Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Arrhythmias and mortality after myocardial infarction in diabetic patients - Relationship to diabetes treatment

OBJECTIVE- To assess the relationship between clinical course after acute myocardial infarction (AMI) and diabetes treatment. RESEARCH DESIGN AND METHODS- Retrospective analysis of data from all patients aged 25-64 years admitted to hospitals in Perth, Australia, between 1985 and 1993 with AMI diagnosed according to the International Classification of Diseases (9th revision) criteria was conducted. Short- (28-day) and long-term survival and complications in diabetic and nondiabetic patients were compared. For diabetic patients, 28-day survival, dysrhythmias, heart block, and pulmonary edema were treated as outcomes, and factors related to each were assessed using multiple logistic regression. Diabetes treatment was added to the model to assess its significance. Long-term survival was compared by means of a Cox proportional hazards model. RESULTS- Of 5,715 patients, 745 (12.9%) were diabetic. Mortality at 28 days was 12.0 and 28.1% for nondiabetic and diabetic patients, respectively (P < 0.001); there were no significant drug effects in the diabetic group. Ventricular fibrillation in diabetic patients taking glibenclamide (11.8%) was similar to that of nondiabetic patients (11.0%) but was lower than that for those patients taking either gliclazide (18.0%; 0.1 > P > 0.05) or insulin (22.8%; P < 0.05). There were no other treatment-related differences in acute complications. Long-term survival in diabetic patients was reduced in those taking digitalis and/or diuretics but type of diabetes treatment at discharge had no significant association with outcome. CONCLUSlONS- These results do not suggest that ischemic heart disease should influence the choice of diabetes treatment regimen in general or of sulfonylurea drug in particular.

High HIV incidence and prevalence among young women in rural South Africa: Developing a cohort for intervention trials

Objective: To measure prevalence and model incidence of HIV infection. Setting: 2013 consecutive pregnant women attending public sector antenatal clinics in 1997 in Hlabisa health district, South Africa. Historical seroprevalence data, 1992-1995. Methods: Serum remaining from syphilis testing was tested anonymously for antibodies to HIV to determine seroprevalence. Two models, allowing for differential mortality between HIV-positive and HIV-negative people, were used. The first used serial seroprevalence data to estimate trends in annual incidence. The second, a maximum likelihood model, took account of changing force of infection and age-dependent risk of infection, to estimate age-specific HIV incidence in 1997. Multiple logistic regression provided adjusted odds ratios (OR) for risk factors for prevalent HIV infection. Results: Estimated annual HIV incidence increased from 4% in 1992/1993 to 10% in 1996/1997. In 1997, highest age-specific incidence was 16% among women aged between 20 and 24 years. in 1997, overall prevalence was 26% (95% confidence interval [CI], 24%-28%) and at 34% was highest among women aged between 20 and 24 years. Young age (<30 years; odds ratio [OR], 2.1; p = .001), unmarried status (OR 2.2; p = .001) and living in less remote parts of the district (OR 1.5; p = .002) were associated with HIV prevalence in univariate analysis. Associations were less strong in multivariate analysis. Partner's migration status was not associated with HIV infection. Substantial heterogeneity of HIV prevalence by clinic was observed (range 17%-31%; test for trend, p = .001). Conclusions: This community is experiencing an explosive HIV epidemic. Young, single women in the more developed parts of the district would form an appropriate cohort to test, and benefit from, interventions such as vaginal microbicides and HIV vaccines.

Pricing corporate bonds in Brazil: 2000 to 2004

This paper analyzes the factors that influence the issuing price of debentures in Brazil in the period from year 2000 to 2004, applying a factor model, in which exogenous variables explain return and price behavior. The variables in this study include: rating, choice of index, maturity, country risk, basic interest rate, long-term and short-term rate spread, the stock market index, and the foreign exchange rate. Results indicate that the index variable, probability of default and bond`s maturity influence pricing and points out associations of long-term bonds with better rating issues. (C) 2008 Elsevier Inc. All rights reserved.

Breastfeeding, menopause, and epithelial ovarian cancer

No previous study has examined the modifying effect of menopausal status on the association between lactation and ovarian cancer risk. We recruited 824 epithelial ovarian cancer cases and 855 community controls in three Australian states, collecting reproductive and lactation histories by means of a contraceptive calendar and pregnancy and breastfeeding record. We report results in women with at least one liveborn infant for unsupplemented breastfeeding, in line with a biological model linking suppression of ovulation to reduction in ovarian cancer risk. We derived odds ratios from multiple logistic regression models including number of liveborn children, age, age at first or last birth, and other potential confounders, overall and by menopausal status. Estimates of relative risk of ovarian cancer per month of full lactation were 0.99 [95% confidence interval(CI) = 0.97-1.00] overall and 1.00 (95% CI = 0.99-1.01) and 0.98 (95% CI = 0.95-1.01) among post- and premenopausal women, respectively. We tailored a lactation variable to the incessant ovulation hypothesis by progressively discounting breastfeeding the longer after birth it occurred, finding odds ratios similar to those for the unmodified duration variable. We found no association of note among postmenopausal women. Breastfeeding seems to be somewhat protective against ovarian cancer, but only before menopause.

Association between ADAMTS13 polymorphisms and risk of cardiovascular events in chronic coronary disease

Introduction: Association between ADAMTS13 levels and cardiovascular events has been described recently. However, no genetic study of ADAMTS13 in coronary patients has been described. Materials and Methods: Based on related populations frequencies and functional studies, we tested three ADAMTS13 polymorphisms: C1342G (Q448E), C1852G (P618A) and C2699T (A900V) in a group of 560 patients enrolled in the Medical, Angioplasty, or Surgery Study II (MASS II), a randomized trial comparing treatments for patients with coronary artery disease (CAD) and preserved left ventricular function. The incidence of the 5-year end-points of death and death from cardiac causes, myocardial infarction, refractory angina requiring revascularization and cerebrovascular accident was determined for each polymorphim`s allele, genotype and haplotype. Risk was assessed with the use of logistic regression and Cox proportional-hazards model and multivariable adjustment was employed for possible confounders. Results: Clinical characteristics and received treatment of each genotype group were similar at baseline. In an adjusted model for cardiovascular risk variables, we were able to observe a significant association between ADAMTS13 900V variant and an increased risk of death (OR: 1,92 CI: 1,14-3,23, p = 0,015) or death from cardiac cause (OR: 2,67, CI: 1,59-4,49, p = 0,0009). No association between events and ADAMTS13 Q448E or P618A was observed. Conclusions: This first report studying the association between ADAMTS13 genotypes and cardiovascular events provides evidence for the association between ADAMTS13 900V variant and an increased risk of death in a population with multi-vessel CAD. (C) 2009 Elsevier Ltd. All rights reserved.

Left ventricular Systolic function and outcome after in-hospital cardiac arrest

Background - The effect of prearrest left ventricular ejection fraction ( LVEF) on outcome after cardiac arrest is unknown. Methods and Results - During a 26-month period, Utstein-style data were prospectively collected on 800 consecutive inpatient adult index cardiac arrests in an observational, single-center study at a tertiary cardiac care hospital. Prearrest echocardiograms were performed on 613 patients ( 77%) at 11 +/- 14 days before the cardiac arrest. Outcomes among patients with normal or nearly normal prearrest LVEF ( >= 45%) were compared with those of patients with moderate or severe dysfunction ( LVEF < 45%) by chi(2) and logistic regression analyses. Survival to discharge was 19% in patients with normal or nearly normal LVEF compared with 8% in those with moderate or severe dysfunction ( adjusted odds ratio, 4.8; 95% confidence interval, 2.3 to 9.9; P < 0.001) but did not differ with regard to sustained return of spontaneous circulation ( 59% versus 56%; P = 0.468) or 24-hour survival ( 39% versus 36%; P = 0.550). Postarrest echocardiograms were performed on 84 patients within 72 hours after the index cardiac arrest; the LVEF decreased 25% in those with normal or nearly normal prearrest LVEF ( 60 +/- 9% to 45 +/- 14%; P < 0.001) and decreased 26% in those with moderate or severe dysfunction ( 31 +/- 7% to 23 +/- 6%, P < 0.001). For all patients, prearrest beta-blocker treatment was associated with higher survival to discharge ( 33% versus 8%; adjusted odds ratio, 3.9; 95% confidence interval, 1.8 to 8.2; P < 0.001). Conclusions - Moderate and severe prearrest left ventricular systolic dysfunction was associated with substantially lower rates of survival to hospital discharge compared with normal or nearly normal function.

A practical approach to assess depression risk and to guide risk reduction strategies in later life

Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.

Patient Characteristics as Predictors of Image Quality and Diagnostic Accuracy of MDCT Compared With Conventional Coronary Angiography for Detecting Coronary Artery Stenoses: CORE-64 Multicenter International Trial

OBJECTIVE. The purpose of the study was to investigate patient characteristics associated with image quality and their impact on the diagnostic accuracy of MDCT for the detection of coronary artery stenosis. MATERIALS AND METHODS. Two hundred ninety-one patients with a coronary artery calcification (CAC) score of <= 600 Agatston units (214 men and 77 women; mean age, 59.3 +/- 10.0 years [SD]) were analyzed. An overall image quality score was derived using an ordinal scale. The accuracy of quantitative MDCT to detect significant (>= 50%) stenoses was assessed using quantitative coronary angiography (QCA) per patient and per vessel using a modified 19-segment model. The effect of CAC, obesity, heart rate, and heart rate variability on image quality and accuracy were evaluated by multiple logistic regression. Image quality and accuracy were further analyzed in subgroups of significant predictor variables. Diagnostic analysis was determined for image quality strata using receiver operating characteristic (ROC) curves. RESULTS. Increasing body mass index (BMI) (odds ratio [OR] = 0.89, p < 0.001), increasing heart rate (OR = 0.90, p < 0.001), and the presence of breathing artifact (OR = 4.97, p = 0.001) were associated with poorer image quality whereas sex, CAC score, and heart rate variability were not. Compared with examinations of white patients, studies of black patients had significantly poorer image quality (OR = 0.58, p = 0.04). At a vessel level, CAC score (10 Agatston units) (OR = 1.03, p = 0.012) and patient age (OR = 1.02, p = 0.04) were significantly associated with the diagnostic accuracy of quantitative MDCT compared with QCA. A trend was observed in differences in the areas under the ROC curves across image quality strata at the vessel level (p = 0.08). CONCLUSION. Image quality is significantly associated with patient ethnicity, BMI, mean scan heart rate, and the presence of breathing artifact but not with CAC score at a patient level. At a vessel level, CAC score and age were associated with reduced diagnostic accuracy.

Benefit of antiretroviral therapy on survival of human immunodeficiency virus-infected patients admitted to an intensive care unit

Objective: To evaluate the impact of antiretroviral therapy (ART) and the prognostic factors for in-intensive care unit (ICU) and 6-month mortality in human immunodeficiency virus (HIV)-infected patients. Design: A retrospective cohort study was conducted in patients admitted to the ICU from 1996 through 2006. The follow-up period extended for 6 months after ICU admission. Setting: The ICU of a tertiary-care teaching hospital at the Universidade de Sao Paulo, Brazil. Participants: A total of 278 HIV-infected patients admitted to the ICU were selected. We excluded ICU readmissions (37), ICU admissions who stayed less than 24 hours (44), and patients with unavailable medical charts (36). Outcome Measure: In-ICU and 6-month mortality. Main Results: Multivariate logistic regression analysis and Cox proportional hazards models demonstrated that the variables associated with in-ICU and 6-month mortality were sepsis as the cause of admission (odds ratio [OR] = 3.16 [95% confidence interval [CI] 1.65-6.06]); hazards ratio [HR] = 1.37 [95% Cl 1.01-1.88)), an Acute Physiology and Chronic Health Evaluation 11 score >19 [OR = 2.81 (95% CI 1.57-5.04); HR = 2.18 (95% CI 1.62-2.94)], mechanical ventilation during the first 24 hours [OR = 3.92 (95% CI 2.20-6.96); HR = 2.25 (95% CI 1.65-3.07)], and year of ICU admission [OR = 0.90 (95% CI 0.81-0.99); HR = 0.92 [95% CI 0.87-0.97)]. CD4 T-cell count <50 cells/mm(3) Was only associated with ICU mortality [OR = 2.10 (95% Cl 1.17-3.76)]. The use of ART in the ICU was negatively predictive of 6-month mortality in the Cox model [HR = 0.50 (95% CI 0.35-0.71)], especially if this therapy was introduced during the first 4 days of admission to the ICU [HR = 0.58 (95% CI 0.41-0.83)]. Regarding HIV-infected patients admitted to ICU without using ART, those who have started this treatment during ICU, stay presented a better prognosis when time and potential confounding factors were adjusted for [HR 0.55 (95% CI 0.31-0.98)]. Conclusions: The ICU outcome of HIV-infected patients seems to be dependent not only on acute illness severity, but also on the administration of antiretroviral treatment. (Crit Care Med 2009; 37: 1605-1611)

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Depersonalization and personality in panic disorder

Background: Prevalence and clinical correlates of depersonalization symptoms have been associated with panic disorder. Personality traits might increase the likelihood of experiencing depersonalization symptoms or depersonalization disorder in panic patients. Aims: The objectives of this study are to establish the prevalence of depersonalization symptoms during the panic attack and in depersonalization disorder and to examine the personality factors associated with the presence of depersonalization in patients with panic disorder. Methods: The sample comprised 104 consecutive adult outpatients with panic disorder, diagnosed according to the Semistructured Clinical Interview for DSM-IV (Axis I/II disorders). Participants were assessed with the Cambridge Depersonalization Scales, the Temperament and Character Inventory, and the Panic and Agoraphobia Scale. Results: Forty-eight percent of the sample had depersonalization symptoms during the panic attack, whereas 20% of patients had a depersonalization disorder. Women presented more depersonalization disorders than did men (P = .036). Patients with panic disorder with depersonalization disorder had a more severe panic disorder (P = .002). Logistic regression analysis showed that self-transcendence trait (odds ratio, 1.089; 95% confidence interval, 1.021-1.162; P = .010) and severity of panic (odds ratio, 1.056; 95% confidence interval, 1.005-1.110; P = .032) were independently associated with depersonalization disorder. Conclusions: A high prevalence of depersonalization symptoms and depersonalization disorder was confirmed in patients with panic disorder, supporting a dosage effect model for understanding depersonalization pathology. Self-transcendence trait and severity of panic disorder were reported as risk factors for depersonalization disorder. (C) 2011 Elsevier Inc. All rights reserved.

Tooth loss prevalence and risk indicators in an isolated population of Brazil

Objective. The aim of this study was to assess the prevalence, extent, and risk indicators of tooth loss in an isolated population of Brazil. Material and methods. Two-hundred-and-forty-two subjects, ranging in age from 14 to 82 years (mean 36.2 years), were identified by census in an isolated population of Brazil. All consenting subjects received a full-mouth clinical (DFT index and information about missing teeth) and periodontal examination of 6 sites per tooth. Furthermore, they were interviewed using a structured written questionnaire in order to gather information about demographic, environmental, and biological variables. Results. Of the 200 subjects (80% response rate), 19 (9.5%) were edentulous, 90% had lost at least one tooth, and 39% had lost more than 8 teeth. The mean number of teeth lost was 9.5 (95% CI = 8.2-10.8). First mandibular molars were the most commonly missing teeth. In a multiple logistic regression analysis based on a theoretical hierarchical model of tooth loss, having more than 8 teeth lost was strongly associated with adult age (OR = 18.3-17.3, 95% CIs = 4.8-69.7 and 4.0-75.1) and female gender (OR = 5.9, 95% CI = 1.9-18.2) in the final model. Conclusions. Tooth loss was highly prevalent and extensive in this isolated population. Demographic and behavioral factors played an important role in tooth loss prevalence in this population.

Lipid peroxidation in hepatic steatosis in humans is associated with hepatic fibrosis and occurs predominately in acinar zone 3

Background and Aims: Hepatic steatosis has been shown to be associated with lipid peroxidation and hepatic fibrosis in a variety of liver diseases including non-alcoholic fatty liver disease. However, the lobular distribution of lipid peroxidation associated with hepatic steatosis, and the influence of hepatic iron stores on this are unknown. The aim of this study was to assess the distribution of lipid peroxidation in association with these factors, and the relationship of this to the fibrogenic cascade. Methods: Liver biopsies from 39 patients with varying degrees of hepatic steatosis were assessed for evidence of lipid peroxidation (malondialdehyde adducts), hepatic iron, inflammation, fibrosis, hepatic ;stellate cell activation (alpha-smooth muscle actin and TGF-beta expression) and collagen type I synthesis (procollagen a 1 (I) mRNA). Results: Lipid peroxidation occurred in and adjacent to fat-laden hepatocytes and was maximal in acinar zone 3. Fibrosis was associated with steatosis (P < 0.04), lipid peroxidation (P < 0.05) and hepatic iron stores (P < 0.02). Multivariate logistic regression analysis confirmed the association between steatosis and lipid peroxidation within zone 3 hepatocytes (P < 0.05), while for hepatic iron, lipid peroxidation was seen within sinusoidal cells (P < 0.05), particularly in zone 1 (P < 0.02). Steatosis was also associated with acinar inflammation (P < 0.005). α-Smooth muscle actin expression was present in association with both lipid peroxidation and fibrosis. Although the effects of steatosis and iron on lipid peroxidation and fibrosis were additive, there was no evidence of a specific synergistic interaction between them. Conclusions: These observations support a model where steatosis exerts an effect on fibrosis through lipid peroxidation, particularly in zone 3 hepatocytes. (C) 2001 Blackwell Science Asia Pty Ltd.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.