Browsing by Subject "Screening"

Now showing 1 - 11 of 11
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    Breast Cancer Screening: Your Guide To Health
    (2010-07-22) Flaten, Dean B
    Mammography has consistently been proven to be an effective and safe method of screening women 50 and older for breast cancer. However, this study found that annual screening with mammography for women in their 40’s was not effective at reducing breast cancer mortality compared with women who undergo usual care with breast physical examination and breast self-examination. In general then, universal screening mammography for women in their 40’s should not be mandate, but rather an informed, personal decision between the physician and patient based on individual concerns, family history and acceptable risk/benefit profiles.
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    Colorectal Cancer Screening in the US: The Impact of Oversurveillance, Physician Supply and Coverage Mandates
    (2015-10) Abban, Bartholomew
    Screening for precursor adenomatous polyps has been proven to be effective in reducing colorectal cancer mortality risk. Although most screening guidelines do not recommend any one of the several screening tests for CRC over the others, colonoscopy increasingly is being adopted as the primary test for screening. In addition, colonoscopy is recommended for post-polypectomy and post-colectomy surveillance of colorectal cancer. Despite the considerable evidence supporting the effectiveness of screening for CRC, its uptake has lagged considerably behind that of breast cancer screening. Over the past twenty years, the Department of Health and Human Services (DHHS), the Centers for Disease Control and Prevention (CDC) and many national, state and local organizations have embarked on several programs and campaigns in a bid to raise awareness about colorectal cancer and increase screening uptake. At the same time, there is a growing concern that the current physician supply is inadequate to support a broader colonoscopy-based screening and surveillance. This research examines these concerns from three fronts. First, we use a population-based state-transition Markov model of the natural history of colorectal cancer, applied to census data and prevailing screening guidelines, to forecast the demand for colonoscopy and examine the impact of premature post-polypectomy CRC surveillance on the annual volume of colonoscopies. Second, we combine the Behavioral Risk Factor Surveillance System (BRFSS) survey with physician resource data to examine the conditional effect of county-level physician supply on screening participation. Third, we use longitudinal BRFSS survey data to estimate the effect of the policy of state-mandated colorectal cancer screening benefit by health insurers on the probability of an insured individual undergoing screening.
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    Comparison of placement decisions based on picture Naming 1.0 and Picture Naming 2.0
    (2014-06) Besner, Amanda
    Learning to read is a lifelong skill that begins during early childhood. There are a number of foundational skills that children should have before they start kindergarten in order to ensure that they are able to be successful during later reading instruction. These skills are often referred to as early literacy skills, include skills such as expressive and receptive vocabulary. It is critical to identify preschool children with delays in vocabulary and provide them with additional instruction. The screening process involved in a Response to Intervention (RTI) framework provides a means for identifying students who need addition instruction. The purpose of this study is evaluate to two different screening measures of vocabulary in order to evaluate their classification accuracy, or their ability to discriminate between students who need additional instruction or those who are making adequate progress in the general classroom. Classification accuracy of the two versions of Picture Naming differed by analysis, with Picture Naming 1.0 demonstrating greater sensitivity and specificity, while Picture Naming 2.0 demonstrated a higher AUC value and more promising ROC curve.
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    Evaluating bias caused by screening in observational risk-factor studies of lung cancer nested in the PLCO randomized screening trial.
    (2009-09) Jansen, Ricky Jeffrey
    It is well-known that bias such as lead-time and length distort studies of screening efficacy whether survival or incidence is of interest. A third bias, usually called overdiagnosis bias, occurs when an individual is only diagnosed with disease before death from a different cause because he/she is screened. These forms of bias can also arise in observational studies where the proportion screened and screening rates vary by risk-factor strata. This difference in screening behaviors influences corresponding case ascertainment or case enrollment probabilities which can lead to erroneous conclusions about the size of the risk-factor effect on the disease. It has been suggested that classic confounding occurs in such risk-factor studies when screening is efficacious; therefore, it can be addressed by conventional analyses such as stratification or confounder adjustment in regression models. However, even if the test is not efficacious, screening creates changes in case ascertainment probabilities which must be addressed using alternative methods. Recurrence-time models, long used for screening programs, can be adapted to model the affect screening use has on risk-factor studies. These models can be used to study the magnitude of potential bias, but may also be adapted to provide an analytic approach to correct estimates for such bias. The risk-factor studies nested in the PLCO trial are potentially affected by such bias, and this randomized study also provides a structure within which models of screening bias may be tested and validated. To validate our model, a variety of nested case-control studies will be developed that measure the effect smoking has on lung cancer and the degree to which the bias affecting those estimates change based on the study design will be determined. This process will include a) expanding a previously developed lead-time bias model to incorporate length and overdiagnosis; b) incorporating a more flexible and realistic model of screening that can incorporate the patterns documented in the PLCO trial; c) exploring if the mathematical model is valid using varied nested study designs within PLCO and comparing resulting logistic regression estimates to simulated results; and d) using the validated models to produce correction factors for use in other nested risk-factor studies. Results indicate that the mathematical model is highly sensitive to overdiagnosis as increasing rates increase expected bias, but relatively insensitive to using different screening test sensitivities. Increasing screening behavior differential during the study, preclinical duration length, and selecting from the intervention group are associated with increasing expected screening bias. Increasing screening behavior before the study and selecting from the usual-care group are associated with a decreasing expected screening bias. Although the mathematical model couldn't be validated as a correction factor here, the results suggest using a shorter preclinical duration distribution for the model may produce more accurate screening bias values. The focus of this work was to identify if chest x-ray screening could modify the estimated risk of smoking on lung cancer diagnosis. An additional goal was to develop a usable method for adjusting observational studies of lung cancer for the bias arising from differential chest x-ray screening between ever and never smoking groups. In a boarder sense, this work has provided an explanation of the effect screening use may have on an observational risk-factor study and an example of how to implement the mathematical technique. Additionally, this project has provided a more general method for doing sensitivity analyses on the screening related assumptions involved with these studies, whether nested in a randomized trial or sampled from the population at large.
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    No Screening for Lung Cancer
    (2009-05-06) Lackner, Josh
    The most recent assessment of available evidence on lung cancer screening with a sensitive modality (computed tomography) found that we cannot conclude that such screening provides a mortality benefit. The main reason for this, is that there is no available trial that compares CT screening to no screening over an adequate duration of time. Of note, false positive results were very common and tumors found on screening had different characteristics from those found clinically.
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    Statistical and mathematical modeling to evaluate the cost-effectiveness of Helicobacter pylori screening and treating strategies in Mexico in the setting of antibiotic resistance
    (2017-08) Alarid Escudero, Fernando
    Helicobacter pylori (H. pylori), a bacterium that is present in the stomach of half of the world’s population with disproportionate burden in developing countries, is the strongest known biological risk factor for gastric cancer. Gastric cancer is the fourth most common type of cancer and the second cause of cancer death in the world. In particular, in Mexico gastric cancer is the third highest cause of cancer death in adults, with some regions having cancer mortality rates that are twice the national average (8.0 vs. 3.9 per 100,000, respectively). H. pylori can be treated with antibiotics, but widespread treatment may lead to significant levels of antibiotic resistance (ABR). ABR is one of the main causes of H. pylori treatment failure and represents one of the greatest emerging global health threats. In this thesis, we use statistical and mathematical modeling to investigate the health benefits, harms, costs and cost-effectiveness of screen-and-treat strategies for identifying and treating persons with H. pylori to inform public health practice in three steps. First, we estimated the age-specific force of infection of H. pylori --defined as the instantaneous per capita rate at which susceptibles acquire infection-- using a novel hierarchical nonlinear Bayesian catalytic epidemic model with data from a national H. pylori seroepidemiology survey in Mexico. Second, we developed an age-structured, susceptible-infected-susceptible (SIS) transmission model of H. pylori infection in Mexico that included both treatment-sensitive and treatment-resistant strains. Model parameters were derived from the published literature and estimated from primary data. Using the model, we projected H. pylori infection and resistance levels over 20 years without treatment and for three hypothetical population-wide treatment policies assumed to be implemented in 2018. In sensitivity analyses, we considered different mixing patterns and trends of background antibiotic use. We validated the model against historical values of prevalence of infection and ABR of H. pylori. Third, we expanded the SIS model to incorporate the natural history of gastric carcinogenesis including gastritis, intestinal metaplasia, dysplasia and ultimately non-cardia gastric cancer. We then estimated the cost-effectiveness of various screen-and-treat strategies for H. pylori infection and ABR in the Mexican population from the health sector perspective.
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    The utility of skinfold thickness for estimating insulin resistance and serum triglycerides in adolescents
    (2010-12) Addo, Oppong Yaw
    Skinfold thickness has long been found to be highly correlated with total body fat. Yet it remains largely underutilized in comparison to other anthropometric measures. The ability of skinfold thickness to characterize adiposity-related health outcomes should contribute to its utility in studying these outcomes. Objective: To determine comparability of skinfold thickness with whole body total fat, measured by dual energy X-ray absorptiometry (DXA), and their relationships with insulin resistance and serum triglyceride levels in a large sample of US adolescents. The utility of skinfold thickness was evaluated by determining optimum subscapular percentile-cut points for identifying adolescents who are at risk of elevated insulin resistance. Methods: Pooled serial cross-sectional data from the continuous National Health and Nutrition Examination Survey (NHANES) cycles 2001-04 were analyzed. Primary data used included skinfold thicknesses, DXA-based total body fat (DXF), serum insulin and fasting glucose (for homeostasis model assessment of insulin resistance; HOMA-IR), and serum triglycerides. Data from a total of approximately 1500 US youths aged 12-18 years were used in this work. Findings from manuscript one demonstrated that skinfold thickness is comparably associated with both continuous HOMA and the upper quintile of elevated insulin resistance in adolescents as total body fat weight measured with DXA. Similarly, in manuscript two skinfold thickness was comparable to DXA in associations with variation in serum triglycerides, and in predicting adolescents who have elevated serum triglyceride levels. Additionally, subscapular skinfold was found to be better at identifying adolescent girls at risk of elevated serum triglyceride levels than DXA whole-body fat weight. In manuscript three, subscapular skinfold thickness was found to be sufficiently correlated with HOMA-IR to justify identification of age- and sex-specific percentile cut-offs for identifying elevated insulin resistance in adolescents. These new subscapular skinfold percentile cut-offs can be used as a screening tool for identifying US adolescents at risk of elevated insulin resistance, who can then be referred for subsequent follow-up and diagnostic studies. Findings from this dissertation have demonstrated that skinfolds are amply correlated with insulin resistance and serum triglyceride levels, thus supporting their wider use in anthropometric assessment of obesity and its related health outcomes in adolescents.
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    Variable selection in high-dimensional classification
    (2013-06) Mai, Qing
    Classification has long been an important research topic for statisticians. Nowadays, scientists are further challenged by classification problems for high-dimensional datasets in various fields, ranging from genomics, economics to machine learning. For such massive datasets, classical classification techniques may be inefficient or even infeasible, while new techniques are highly sought-after. My dissertation work tackles high-dimensional classification problems by utilizing variable selection. In particular, three methods are proposed and studied: direct sparse discriminant analysis, semiparametric sparse discriminant analysis and the Kolmogorov filter. In the proposal of direct sparse discriminant analysis (DSDA), I first point out the disadvantage in many current methods that they ignore the correlation structure between predictors. Then DSDA is proposed to extend the well-known linear discriminant analysis to high dimensions, fully respecting the correlation structure. The proposal is efficient and consistent, with excellent numerical performance. In addition to the proposal of DSDA, I also study its connection to many popular proposals of linear discriminant analysis in high dimensions, including the L1-Fisher's discriminant analysis and the sparse optimal scoring. Semiparametric sparse discriminant analysis (SeSDA) extends DSDA by relaxing the normality assumption, which is fundamental for any method requiring the linear discriminant analysis model. SeSDA is more robust than DSDA, while it preserves the good properties of DSDA. Along with the development of SeSDA, a new concentration inequality is obtained that can provide theoretical justifications for methods based on Gaussian copulas. Moreover, the Kolmogorov filter is proposed as a fully nonparametric method that performs variable selection for high-dimensional classification. It requires minimal assumptions on the distribution of the predictors, and is supported by both theoretical and numerical examples. Also, some potential future work is discussed on variable selection in classification.
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    What do I need to know about Testicular Cancer?
    (2009-08-19) Savard, Elizabeth Koffel
    Screening for testicular cancer screening in men is not necessary because it is a fairly rare disease with an impressively high cure rate. It is also usually found by the patient or his sexual partner without any screening exam. However, patients must be educated on how it may present so that they do go see their physician as early as possible. Some additional information on risk factors is also included.