SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

A PROCESS FOR ACHIEVING COMPARABLE DATA FROM HETEROGENEOUS DATABASES

The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, collected for different purposes and represented differently, that are presently impossible to share or analyze in toto. The greatest challenge for large-scale and meaningful analyses of health-related data is to achieve a uniform data representation for data extracted from heterogeneous source representations. Based upon an analysis and categorization of heterogeneities, a process for achieving comparable data content by using a uniform terminological representation is developed. This process addresses the types of representational heterogeneities that commonly arise in healthcare data integration problems. Specifically, this process uses a reference terminology, and associated "maps" to transform heterogeneous data to a standard representation for comparability and secondary use. The capture of quality and precision of the “maps” between local terms and reference terminology concepts enhances the meaning of the aggregated data, empowering end users with better-informed queries for subsequent analyses. A data integration case study in the domain of pediatric asthma illustrates the development and use of a reference terminology for creating comparable data from heterogeneous source representations. The contribution of this research is a generalized process for the integration of data from heterogeneous source representations, and this process can be applied and extended to other problems where heterogeneous data needs to be merged.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

EVALUATION OF INTENSITY MODULATED RADIATION THERAPY (IMRT) DELIVERY ERROR DUE TO IMRT TREATMENT PLAN COMPLEXITY AND IMPROPERLY MATCHED DOSIMETRY DATA

Intensity modulated radiation therapy (IMRT) is a technique that delivers a highly conformal dose distribution to a target volume while attempting to maximally spare the surrounding normal tissues. IMRT is a common treatment modality used for treating head and neck (H&N) cancers, and the presence of many critical structures in this region requires accurate treatment delivery. The Radiological Physics Center (RPC) acts as both a remote and on-site quality assurance agency that credentials institutions participating in clinical trials. To date, about 30% of all IMRT participants have failed the RPC’s remote audit using the IMRT H&N phantom. The purpose of this project is to evaluate possible causes of H&N IMRT delivery errors observed by the RPC, specifically IMRT treatment plan complexity and the use of improper dosimetry data from machines that were thought to be matched but in reality were not. Eight H&N IMRT plans with a range of complexity defined by total MU (1460-3466), number of segments (54-225), and modulation complexity scores (MCS) (0.181-0.609) were created in Pinnacle v.8m. These plans were delivered to the RPC’s H&N phantom on a single Varian Clinac. One of the IMRT plans (1851 MU, 88 segments, and MCS=0.469) was equivalent to the median H&N plan from 130 previous RPC H&N phantom irradiations. This average IMRT plan was also delivered on four matched Varian Clinac machines and the dose distribution calculated using a different 6MV beam model. Radiochromic film and TLD within the phantom were used to analyze the dose profiles and absolute doses, respectively. The measured and calculated were compared to evaluate the dosimetric accuracy. All deliveries met the RPC acceptance criteria of ±7% absolute dose difference and 4 mm distance-to-agreement (DTA). Additionally, gamma index analysis was performed for all deliveries using a ±7%/4mm and ±5%/3mm criteria. Increasing the treatment plan complexity by varying the MU, number of segments, or varying the MCS resulted in no clear trend toward an increase in dosimetric error determined by the absolute dose difference, DTA, or gamma index. Varying the delivery machines as well as the beam model (use of a Clinac 6EX 6MV beam model vs. Clinac 21EX 6MV model), also did not show any clear trend towards an increased dosimetric error using the same criteria indicated above.

Does Immediate Access to Birth Control Help Prevent Pregnancy? A Comparison of Onsite Provision Versus Off Campus Referral for Contraception at Two School-Based Clinics

PURPOSE: The purpose of this study was to assess the impact of different policies on access to hormonal contraception and pregnancy rates at two high school-based clinics. METHODS: Two clinics in high schools (Schools A and B), located in a large urban district in the southwest US, provide primary medical care to enrolled students with parental consent; the majority of whom have no health insurance coverage. The hormonal contraceptive dispensing policy of at School clinic A involves providing barrier, hormonal and emergency contraceptive services on site. School clinic B uses a referral policy that directs students to obtain contraception at an off-campus affiliated family planning clinic. Baseline data (age, race and history of prior pregnancy) on female students seeking hormonal contraception at the two clinics between 9/2008-12/2009 were extracted from an electronic administrative database (AHLERS Integrated System). Data on birth control use and pregnancy tests for each student was then tracked electronically through 3/31/2010. The outcomes measures were accessing hormonal contraception and positive pregnancy tests at any point during or after birth control use were started through 12/2009. The appointment keeping rate for contraceptive services and the overall pregnancy rates were compared between the two schools. In addition the pregnancy rates were compared between the two schools for students with and without a prior history of pregnancy. RESULTS: School clinic A: 79 students sought hormonal contraception; mean age 17.5 years; 68% were > 18 years; 77% were Hispanic; and 20% reported prior pregnancy. The mean duration of the observation period was 13 months (4-19 months). All 79 students received hormonal contraception (65% pill and 35% long acting progestin injection) onsite. During the observation period, the overall pregnancy rate was 6% (5/79); 4.7% (3/63) among students with no prior pregnancy. School clinic B: 40 students sought hormonal contraception; mean age 17.5 years; 52% > 18 years; 88 % were Hispanic; and 7.5% reported prior pregnancy. All 40 students were referred to the affiliated clinic. The mean duration of the observation period was 11.9 months (4-19 months). 50% (20) kept their appointment. Pills were dispensed to 85% (17/20) and 15% (3/20) received long acting progestin injection. The overall pregnancy rate was 20% (8/40); 21.6% (8/37) among students with no prior pregnancy. A significantly higher frequency of students seeking hormonal contraception kept their initial appointment for birth control at the school dispensing onsite contraception compared to the school with a referral policy for contraception (p<0.05). The pregnancy rate was significantly higher for the school with a referral policy for contraception compared to the school with onsite contraceptive services (p< 0.05). The pregnancy rate was also significantly higher for students without a prior history of pregnancy in the school with a referral policy for contraception (21.6%) versus the school with onsite contraceptive services (4.7%) (p< 0.05). CONCLUSION: This preliminary study showed that School clinic B with a referral policy had a lower appointment keeping rate for contraceptive services and a higher pregnancy rate than School clinic A with on-site contraceptive services. An on-site dispensing policy for hormonal contraceptives at high school-based health clinics may be a convenient and effective approach to prevent unintended first and repeat pregnancies among adolescents who seek hormonal contraception. This study has strong implications for reproductive health policy, especially as directed toward high-risk teenage populations.

Adolescent Sexual Behavior: Examining Data from Texas and the US

Background: The US has higher rates of teen births and sexually transmitted infections (STI) than other developed countries. Texas youth are disproportionately impacted. Purpose: To review local, state, and national data on teens’ engagement in sexual risk behaviors to inform policy and practice related to teen sexual health. Methods: 2009 middle school and high school Youth Risk Behavior Survey (YRBS) data, and data from All About Youth, a middle school study conducted in a large urban school district in Texas, were analyzed to assess the prevalence of sexual initiation, including the initiation of non-coital sex, and the prevalence of sexual risk behaviors among Texas and US youth. Results: A substantial proportion of middle and high school students are having sex. Sexual initiation begins as early as 6th grade and increases steadily through 12th grade with almost two-thirds of high school seniors being sexually experienced. Many teens are not protecting themselves from unintended pregnancy or STIs – nationally, 80% and 39% of high school students did not use birth control pills or a condom respectively the last time they had sex. Many middle and high school students are engaging in oral and anal sex, two behaviors which increase the risk of contracting an STI and HIV. In Texas, an estimated 689,512 out of 1,327,815 public high school students are sexually experienced – over half (52%) of the total high school population. Texas students surpass their US peers in several sexual risk behaviors including number of lifetime sexual partners, being currently sexually active, and not using effective methods of birth control or dual protection when having sex. They are also less likely to receive HIV/AIDS education in school. Conclusion: Changes in policy and practice, including implementation of evidence-based sex education programs in middle and high schools and increased access to integrated, teen-friendly sexual and reproductive health services, are urgently needed at the state and national levels to address these issues effectively.

The determinants of physician and pharmacist utilization and equity of access under Korean universal health insurance

This study examines the social and behavioral determinants of two types of primary care, seeing a physician or a pharmacist, for Koreans and evaluates the equity of the Korean national health insurance system. The study applies the Aday and Andersen access framework to cross-sectional data from the 1992 Korean National Health Interview Survey (N = 21,841).^ The study found that in Korea, the elderly were most likely, and children least likely, to have used physician services. Women, household heads, those in small families, and the less educated were more likely than their counterparts to use physician and pharmacist services. Health status and need were important determinants of Koreans seeing a doctor or a pharmacist. Differences in need substantially accounted for the original differences observed between subgroups. Resources associated with having insurance coverage, a regular source of care, and place of residence (rural/urban) ameliorated to some extent the subgroup differences in the use of physicians' and pharmacists' services among Koreans. They were also major independent predictors of access. Having insurance remains a particularly important predictor of who uses physician services. Among the insured, trade-offs in the use of physician and pharmacist services were found in the current system, i.e., uninsured and poor Koreans were more likely to use pharmacist services, while insured and rural Koreans were more likely to use doctor services. Among the insured, cost sharing rates are lower for physician than for pharmacist services. Self-employed persons were less likely than government and industrial workers to use physician services. An underlying expectation under universal health insurance was that the Korean health care system would be equitable. The research results, however, did not fully support this expectation.^ The policy implications of these findings are that measures are required to extend insurance coverage to the uninsured, to equalize differences in benefit packages between health plans, and to expand the availability of physicians in rural areas. Further research is also needed to understand those who do not currently have a regular source of care and why and the access barriers that may exist for selected demographic subgroups (those in large families and unmarried or divorced/widowed persons). ^

The effect of immigration status on racial differences in health insurance coverage, access to care, and utilization in the United States

Background. Lack of coverage, lack of access, and failure to utilize health care services have all been linked to dismal health outcomes in the US. Such consequences have been a longstanding challenge that US minorities are faced with, in the context of a health care system believed to be lacking efficiency and equity. National population surveys in the US suggest that the number of uninsured approaches 50 millions, while some concerns and suspicions are raised by opponents to the growing number of foreign born US residents, many of whom are Hispanic. Research shows that race is a significant predictor of lack of coverage, access, and utilization, while age, gender, education, and income are also linked to these outcomes. We investigated the potential effect of immigration status or duration in the US on the association between coverage, access, use, and race. Methods. Using National Health Interview Survey (NHIS) data of 2006, we selected 22, 667 individuals of Non-Hispanic Black, Hispanic, and Non-Hispanic White descent, at least 18 years of age, US-born and foreign-born who reported their duration of residence in the US. Through complex sample survey logistic regression analysis, we computed odds ratios, beta coefficients, and 95% confidence intervals using models which excluded then included immigration status. Results. Although a significant predictor of the outcomes, immigration status did not change the relationship between each of the dependent variables (coverage, access, utilization), and the factor race, while adjusting for age, gender, education, and income. Our results show that Hispanics were least likely to have coverage (OR=.58; 95% CI[.49, .68]), access (OR=.62; 95% CI[.50, .76]), and to utilize services (OR=.60; 95% CI[.46, .79]) followed by Non-Hispanic Blacks, and Non-Hispanic Whites. These results were not changed by stratification, or the inclusion of interaction terms to eliminate the potential effect of relationships between independent variables. Recent immigrants (<5 years in US) were 0.12 times less likely to be insured, but also 0.26 times less likely to utilize services (p<0.001), and in addition they represented only 7.3% of the uninsured and 1.9% of the US population in 2006. Furthermore, 12% of the Non-Hispanic White population in the US was not covered, and 65% of the uninsured individuals were US-Born Citizens. Other predictors of lack of coverage, access and use were age below 45, male gender, education at high school or below, and income of less than $20,000. Conclusion. This investigation shows that the high percentage of uninsured was not directly caused by Hispanics, and immigration status alone could not explain racial differences in coverage, access, and utilization. An immigration reform may not be the solution to the healthcare crisis, and more specifically, will not stop the increase in the number of uninsured in the US, nor reduce the cost of health care. As a better alternative, universal health insu rance coverage should be considered, when aiming to eliminate racial disparities, and to solve the health care crisis. ^ Keywords. health insurance, coverage, access, utilization, race, immigration, disparities.^

The relationship between risk perception and ethnicity as an explanation for late stage skin cancer diagnosis in Black and Hispanic populations: An analysis using data from the 2005 Health Information and National Trends Survey

Objective. The purpose of this study was to determine the relationship between ethnicity and skin cancer risk perception while controlling for other risk factors: education, gender, age, access to healthcare, family history of skin cancer, fear, and worry. ^ Methods. This study utilized the Health Information National Trends Survey (HINTS) dataset, a nationally representative sample of 5,586 individuals 18 years of age or older. One third of the respondents were chosen at random and asked questions involving skin cancer. Analysis was based on questions that identified skin cancer risk perception, fear of finding skin cancer, and frequency of worry about skin cancer and a variety of sociodemographic factors. ^ Results. Ethnicity had a significant impact on risk perception scores while controlling for other risk factors. Other risk factors that also had a significant impact on risk perception scores included family history of skin cancer, age, and worry. ^

Estimating parameters in Markov models for longitudinal studies with missing data or surrogate outcomes

The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^

Understanding causes of hospitalization and access to care among newly diagnosed HIV patients in Houston, TX

More than a quarter of patients with HIV in the United States are diagnosed in hospital settings most often with advanced HIV related conditions.(1) There has been little research done on the causes of hospitalization when the patients are first diagnosed with HIV. The aim of this study was to determine if the patients are hospitalized due to an HIV related cause or due to some other co-morbidity. Reduced access to care could be one possible reason why patients are diagnosed late in the course of the disease. This study compared the access to care of patients diagnosed with HIV in hospital and outpatient setting. The data used for the study was a part of the ongoing study “Attitudes and Beliefs and Steps of HIV Care”. The participants in the study were newly diagnosed with HIV and recruited from both inpatient and outpatient settings. The primary and the secondary diagnoses from hospital discharge reports were extracted and a primary reason for hospitalization was ascertained. These were classified as HIV-related, other infectious causes, non–infectious causes, other systemic causes, and miscellaneous causes. Access to care was determined by a score based on responses to a set of questions derived from the HIV Cost and Services Utilization Study (HCSUS) on a 6 point scale. The mean score of the hospitalized patients and mean score of the patients diagnosed in an outpatient setting was compared. We used multiple linear regressions to compare mean differences in the two groups after adjusting for age, sex, race, household income educational level and health insurance at the time of diagnosis. There were 185 participants in the study, including 78 who were diagnosed in hospital settings and 107 who were diagnosed in outpatient settings. We found that HIV-related conditions were the leading cause of hospitalization, accounting for 60% of admissions, followed by non-infectious causes (20%) and then other infectious causes (17%). The inpatient diagnosed group did not have greater perceived access-to-care as compared to the outpatient group. Regression analysis demonstrated a statistically significant improvement in access-to-care with advancing education level (p=0.04) and with better health insurance (p=0.004). HIV-related causes account for many hospitalizations when patients are first diagnosed with HIV. Many of these HIV-related hospitalizations could have been prevented if patients were diagnosed early and linked to medical care. Programs to increase HIV awareness need to be an integral part of activities aimed at control of spread of HIV in the community. Routine testing for HIV infection to promote early HIV diagnosis can prevent significant morbidity and mortality.^

Determining the association between nativity status and mammography utilization among women in the United States using 2000 and 2005 NHIS data

Objective. To determine the association between nativity status and mammography utilization among women in the U.S. and assess whether demographic variables, socioeconomic factors healthcare access, breast cancer risk factors and acculturation variables were predictors in the relationship between nativity status and mammography in the past two years. ^ Methods. The NHIS collects demographic and health information using face-to-face interviews among a representative sample of the U.S. population and a cancer control module assessing screening behaviors is included every five years. Descriptive statistics were used to report demographic characteristics of women aged 40 and older who have received a mammogram in the last 2 years from 2000 and 2005. We used chi square analyses to determine statistically significant differences by mammography screening for each covariate. Logistic regression was used to determine whether demographic characteristics, socioeconomic characteristics, healthcare access, breast cancer risk factors and acculturation variables among foreign-born Hispanics affected the relationship between nativity status and mammography use in the past 2 years. ^ Results. In 2000, the crude model between nativity and mammography was significant but results were not significant after adjusting for health insurance, access and reported health status. Significant results were also reported for years in U.S. and mammography among foreign-born born women. In 2005, the crude model was also significant but results were not significant after adjusting for demographic factors. Furthermore, there was a significant finding between citizenship and mammography in the past 2 years. ^ Conclusions. Our study contributes to the literature as one of the first national-based studies assessing mammography in the past two years based on nativity status. Based on our findings, health insurance and access to care is an important predictor in mammography utilization among foreign-born women. For those with health care access, physician recommendation should further be assessed to determine whether women are made aware of mammography as a means to detect breast cancer at an early stage and further reduce the risk of mortality from the breast cancer.^

Physical activity levels and access to places to be physically active

The built environment is recognized as having an impact on health and physical activity. Ecological theories of physical activity suggest that enhancing access to places to be physically active may increase activity levels. Studies show that users of fitness facilities are more likely to be active than inactive and active people are more likely to report access to fitness facilities. The purpose of this study was to examine the ecologic relationship between density of fitness facilities and self-reported levels of physical activity in adults in selected Metropolitan Statistical Areas (MSAs) in the United States.^ The 2007 MSA Business Patterns and the 2007 Behavioral Risk Factor Surveillance System (BRFSS) were used to gather fitness facility and physical activity data for 141 MSAs in the United States. Pearson correlations were performed between fitness facility density (number of facilities/100,000 people) and six summary measures of physical activity prevalence. Regional analysis was done using the nine U.S. Standard Regions for Temperature and Precipitation. ^ Direct correlations between fitness facility density and the percent of those physically active (r=0.27, 95% CI 0.11, 0.42, p=0.0012), those meeting moderate-intensity activity guidelines, (r=0.23, 95% CI 0.07, 0.38, p=0.006), and those meeting vigorous-intensity activity guidelines (r=0.30, 95% CI 0.14, 0.44, p=0.003) were found. An inverse correlation was found between fitness facility density and the percent of people physically inactive (r=-0.45, 95% CI -0.57, -0.31), p<0.0001). Regional analysis showed the same trends across most regions.^ Access to fitness facilities, defined here as fitness facility density, is related to physical activity levels. Results suggest the potential importance of the influence of the built environment on physical activity behaviors. Public health officials and city planners should consider the possible positive effect that increasing the number of fitness facilities in communities would have on activity levels.^

Effects of congressional modernization laws on public access to innovative medical device technologies

The Federal Food and Drug Administration (FDA) and the Centers for Medicare and Medicaid (CMS) play key roles in making Class III, medical devices available to the public, and they are required by law to meet statutory deadlines for applications under review. Historically, both agencies have failed to meet their respective statutory requirements. Since these failures affect patient access and may adversely impact public health, Congress has enacted several “modernization” laws. However, the effectiveness of these modernization laws has not been adequately studied or established for Class III medical devices. ^ The aim of this research study was, therefore, to analyze how these modernization laws may have affected public access to medical devices. Two questions were addressed: (1) How have the FDA modernization laws affected the time to approval for medical device premarket approval applications (PMAs)? (2) How has the CMS modernization law affected the time to approval for national coverage decisions (NCDs)? The data for this research study were collected from publicly available databases for the period January 1, 1995, through December 31, 2008. These dates were selected to ensure that a sufficient period of time was captured to measure pre- and post-modernization effects on time to approval. All records containing original PMAs were obtained from the FDA database, and all records containing NCDs were obtained from the CMS database. Source documents, including FDA premarket approval letters and CMS national coverage decision memoranda, were reviewed to obtain additional data not found in the search results. Analyses were conducted to determine the effects of the pre- and post-modernization laws on time to approval. Secondary analyses of FDA subcategories were conducted to uncover any causal factors that might explain differences in time to approval and to compare with the primary trends. The primary analysis showed that the FDA modernization laws of 1997 and 2002 initially reduced PMA time to approval; after the 2002 modernization law, the time to approval began increasing and continued to increase through December 2008. The non-combined, subcategory approval trends were similar to the primary analysis trends. The combined, subcategory analysis showed no clear trends with the exception of non-implantable devices, for which time to approval trended down after 1997. The CMS modernization law of 2003 reduced NCD time to approval, a trend that continued through December 2008. This study also showed that approximately 86% of PMA devices do not receive NCDs. ^ As a result of this research study, recommendations are offered to help resolve statutory non-compliance and access issues, as follows: (1) Authorities should examine underlying causal factors for the observed trends; (2) Process improvements should be made to better coordinate FDA and CMS activities to include sharing data, reducing duplication, and establishing clear criteria for “safe and effective” and “reasonable and necessary”; (3) A common identifier should be established to allow tracking and trending of applications between FDA and CMS databases; (4) Statutory requirements may need to be revised; and (5) An investigation should be undertaken to determine why NCDs are not issued for the majority of PMAs. Any process improvements should be made without creating additional safety risks and adversely impacting public health. Finally, additional studies are needed to fully characterize and better understand the trends identified in this research study.^