In 1963 – 1965, a large-scale health screening survey was undertaken in Sweden and this data set was linked to data from the national cause of death register. The data set involved more than 60,000 participants whose age at death less than 80 years. During the follow-up period until 2007, a total of 437 (338 males and 99 females) participants died from aortic aneurysm. The survival analysis, continuation ratio model, and logistic regression were applied in order to identify significant risk factors. The Cox regression after stratification for AGE revealed that SEX, Blood Diastolic Pressure (BDP), and Beta-lipoprotein (BLP) were the most significant risk factors, followed by Cholesterol (KOL), Sialic Acid (SIA), height, Glutamic Oxalactic Transaminase, Urinary glucose (URIN_SOC), and Blood Systolic Pressure (BSP). Moreover, SEX and BDP were found as risk factors in almost every age group. Furthermore, BDP was strongly significant in both male and female subgroup.   The data set was divided into two sets: 70 percent for the training set and 30 percent for the test set in order to find the best technique for predicting aortic aneurysm. Five techniques were implemented: the Cox regression, the continuation ratio model, the logistic regression, the back-propagated artificial neural network, and the decision tree. The performance of each technique was evaluated by using area under the receiver operating characteristic curve. In our study, the continuation ratio and the logistic regression outperformed among the other techniques.

No description available.

The objective of the current work is to develop novel procedures for the analysis of functional data and apply them for investigation of gender disparity in survival of lung cancer patients. In particular, we use the time-dependent Cox proportional hazards model where the clinical information is incorporated via time-independent covariates, and the current age is modeled using its expansion over wavelet basis functions. We developed computer algorithms and applied them to the data set which is derived from Florida Cancer Data depository data set (all personal information which allows to identify patients was eliminated). We also studied the problem of estimation of a continuous matrix-variate function of low rank. We have constructed an estimator of such function using its basis expansion and subsequent solution of an optimization problem with the Schattennorm penalty. We derive an oracle inequality for the constructed estimator, study its properties via simulations and apply the procedure to analysis of Dynamic Contrast medical imaging data.

Infection with human immunodeficiency virus (HIV) and progression to acquired immune deficiency syndrome (AIDS) often result in neurologic and neuropsychiatric changes, although the prognostic information available for patients affected by HIV/AIDS-related neurologic diagnoses has been limited. The objective of the present study was to characterize the patterns and predictors of survival, including the impacts of antiretroviral therapy (ART) use and potential factors in healthcare access and disparity, among patients with one or more of the following conditions: cryptococcosis, toxoplasmosis, primary central nervous system lymphoma, progressive multifocal leukoencephalopathy, and HIV-associated dementia. To accomplish this, a cohort was drawn from the Iowa HIV/AIDS reporting system, and a non-independent, university-based cohort was then used to validate the analyses conducted for the statewide sample. Patterns of ART use were identified in each cohort using logistic regression, and survival analyses were conducted using Kaplan-Meier analysis, Cox regression, and accelerated failure time modeling. Survival was poor in both cohorts, although the university-based setting (University of Iowa Hospitals and Clinics) was associated with better overall survival. Of 230 persons in the statewide cohort, 77.0% were deceased by the end of the study period (1982-2008), and the median survival was 1.13 years (95% CI: 0.90 to 1.86 years, n=225). By contrast, 56.4% of the university-based cohort was deceased by the end of the study period (1984-2009), and the median survival in this group was 3.04 years (95% CI: 1.79 to 11.62 years, n=172). Both cohorts were predominantly male, non-Hispanic white, and residents of a small metropolitan area at the time of the AIDS diagnosis. ART use had a strong protective effect on survival in both cohorts. Use of ART among patients diagnosed during the era of highly active antiretroviral therapies (HAART) was associated with an 80% reduction in the rate of death (HR=0.20, 95% CI: 0.08 to 0.46) compared to the non-users diagnosed during the pre-HAART era (that is, prior to 1996), after adjustment for age, race, birth sex, healthcare facility type, opportunistic infection count, HIV transmission risk category, neurologic condition, years since AIDS diagnosis, and timing of neuro-AIDS in a Cox regression model. In the UIHC cohort, the adjusted expected survival time among ART/HAART users was 37.71 (95% CI: 14.44 to 99.48) times that among non-users. Women had significantly poorer outcomes than men in the statewide cohort (adjusted HR=2.31, 95% CI: 1.22 to 4.35), and a similar, non-significant trend was observed among university-based cases. Secondary analyses suggested that this difference persisted over the course of the epidemic and was not attributable to differential ART response among men and women. Evidence for a role of disease severity, psychosocial support, and/or psychiatric comorbidity in the differential survival of men and women was identified. This study provides useful prognostic data for patients and providers and may guide future research efforts aimed toward improved survival for neuro-AIDS patients. The survival disadvantage of women compared to men should be confirmed and the mechanisms underlying this disparity elucidated. Meanwhile, clinical and public health efforts might be directed towards screening, treatment, and support for women affected by neuro-AIDS, including potential assessment of comorbid psychiatric disorders.

<p><strong>Målsättning</strong><strong></strong></p><p>Att utreda skillnader i tillgänglighet till insulinpump mellan olika patientgrupper samt vad som orsakar ett byte till insulinpump.</p><p><strong>Metod</strong><strong></strong></p><p>Data från 7224 individer med typ 1 diabetes vid tio olika vårdenheter analyserades för att utreda effekterna av njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration samt ålder. Jämförelsen mellan patientgrupper utfördes med logistisk regression som en tvärsnittsstudie och Cox-regression för att utreda vad som föregått ett byte till pump.</p><p><strong>Resultat</strong><strong></strong></p><p>Genom logistisk regression erhölls en bild av hur skillnader mellan patienter som använder insulinpump och patienter som inte gör det ser ut i dagsläget. Cox-regressionen tar med ett tidsperspektiv och ger på så sätt svar på vad som föregått ett byte till insulinpump. Dessa analyser gav liknande resultat gällande variabler konstanta över tiden. Kvinnor använder pump i större utsträckning än män och andelen pumpanvändare skiljer sig åt vid olika vårdenheter. I dagsläget visar sig hög ålder sänka sannolikheten att använda insulinpump, vilket bekräftas vid den tidsberoende studien som visade hur sannolikheten att byta till pump är avsevärt lägre vid hög ålder. Långtidsblodsockret har också tydlig effekt på sannolikheten att gå över till pump där ett högt långtidsblodsocker medför hög sannolikhet att byta till insulinpump.</p><p><strong>Slutsatser</strong><strong></strong></p><p>I dagsläget finns det skillnader i andelen insulinpumpanvändare mellan olika patientgrupper och skillnader finns även i de olika gruppernas benägenhet att byta från andra insulinbehandlingar till insulinpump. Beroende av patienters njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration och ålder har dessa olika sannolikheter att byta till insulinpump.<strong></strong></p>

Målsättning Att utreda skillnader i tillgänglighet till insulinpump mellan olika patientgrupper samt vad som orsakar ett byte till insulinpump. Metod Data från 7224 individer med typ 1 diabetes vid tio olika vårdenheter analyserades för att utreda effekterna av njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration samt ålder. Jämförelsen mellan patientgrupper utfördes med logistisk regression som en tvärsnittsstudie och Cox-regression för att utreda vad som föregått ett byte till pump. Resultat Genom logistisk regression erhölls en bild av hur skillnader mellan patienter som använder insulinpump och patienter som inte gör det ser ut i dagsläget. Cox-regressionen tar med ett tidsperspektiv och ger på så sätt svar på vad som föregått ett byte till insulinpump. Dessa analyser gav liknande resultat gällande variabler konstanta över tiden. Kvinnor använder pump i större utsträckning än män och andelen pumpanvändare skiljer sig åt vid olika vårdenheter. I dagsläget visar sig hög ålder sänka sannolikheten att använda insulinpump, vilket bekräftas vid den tidsberoende studien som visade hur sannolikheten att byta till pump är avsevärt lägre vid hög ålder. Långtidsblodsockret har också tydlig effekt på sannolikheten att gå över till pump där ett högt långtidsblodsocker medför hög sannolikhet att byta till insulinpump. Slutsatser I dagsläget finns det skillnader i andelen insulinpumpanvändare mellan olika patientgrupper och skillnader finns även i de olika gruppernas benägenhet att byta från andra insulinbehandlingar till insulinpump. Beroende av patienters njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration och ålder har dessa olika sannolikheter att byta till insulinpump.

Background: Knowledge of the incidence of tuberculosis (TB) and hospitalization postpartum could reduce maternal morbidity and mortality. TB infections are prevalent in pregnant women living with Human immunodeficiency virus (HIV) compared to women not living with HIV in South Africa. Adherence to Antiretroviral Therapy (ART) is poor among pregnant and postpartum women living with HIV (WLHIV), thus making WLHIV at a higher risk of hospitalization postpartum, due to the increased risk of Cesarean delivery (CD) and obstetric conditions as a result of HIV. The prevalence of TB among pregnant and postpartum women is poorly defined including in high prevalence TB and HIV locations, indicating limited evidence. The aim is to explore the incidence of TB and hospitalization within four years postpartum among WLHIV, including associated risk factors. Methodology: The study population is from phase 2 of the Maternal and Child HealthAntiretroviral Therapy (MCH-ART) study. It is a single-arm observational cohort study of 628 WLHIV who attended antenatal care (ANC). Enrolment into phase 1 began in March 2013, the final deliveries from phase 2 were in December 2014, and the final follow-up visits were completed in 2016. MCH-ART is an ongoing study with global approval examining strategies for providing HIV care and treatment to HIV-infected women who initiate ART during pregnancy and their HIV-exposed infants. This study took place at the Midwife-Obstetric Unit (MOU) at Gugulethu Community Health Centre, Western Cape South Africa. It consists of three connected study designs and three phases through the antenatal and postnatal periods. Phase 1 is a cross-sectional study, phase 2 is a cohort study and phase 3 is a randomized trial. Kaplan-Meier survival analysis was used to assess the incidence of TB and hospitalization over time among ix WLHIV up to four years postpartum and Cox regression was used to measure the effect of risk factors on the incidence of TB and hospitalization. Results: Thirty-five (35) WLHIV developed TB postpartum at a total person-time of 2365.1 woman-years. The incidence rate (IR) of developing TB among WLHIV postpartum was 1.48 (95% CI=1.03-2.06) cases per 100 woman-years from 2013 to 2018. Twenty-three (23) WLHIV was hospitalized postpartum and a total person-time of 552.8 woman-years was spent. The IR of hospitalization among WLHIV postpartum was 4.16 (95% CI=2.64-6.24) cases per 100 womanyears from 2013 to 2018. The IR of TB and hospitalization among WLHIV postpartum is statistically significant. Adjusting, for other risk factors, the history of diabetes at ANC, the history of TB at ANC and CD4 count (200 - <500) cells/mm3 at ANC also significantly increases the incidence of TB postpartum, whereas, obstetric reasons is associated with the hospitalization of WLHIV.

Master of Science / Department of Statistics / James J. Higgins / The time for an event to take place in an individual is called a survival time. Examples include the time that an individual survives after being diagnosed with a terminal illness or the time that an electronic component functions before failing. A popular parametric model for this type of data is the Weibull model, which is a flexible model that allows for the inclusion of covariates of the survival times. If distributional assumptions are not met or cannot be verified, researchers may turn to the semi-parametric Cox proportional hazards model. This model also allows for the inclusion of covariates of survival times but with less restrictive assumptions. This report compares estimates of the slope of the covariate in the proportional hazards model using the parametric Weibull model and the semi-parametric Cox proportional hazards model to estimate the slope. Properties of these models are discussed in Chapter 1. Numerical examples and a comparison of the mean square errors of the estimates of the slope of the covariate for various sample sizes and for uncensored and censored data are discussed in Chapter 2. When the shape parameter is known, the Weibull model far out performs the Cox proportional hazards model, but when the shape parameter is unknown, the Cox proportional hazards model and the Weibull model give comparable results.

Lung cancer is the most frequent fatal cancer in the United States. Following the notion in actuarial math analysis, we assume an exponential form for the baseline hazard function and combine Cox proportional hazard regression for the survival study of a group of lung cancer patients. The covariates in the hazard function are estimated by maximum likelihood estimation following the proportional hazards regression analysis. Although the proportional hazards model does not give an explicit baseline hazard function, the baseline hazard function can be estimated by fitting the data with a non-linear least square technique. The survival model is then examined by a neural network simulation. The neural network learns the survival pattern from available hospital data and gives survival prediction for random covariate combinations. The simulation results support the covariate estimation in the survival model.

While extensive research has been conducted on the causes of intimate partner violence in the community, very little is known about rates and predictors of domestic violence perpetrated by offenders who have recently been incarcerated. Some evidence suggests that formerly incarcerated individuals may be at an increased risk to perpetrate intimate partner violence during the transition from prison to the community (e.g., Hairston & Oliver 2006; Hilton, Harris, Popham, & Lang, 2010; Oliver & Hairston, 2008). The primary goal of this dissertation was to examine the extent to which former inmates engage in domestic violence during the transition from prison to the community. A second goal of this dissertation was to determine the independent and interactive effects of selected individual, situational, and social-structural factors on post-prison domestic violence. The current dissertation project involved a retrospective study of data collected from n = 1,137 formerly-incarcerated male offenders who were released from state prison between 2004 and 2009. Data regarding individual-level factors of borderline and antisocial personality characteristics and exposure to family-of-origin violence were extracted from institutional records. Additional individual-level demographic characteristics including offenders' age, ethnicity, education need, marital status, number of children, crime of conviction, length of incarceration, and participation in correctional rehabilitation programs extracted from institutional records were also considered. The situational-level factor of offenders' employment after prison release was also collected from institutional records; and the social-structural factor of neighborhood disadvantage was collected from information available in offenders' community supervision records and Census tract-level data. The outcome measure of post-prison domestic violence was gathered from local law enforcement records. Data were entered into statistical models to predict post-prison domestic violence. Main effects on post-prison domestic violence were examined for each of the individual-level demographic characteristics, borderline and antisocial personality features, exposure to family-of-origin violence, employment, and neighborhood disadvantage. Interactive effects on post-prison domestic violence were examined between borderline and antisocial personality characteristics, exposure to family-of-origin violence, employment, and neighborhood disadvantage. Significant predicted main effects on post-prison domestic violence included age, ethnicity, education need, number of children, violent criminal history, attendance of substance abuse treatment in prison, witnessing interparental violence as a child, and neighborhood disadvantage. Significant predicted interaction effects on post-prison domestic violence included the interaction between physical abuse as a child and neighborhood disadvantage. Implications for policies regarding post-prison supervision sentencing, housing, and the advancement of programming to prevent intimate partner violence during the transition from prison to the community are discussed. Contributions to the literature on intimate partner violence, environmental transition theory, and ecological theoretical frameworks are also addressed.