS studies were searched in the areas of coronary heart disease (CHD), cancer, and other common diseases using bibliographic databases and by hand-searching reference lists and journals. Twenty-one independent case-control studies, cohort studies, and simulation studies (12 in CHD, 9 in other diseases) were identified. The underlying statistical assumptions of the GRS using the experience of the Framingham risk score were investigated. Improvements in the construction of a GRS guided by the concept of composite indicators are discussed. The GRS will be a promising risk assessment tool to improve prediction and diagnosis of common diseases.^
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This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^
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Background. About a third of the world’s population is infected with tuberculosis (TB) with sub-Saharan Africa being the worst hit. Uganda is ranked 16th among the countries with the biggest TB burden. The burden in children however has not been determined. The burden of TB has been worsened by the advent of HIV and TB is the leading cause of mortality in HIV infected individuals. Development of TB disease can be prevented if TB is diagnosed during its latent stage and treated with isoniazid. For over a century, latent TB infection (LTBI) was diagnosed using the Tuberculin Skin Test (TST). New interferon gamma release assays (IGRA) have been approved by FDA for the diagnosis of LTBI and adult studies have shown that IGRAs are superior to the TST but there have been few studies in children especially in areas of high TB and HIV endemicity. ^ Objective. The objective of this study was to examine whether the IGRAs had a role in LTBI diagnosis in HIV infected children in Uganda. ^ Methods. Three hundred and eighty one (381) children were recruited at the Baylor College of Medicine-Bristol Meyers Squibb Children’s Clinical Center of Excellence at Mulago Hospital, Kampala, Uganda between March and August 2010. All the children were subjected to a TST and T-SPOT ®.TB test which was the IGRA chosen for this study. Sputum examination and chest x-rays were also done to rule out active TB. ^ Results. There was no statistically significant difference between the tests. The agreement between the two assays was 95.9% and the kappa statistic was 0.7 (95% CI: 0.55–0.85, p-value<0.05) indicating a substantial or good agreement. The TST was associated with older age and higher weight for age z-scores but the T-SPOT®. TB was not. Both tests were associated with history of taking anti-retroviral therapy (ART). ^ Conclusion. Before promoting use of IGRAs in children living in HIV/TB endemic countries, more research needs to be done. ^
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Introduction. Cancer registries provide information about treatment initiation but not the full course of treatment. In an effort to identify patient reported reasons for discontinuing cancer treatment, patients with prostate, breast, and colorectal cancer were identified from Alabama State Cancer Registry (ASCR) -Alabama Medicare linked database for interview. This study has two specific aims: (1) determine whether the ASCR-Medicare database accurately reflects patients’ treatment experiences in terms of whether they started and completed treatment when compared to patient self-report and (2) determine which patient demographic and health care system factors are related to treatment completion as defined by patient self-report. ^ Methods. The ASCR-Medicare claims dataset supplemented patient interview responses to identify treatment initiation and completion among prostate, breast, and colorectal cancer patients in Alabama from 1999-2003. Kappa statistic was used to test for concordance of treatment initiation and completion between patient self-report and Medicare claims data. Patients who reported not completing treatment were asked questions to ascertain reasons for treatment discontinuation. Logistic regression models were constructed to explore the association of patient and tumor characteristics with discontinuation of radiation and chemotherapy. ^ Results. Overall, there was a fair agreement across all cancer sites about whether one had surgery (Kappa=.382). There was fair agreement between self-report and Medicare claims data for starting radiation treatment (Kappa=.278). For starting chemotherapy there was moderate agreement (Kappa=.414). There was no agreement for completing treatment for radiation and chemotherapy between the self-report and claims data. Patients most often reported doctor’s recommendation (40% for radiation treatment and 21.4% for chemotherapy) and side effects (30% for radiation treatment and 42.8% for chemotherapy) for discontinuing treatment. Females were less likely to complete radiation than males (OR=.24, 95% CI=.11–.50). Stage I patients were more likely to drop radiation treatment than stage III patients (OR=3.34, 95% CI=1.12–9.95). Younger patients were more likely to discontinue chemotherapy than older patients (OR=2.84 95%, CI=1.08–7.69) and breast cancer patients were less likely to discontinue chemotherapy than colorectal patients (OR=.13, 95% CI=.04–.46). ^ Conclusion. This study reveals that patients recall starting treatment more accurately than completing treatment and that there are several demographic and tumor characteristics that influence treatment discontinuation. Providing patients with treatment summaries and survivorship plans can help patients their follow-up care when there are gaps in treatment recall and discontinuation of treatment.^
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Introduction. Cancer is the second most common cause of death in the USA (2). Studies have shown a coexistence of cancer and hypogonadism (9,31,13). The majority of patients with cancer develop cachexia, which cannot be solely explained by anorexia seen in these patients. Testosterone is a male sex hormone which is known to increase muscle mass and strength, maintain cancellous bone mass, and increase cortical bone mass, in addition to improving libido, sexual desire, and fantasy (14). If a high prevalence of hypogonadism is detected in male cancer patients, and a significant difference exists in testosterone levels in cancer patients with cachexia versus those without cachexia, testosterone may be administered in future randomized trials to help alleviate cachexia. Study group and design The study group consisted of male cancer patients and non-cancer controls aged between 40 and 70 years. The primary study design was cross-sectional with a sample size of 135. The present data analysis is done on a subset convenience sample of 72 patients recruited between November 2006 and January 2010. ^ Methods. Patients aged 40-70 years with or without a diagnosis of cancer were recruited into the study. All patients with a BMI over 35, significant edema, non-melanomatous skin cancer, current alcohol or illicit drug abuse, concomitant usage of medications interfering with gonadal axis, and anabolic agents, patients on tube feeds or parenteral nutrition within 3 months prior to enrollment were excluded from the study. The study was approved by the Institutional Review Board of Baylor College of Medicine and is being conducted at the Michael E. DeBakey Veterans Affairs Medical Center at Houston. My thesis is a pilot data analysis that employs a smaller subset convenience sample of 72 patients determined by using the data available for the 72 patients (of the intended sample of 135 patients) recruited between November 2006 and January 2010. The primary aim of this analysis is to compare the proportion of patients with hypogonadism in the male cancer and non-cancer control groups, and to evaluate if a significant difference exists with respect to testosterone levels in male cancer patients with cachexia versus those without cachexia. The procedures of the study relevant to the current data analysis included blood collection to measure levels of testosterone and measurement of body weight to categorize cancer patients into cancer cachexia and cancer non-cachexia sub-groups. ^ Results. After logarithmic transformation of data of cancer and control groups, the unpaired t test with unequal variances was done. The proportion of patients with hypogonadism in the male cancer and non-cancer control groups was 47.5% and 22.7% with a Pearson chi2 statistic of 1.6036 and a p value of 0.205. Comparing the mean calculated Bioavailable testosterone in male cancer patients and non-cancer controls resulted in a t statistic of 21.83 and a p value less than 0.001. When the cancer group alone was taken, the mean free testosterone, calculated bioavailable testosterone and total testosterone levels in the cancer non-cachexia sub-group were 3.93, 5.09, 103.51 respectively and in the cancer cachexia sub-group were 3.58, 4.17, 84.08 respectively. The unpaired t test with equal variances showed that the two sub-groups had p values of 0.2015, 0.1842, and 0.4894 with respect to calculated bioavailable testosterone, free testosterone, and total testosterone respectively. ^ Conclusions. The small sample size of this exploratory study, resulting in a small power, does not allow us to draw definitive conclusions. For the given sub-sample, the proportion of patients with hypogonadism in the cancer group was not significantly different from that of patients with hypogonadism in the control group. Inferences on prevalence of hypogonadism in male cancer patients could not be made in this paper as the sub-sample is small and therefore not representative of the general population. However, there was a statistically significant difference in calculated Bioavailable testosterone levels in male cancer patients versus non-cancer controls. Analysis of cachectic and non-cachectic patients within the male cancer group showed no significant difference in testosterone levels (total, free, and calculated bioavailable testosterone) between both sub-groups. However, to re-iterate, this study is exploratory and the results may change once the complete dataset is obtained and analyzed. It however serves as a good template to guide further research and analysis.^
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Coalescent theory represents the most significant progress in theoretical population genetics in the past three decades. The coalescent theory states that all genes or alleles in a given population are ultimately inherited from a single ancestor shared by all members of the population, known as the most recent common ancestor. It is now widely recognized as a cornerstone for rigorous statistical analyses of molecular data from population [1]. The scientists have developed a large number of coalescent models and methods[2,3,4,5,6], which are not only applied in coalescent analysis and process, but also in today’s population genetics and genome studies, even public health. The thesis aims at completing a statistical framework based on computers for coalescent analysis. This framework provides a large number of coalescent models and statistic methods to assist students and researchers in coalescent analysis, whose results are presented in various formats as texts, graphics and printed pages. In particular, it also supports to create new coalescent models and statistical methods. ^
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Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^
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An extension of k-ratio multiple comparison methods to rank-based analyses is described. The new method is analogous to the Duncan-Godbold approximate k-ratio procedure for unequal sample sizes or correlated means. The close parallel of the new methods to the Duncan-Godbold approach is shown by demonstrating that they are based upon different parameterizations as starting points.^ A semi-parametric basis for the new methods is shown by starting from the Cox proportional hazards model, using Wald statistics. From there the log-rank and Gehan-Breslow-Wilcoxon methods may be seen as score statistic based methods.^ Simulations and analysis of a published data set are used to show the performance of the new methods. ^