Carmen Cadarso-Suárez

Multi-state models for the analysis of time-to-event data.

The experience of a patient in a survival study may be modelled as a process with two states and one possible transition from an “alive” state to a “dead” state. In some studies, however, the “alive” state may be partitioned into two or more intermediate (transient) states, each of which corresponding to a particular stage of the illness. In such studies, multi-state models can be used to model the movement of patients among the various states. In these models issues, of interest include the estimation of progression rates, assessing the effects of individual risk factors, survival rates or prognostic forecasting. In this article, we review modelling approaches for multi-state models, and we focus on the estimation of quantities such as the transition probabilities and survival probabilities. Differences between these approaches are discussed, focussing on possible advantages and disadvantages for each method. We also review the existing software currently available to fit the various models and present new software developed in the form of an R library to analyse such models. Different approaches and software are illustrated using data from the Stanford heart transplant study and data from a study on breast cancer conducted in Galicia, Spain.

Assessing relationships between health-related quality of life and adherence to antiretroviral therapy

Objective: To investigate associations between health-related quality of life (HRQoL), as assessed using the multidimensional quality of life-HIV (MQOL-HIV) questionnaire, and adherence to antiretroviral treatment in HIV-infected subjects. Design: Multicentre cross-sectional study in three institutional tertiary hospitals in northwest Spain. Patients and methods: The MQOL-HIV was completed by 235 HIV-infected adults undergoing antiretroviral treatment. Adherence to antiretroviral therapy was assessed by using patients self-report. Information about sociodemographic characteristics and clinical variables was also collected. Results: Good adherence (≥95% of prescribed pills correctly taken) was reported by 131 patients (55.7%). Univariate analyses indicated that the sociodemographic and clinical variables associated with adherence were age, educational level, income, employment, home stability, transmission route, history of previous antiretroviral therapy, and number of prescribed pills/day. Subscales of MQOL-HIV associated with adherence were mental health, cognitive functioning, financial status, medical care, partner intimacy, and (in men only) sexual functioning. Stepwise logistic regression showed that good adherence was more frequent in patients aged >40 years (odds ratio, OR: 2.50; 95% confidence interval, CI: 1.15–5.61) and in patients with high cognitive functioning (OR: 2.26; 95% CI: 1.19–4.30). Conversely, poor adherence was more frequent in patients without stable home (OR: 2.96; 95% CI: 1.39–6.32), in patients required to take 14 or more pills/day (OR: 2.17; 95% CI: 1.18–4.28), in patients with low financial status (OR: 3.42; 95% CI: 1.57–7.45), and in patients reporting low medical care (OR: 2.07; 95% CI: 1.07–3.98). Conclusions: HRQoL dimensions, notably cognitive functioning, financial status and medical care, are closely associated with antiretroviral therapy adherence.

Asymptotic properties of a generalized kaplan-meier estimator with some applications

A generalized Kaplan-Meier estimator has been considered in the literature on conditional survival analysis (Beran (1981), Gonzalez-Manteiga and Cadarso-Suarez (1991) and Gentleman and Crowley (1991)). An almost sure representation as a sum of independent variables is given here for this estimator. Some applications are obtained as consequences of these results.

Emergence of asiatic vibrio diseases in south america in phase with El Niño

Background: The seventh pandemic of Vibrio cholerae unexpectedly reached the coast of Peru in 1991, causing an explosive emergence of infections throughout the American continents. The origin and routes of dissemination are as yet unknown. A new Vibrio epidemic arose in 1997 in South America (northern Chile) when the pandemic clone of Vibrio parahaemolyticus was for the fist time detected outside of Asia. These 2 cases were concurrent with 2 episodes of El Niño. Methods: We carried out a survey of records of V. parahaemolyticus infection and of strains existing in the Instituto Nacional de Salud of Peru between 1994 and 2005. Association between the El Niño event and the V. parahaemolyticus disease was analyzed through generalized additive models applied to time-series data with negative binomial response, selecting some oceanographic factors distinctive of the movement of the El Niño waters. Results: Epidemiologic data and laboratory investigations of the strains showed that V. parahaemolyticus infections caused by the pandemic clone emerged in the coasts of Peru linked to the 1997 El Niño episode. The epidemic dissemination of this clone matched the expansion and dynamics of the poleward propagation and the receding of the El Niño waters. This pattern was similar to previously reported onset of cholera epidemic in 1991. Conclusions: These findings identify the El Niño episodes as a reliable vehicle for the introduction and propagation of Vibrio pathogens in South America. The movement of oceanic waters seems to be one of the driving forces of the spread of Vibrio diseases.

HEpiMA: software for the identification of heterogeneity in meta-analysis

Meta-analysis is a quantitative method available to epidemiologists, psychologists, social scientists and others who wish to produce a summary measure of the effect of exposure on disease, based on results from published studies along with a summary measure of uncertainty. The magnitude of the effect vary from study to study because of differences in the features of these studies (design, population, control of confounding variables etc.). From the various studies an estimator is formed by pooling the results found in each study in one summary measure. This summary (or pooled) measure is meaningful only if the magnitude of heterogeneity between study effects is small and can be explained by sampling variation. In this paper, we present HEpiMA, a new comprehensive and user-friendly software program for epidemiologic meta-analysis. HEpiMA has new features that are not available in other programs. The program carries out a complete study of heterogeneity of study effects with 11 hypothesis test results. In addition to model-based methods, the program also implements bootstrap methodology. New useful estimators of heterogeneity, Ri and CV(B), developed by the authors are given in the output. In addition to these unique features, the major advantage of this software is the option for direct entry of adjusted relative risk estimates of individual studies, the most common form of presentation of results in the epidemiologic literature. This program may also be useful for meta-analysts of clinical trials, in which the relative risk is the parameter of interest as it also allows the entry of crude data under the form of 2x2 tables.

Characteristics and dynamics of Salmonella contamination along the coast of Agadir, Morocco.

ABSTRACT The occurrence of Salmonella enterica in the environment of tropical and desert regions has remained largely uninvestigated in many areas of the world, including Africa. In the present study, we investigated the presence of Salmonella spp. along 122 km of the coastline of Agadir (southern Morocco) in relation to environmental parameters. A total of 801 samples of seawater (243), marine sediment (279), and mussels (279) were collected from six sites between July 2004 and May 2008. The overall prevalence of Salmonella spp. was 7.1%, with the highest occurrence in mussels (10%), followed by sediment (6.8%) and seawater (4.1%). Only three serotypes were identified among the 57 Salmonella sp. strains isolated. S. enterica serotype Blockley represented 43.8% of all Salmonella strains and was identified in mussel and sediment samples. S. enterica serotype Kentucky (29.8%) was found almost exclusively in mussels, whereas S. enterica serotype Senftenberg (26.3%) was detected in sediment and seawater. Statistical analysis using generalized additive models identified seawater temperature, environmental temperature, rainfall, and solar radiation as significant factors associated with the presence of Salmonella. Rainfall was the only variable showing a linear positive effect on the presence of Salmonella in the sea, whereas the remaining variables showed more complex nonlinear effects. Twenty-eight (49.1%) Salmonella isolates displayed resistance to ampicillin (22 isolates), nalidixic acid (9 isolates), sulfonamide compounds (2 isolates), and tetracycline (1 isolate), with six of these isolates displaying multiple resistance to two of these antimicrobial agents. Pulsed-field gel electrophoresis analysis revealed homogenous restriction patterns within each serotype that were uncorrelated with the resistance pattern profiles.

Insulin resistance index (HOMA-IR) levels in a general adult population: Curves percentile by gender and age. The EPIRCE study

AIMS To describe the distribution of HOMA-IR levels in a general nondiabetic population and its relationships with metabolic and lifestyles characteristics. METHODS Cross-sectional study. Data from 2246 nondiabetic adults in a random Spanish population sample, stratified by age and gender, were analyzed. Assessments included a structured interview, physical examination, and blood sampling. Generalized additive models (GAMs) were used to assess the effect of lifestyle habits and clinical and demographic measurements on HOMA-IR. Multivariate GAMs and quantile regression analyses of HOMA-IR were carried out separately in men and women. RESULTS This study shows refined estimations of HOMA-IR levels by age, body mass index, and waist circumference in men and women. HOMA-IR levels were higher in men (2.06) than women (1.95) (P=0.047). In women, but not men, HOMA-IR and age showed a significant nonlinear association (P=0.006), with increased levels above fifty years of age. We estimated HOMA-IR curves percentile in men and women. CONCLUSIONS Age- and gender-adjusted HOMA-IR levels are reported in a representative Spanish adult non-diabetic population. There are gender-specific differences, with increased levels in women over fifty years of age that may be related with changes in body fat distribution after menopause.

smoothHR: An R Package for Pointwise Nonparametric Estimation of Hazard Ratio Curves of Continuous Predictors

The Cox proportional hazards regression model has become the traditional choice for modeling survival data in medical studies. To introduce flexibility into the Cox model, several smoothing methods may be applied, and approaches based on splines are the most frequently considered in this context. To better understand the effects that each continuous covariate has on the outcome, results can be expressed in terms of splines-based hazard ratio (HR) curves, taking a specific covariate value as reference. Despite the potential advantages of using spline smoothing methods in survival analysis, there is currently no analytical method in the R software to choose the optimal degrees of freedom in multivariable Cox models (with two or more nonlinear covariate effects). This paper describes an R package, called smoothHR, that allows the computation of pointwise estimates of the HRs—and their corresponding confidence limits—of continuous predictors introduced nonlinearly. In addition the package provides functions for choosing automatically the degrees of freedom in multivariable Cox models. The package is available from the R homepage. We illustrate the use of the key functions of the smoothHR package using data from a study on breast cancer and data on acute coronary syndrome, from Galicia, Spain.

Retinal nerve fiber layer thickness, brain atrophy, and disability in multiple sclerosis patients.

Objective: To study the relationship between retinal nerve fiber layer (RNFL) thickness and brain atrophy using magnetic resonance imaging (MRI) with bicaudate ratio (BCR) in patients with multiple sclerosis (MS) with different levels of disease severity. We also assessed whether RNFL thickness correlated with Expanded Disability Status Scale (EDSS) score. Methods: The participants consisted of 88 patients with MS and 59 age- and sex-matched healthy control subjects. Eleven patients had clinically isolated syndrome (CIS), 68 patients had relapsing-remitting MS (RR-MS), and 9 patients had secondary progressive MS. Patients and controls were evaluated using optical coherence tomography (OCT, Cirrus) and scanning laser polarimetry with variable corneal compensation (GDx VCC). Patients underwent the same brain MRI scanning protocol. Disability was evaluated according to the EDSS. The BCR was calculated by dividing the minimum intercaudate distance by brain width along the same level. Results: The BCR was higher in patients with MS (0.12 ± 0.03) than in controls (0.08 ± 0.009) (P < 0.001). OCT average RNFL thickness in patients with MS was significantly lower (84.51 ± 14.27 &mgr;m) than in control subjects (98.44 ± 6.83 &mgr;m). BCR was correlated with OCT average RNFL thickness (r = −0.48, P = 0.002) in patients with MS without optic neuritis. Significant correlations were found between average RNFL thickness and EDSS (r = −0.43, P = 0.003). Additionally, there were correlations between BCR with GDx parameters in patients with MS without optic neuritis. Conclusions: This study shows that RNFL thickness correlates with BCR and with MS subtypes. Additionally, our study indicates that OCT is better suited for MS assessment than GDx. We conclude that the damage of retinal axons appears related to brain damage in patients with MS.

Flexible regression models for estimating postmortem interval (PMI) in forensic medicine

Correct determination of time of death is an important goal in forensic medicine. Numerous methods have been described for estimating postmortem interval (PMI), but most are imprecise, poorly reproducible and/or have not been validated with real data. In recent years, however, some progress in PMI estimation has been made, notably through the use of new biochemical methods for quantifying relevant indicator compounds in the vitreous humour. The best, but unverified, results have been obtained with [K+] and hypoxanthine [Hx], using simple linear regression (LR) models. The main aim of this paper is to offer more flexible alternatives to LR, such as generalized additive models (GAMs) and support vector machines (SVMs) in order to obtain improved PMI estimates. The present study, based on detailed analysis of [K+] and [Hx] in more than 200 vitreous humour samples from subjects with known PMI, compared classical LR methodology with GAM and SVM methodologies. Both proved better than LR for estimation of PMI. SVM showed somewhat greater precision than GAM, but GAM offers a readily interpretable graphical output, facilitating understanding of findings by legal professionals; there are thus arguments for using both types of models. R code for these methods is available from the authors, permitting accurate prediction of PMI from vitreous humour [K+], [Hx] and [U], with confidence intervals and graphical output provided.