A log-rank-type test to compare net survival distributions.

In population-based cancer studies, it is often interesting to compare cancer survival between different populations. However, in such studies, the exact causes of death are often unavailable or unreliable. Net survival methods were developed to overcome this difficulty. Net survival is the survival that would be observed if the disease under study was the only possible cause of death. The Pohar-Perme estimator (PPE) is a nonparametric consistent estimator of net survival. In this article, we present a log-rank-type test for comparing net survival functions (as estimated by PPE) between several groups. We put the test within the counting process framework to introduce the inverse probability weighting procedure as required by the PPE. We built a stratified version to control for categorical covariates that affect the outcome. We performed simulation studies to evaluate the performance of this test and worked an application on real data

On models for the estimation of the excess mortality hazard in case of insufficiently stratified life tables.

In cancer epidemiology using population-based data, regression models for the excess mortality hazard is a useful method to estimate cancer survival and to describe the association between prognosis factors and excess mortality. This method requires expected mortality rates from general population life tables: each cancer patient is assigned an expected (background) mortality rate obtained from the life tables, typically at least according to their age and sex, from the population they belong to. However, those life tables may be insufficiently stratified, as some characteristics such as deprivation, ethnicity, and comorbidities, are not available in the life tables for a number of countries. This may affect the background mortality rate allocated to each patient, and it has been shown that not including relevant information for assigning an expected mortality rate to each patient induces a bias in the estimation of the regression parameters of the excess hazard model. We propose two parametric corrections in excess hazard regression models, including a single-parameter or a random effect (frailty), to account for possible mismatches in the life table and thus misspecification of the background mortality rate. In an extensive simulation study, the good statistical performance of the proposed approach is demonstrated, and we illustrate their use on real population-based data of lung cancer patients. We present conditions and limitations of these methods and provide some recommendations for their use in practice

SPODT: An R Package to Perform Spatial Partitioning

International audienceSpatial cluster detection is a classical question in epidemiology: Are cases located near other cases? In order to classify a study area into zones of different risks and determine their boundaries, we have developed a spatial partitioning method based on oblique decision trees, which is called spatial oblique decision tree (SpODT). This non-parametric method is based on the classification and regression tree (CART) approach introduced by Leo Breiman. Applied to epidemiological spatial data, the algorithm recursively searches among the coordinates for a threshold or a boundary between zones, so that the risks estimated in these zones are as different as possible. While the CART algorithm leads to rectangular zones, providing perpendicular splits of longitudes and latitudes, the SpODT algorithm provides oblique splitting of the study area, which is more appropriate and accurate for spatial epidemiology. Oblique decision trees can be considered as non-parametric regression models. Beyond the basic function, we have developed a set of functions that enable extended analyses of spatial data, providing: inference, graphical representations, spatio-temporal analysis, adjustments on covariates, spatial weighted partition, and the gathering of similar adjacent final classes. In this paper, we propose a new R package, SPODT, which provides an extensible set of functions for partitioning spatial and spatio-temporal data. The implementation and extensions of the algorithm are described. Function usage examples are proposed, looking for clustering malaria episodes in Bandiagara, Mali, and samples showing three different cluster shapes

313 Probability of significant coronary artery disease in Southern France: A need for distinctive predictive models

Como podrá establecerse en el desarrollo de esta investigación, la búsqueda de derroteros para la solución a este grave problema de “falta de vivienda”, ha determinado que los estados se preocupen por integrar a sus cartas magnas los derechos de las personas a contar con el apoyo de ellos para la satisfacción de su necesidad de contar con una vivienda, y a los organismos internacionales así mismo a interesarse por apoyar a los estados, en el estudio de la problemática y a dispensar recursos humanos y económicos para coadyuvar en la solución sobre todo, en beneficio de los sectores económicamente menos favorecidos. Por otro lado hay que entender que el problema de la vivienda es estructural y por lo tanto debe ser enfrentado desde los aspectos, teóricos, poblacionales, de desarrollo urbano, diseño, tecnología, factores económicos, sociales, políticos y culturales y sobre todo del aprovechamiento los recursos adaptándolos a la realidad existente en un mundo tan velozmente cambiante por la globalización. Además hay que destacar la importancia que para los países, conlleva el establecimiento de políticas de vivienda con tecnologías apropiadas, sobre todo en la Vivienda de Interés Social, que de manera integral y pragmática determinen acciones novedosas y dinámicas, que sostenidas en el tiempo y el espacio se conviertan en Objetivo Nacional Permanente, que permita elevar el bienestar y el mejoramiento de las condiciones de vida de los pueblos.1. Antecedentes 2.Aspectos Normativos Institucionales 3.Situación de la Vivienda en el Ecuador durante los períodos censales 4. Política de Vivienda 5.Propuesta 6.Conclusiones y Recomendacione

PLoS One

BACKGROUND: Long-term growth in HIV-infected infants treated early in resource-limited settings is poorly documented. Incidence of growth retardation, instantaneous risk of death related to malnutrition and growth parameters evolution during the first five years of life of uninfected and early treated HIV-infected children were compared and associated factors with growth retardation were identified. METHODS: Weight-for-age (WAZ), weight-for-length (WLZ), and length-for-age (LAZ) Z-scores were calculated. The ANRS-PEDIACAM cohort includes four groups of infants with three enrolled during the first week of life: HIV-infected (HI, n = 69), HIV-exposed uninfected (HEU, n = 205) and HIV-unexposed uninfected (HUU, n = 196). The last group included HIV-infected infants diagnosed before 7 months of age (HIL, n = 141). The multi-state Markov model was used to describe the incidence of growth retardation and identified associated factors. RESULTS: During the first 5 years, 27.5% of children experienced underweight (WAZ<-2), 60.4% stunting (LAZ<-2) and 41.1% wasting (WLZ<-2) at least once. The instantaneous risk of death observed from underweight state (35.3 [14.1-88.2], 84.0 [25.5-276.3], and 6.0 [1.5-24.1] per 1000 person-months for 0-6 months, 6-12 months, and 12-60 months respectively) was higher than from non-underweight state (9.6 [5.7-16.1], 20.1 [10.3-39.4] and 0.3 [0.1-0.9] per 1000 person-months). Compared to HEU, HIL and HI children were most at risk of wasting (adjusted HR (aHR) = 4.3 (95%CI: 1.9-9.8), P<0.001 and aHR = 3.3 (95%CI: 1.4-7.9), P = 0.01 respectively) and stunting for HIL (aHR = 8.4 (95%CI: 2.4-29.7). The risk of underweight was higher in HEU compared to HUU children (aHR = 5.0 (CI: 1.4-10.0), P = 0.001). Others associated factors to growth retardation were chronic pathologies, small size at birth, diarrhea and CD4< 25%. CONCLUSIONS: HIV-infected children remained at high risk of wasting and stunting within the first 5 years period of follow-up. There is a need of identifying suitable nutritional support and best ways to integrate it with cART in pediatric HIV infection global care