The impact of psychiatric diagnosis on treatment adherence and duration among victimized children and adolescents in Sao Paulo, Brazil

OBJECTIVE: Despite the high prevalence of substance abuse and mood disorders among victimized children and adolescents, few studies have investigated the association of these disorders with treatment adherence, represented by numbers of visits per month and treatment duration. We aimed to investigate the effects of substance abuse and mood disorders on treatment adherence and duration in a special programfor victimized children in Sao Paulo, Brazil. METHODS: A total of 351 participants were evaluated for psychiatric disorders and classified into one of five groups: mood disorders alone; substance abuse disorders alone; mood and substance abuse disorders; other psychiatric disorders; no psychiatric disorders. The associations between diagnostic classification and adherence to treatment and the duration of program participation were tested with logistic regression and survival analysis, respectively. RESULTS: Children with mood disorders alone had the highest rate of adherence (79.5%); those with substance abuse disorders alone had the lowest (40%); and those with both disorders had an intermediate rate of adherence (50%). Those with other psychiatric disorders and no psychiatric disorders also had high rates of adherence (75.6% and 72.9%, respectively). Living with family significantly increased adherence for children with substance abuse disorders but decreased adherence for those with no psychiatric disorders. The diagnostic correlates of duration of participation were similar to those for adherence. CONCLUSIONS: Mood and substance abuse disorders were strong predictive factors for treatment adherence and duration, albeit in opposite directions. Living with family seems to have a positive effect on treatment adherence for patients with substance abuse disorders. More effective treatment is needed for victimized substance-abusing youth.

Comparison of two experimental models of pulmonary hypertension

Objective: To compare two models of pulmonary hypertension (monocrotaline and monocrotaline+pneumonectomy) regarding hemodynamic severity, structure of pulmonary arteries, inflammatory markers (IL-1 and PDGF), and 45-day survival. Methods: We used 80 Sprague-Dawley rats in two study protocols: structural analysis; and survival analysis. The rats were divided into four groups: control; monocrotaline (M), pneumonectomy (P), and monocrotaline+pneumonectomy (M+P). In the structural analysis protocol, 40 rats (10/group) were catheterized for the determination of hemodynamic variables, followed by euthanasia for the removal of heart and lung tissue. The right ventricle (RV) was dissected from the interventricular septum (IS), and the ratio between RV weight and the weight of the left ventricle (LV) plus IS (RV/LV+IS) was taken as the index of RV hypertrophy. In lung tissues, we performed histological analyses, as well as using ELISA to determine IL-1 and PDGF levels. In the survival protocol, 40 animals (10/group) were followed for 45 days. Results: The M and M+P rats developed pulmonary hypertension, whereas the control and P rats did not. The RV/LV+IS ratio was significantly higher in M+P rats than in M rats, as well as being significantly higher in M and M+P rats than in control and P rats. There were no significant differences between the M and M+P rats regarding the area of the medial layer of the pulmonary arteries; IL-1 and PDGF levels; or survival. Conclusions: On the basis of our results, we cannot conclude that the monocrotaline+pneumonectomy model is superior to the monocrotaline model.

The impact of psychiatric diagnosis on treatment adherence and duration among victimized children and adolescents in São Paulo, Brazil

OBJECTIVE: Despite the high prevalence of substance abuse and mood disorders among victimized children and adolescents, few studies have investigated the association of these disorders with treatment adherence, represented by numbers of visits per month and treatment duration. We aimed to investigate the effects of substance abuse and mood disorders on treatment adherence and duration in a special program for victimized children in São Paulo, Brazil. METHODS: A total of 351 participants were evaluated for psychiatric disorders and classified into one of five groups: mood disorders alone; substance abuse disorders alone; mood and substance abuse disorders; other psychiatric disorders; no psychiatric disorders. The associations between diagnostic classification and adherence to treatment and the duration of program participation were tested with logistic regression and survival analysis, respectively. RESULTS: Children with mood disorders alone had the highest rate of adherence (79.5%); those with substance abuse disorders alone had the lowest (40%); and those with both disorders had an intermediate rate of adherence (50%). Those with other psychiatric disorders and no psychiatric disorders also had high rates of adherence (75.6% and 72.9%, respectively). Living with family significantly increased adherence for children with substance abuse disorders but decreased adherence for those with no psychiatric disorders. The diagnostic correlates of duration of participation were similar to those for adherence. CONCLUSIONS: Mood and substance abuse disorders were strong predictive factors for treatment adherence and duration, albeit in opposite directions. Living with family seems to have a positive effect on treatment adherence for patients with substance abuse disorders. More effective treatment is needed for victimized substance-abusing youth

The Integrated European Project "GEHA - GEnetics of Healthy Aging": recruitment, health status assessment and survival of the Italian 90+ sibpairs

The present study is part of the EU Integrated Project “GEHA – Genetics of Healthy Aging” (Franceschi C et al., Ann N Y Acad Sci. 1100: 21-45, 2007), whose aim is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced age in good cognitive and physical function and in the absence of major age-related diseases. Aims The major aims of this thesis were the following: 1. to outline the recruitment procedure of 90+ Italian siblings performed by the recruiting units of the University of Bologna (UNIBO) and Rome (ISS). The procedures related to the following items necessary to perform the study were described and commented: identification of the eligible area for recruitment, demographic aspects related to the need of getting census lists of 90+siblings, mail and phone contact with 90+ subjects and their families, bioethics aspects of the whole procedure, standardization of the recruitment methodology and set-up of a detailed flow chart to be followed by the European recruitment centres (obtainment of the informed consent form, anonimization of data by using a special code, how to perform the interview, how to collect the blood, how to enter data in the GEHA Phenotypic Data Base hosted at Odense). 2. to provide an overview of the phenotypic characteristics of 90+ Italian siblings recruited by the recruiting units of the University of Bologna (UNIBO) and Rome (ISS). The following items were addressed: socio-demographic characteristics, health status, cognitive assessment, physical conditions (handgrip strength test, chair-stand test, physical ability including ADL, vision and hearing ability, movement ability and doing light housework), life-style information (smoking and drinking habits) and subjective well-being (attitude towards life). Moreover, haematological parameters collected in the 90+ sibpairs as optional parameters by the Bologna and Rome recruiting units were used for a more comprehensive evaluation of the results obtained using the above mentioned phenotypic characteristics reported in the GEHA questionnaire. 3. to assess 90+ Italian siblings as far as their health/functional status is concerned on the basis of three classification methods proposed in previous studies on centenarians, which are based on: • actual functional capabilities (ADL, SMMSE, visual and hearing abilities) (Gondo et al., J Gerontol. 61A (3): 305-310, 2006); • actual functional capabilities and morbidity (ADL, ability to walk, SMMSE, presence of cancer, ictus, renal failure, anaemia, and liver diseases) (Franceschi et al., Aging Clin Exp Res, 12:77-84, 2000); • retrospectively collected data about past history of morbidity and age of disease onset (hypertension, heart disease, diabetes, stroke, cancer, osteopororis, neurological diseases, chronic obstructive pulmonary disease and ocular diseases) (Evert et al., J Gerontol A Biol Sci Med Sci. 58A (3): 232-237, 2003). Firstly these available models to define the health status of long-living subjects were applied to the sample and, since the classifications by Gondo and Franceschi are both based on the present functional status, they were compared in order to better recognize the healthy aging phenotype and to identify the best group of 90+ subjects out of the entire studied population. 4. to investigate the concordance of health and functional status among 90+ siblings in order to divide sibpairs in three categories: the best (both sibs are in good shape), the worst (both sibs are in bad shape) and an intermediate group (one sib is in good shape and the other is in bad shape). Moreover, the evaluation wanted to discover which variables are concordant among siblings; thus, concordant variables could be considered as familiar variables (determined by the environment or by genetics). 5. to perform a survival analysis by using mortality data at 1st January 2009 from the follow-up as the main outcome and selected functional and clinical parameters as explanatory variables. Methods A total of 765 90+ Italian subjects recruited by UNIBO (549 90+ siblings, belonging to 258 families) and ISS (216 90+ siblings, belonging to 106 families) recruiting units are included in the analysis. Each subject was interviewed according to a standardized questionnaire, comprising extensively utilized questions that have been validated in previous European studies on elderly subjects and covering demographic information, life style, living conditions, cognitive status (SMMSE), mood, health status and anthropometric measurements. Moreover, subjects were asked to perform some physical tests (Hand Grip Strength test and Chair Standing test) and a sample of about 24 mL of blood was collected and then processed according to a common protocol for the preparation and storage of DNA aliquots. Results From the analysis the main findings are the following: - a standardized protocol to assess cognitive status, physical performances and health status of European nonagenarian subjects was set up, in respect to ethical requirements, and it is available as a reference for other studies in this field; - GEHA families are enriched in long-living members and extreme survival, and represent an appropriate model for the identification of genes involved in healthy aging and longevity; - two simplified sets of criteria to classify 90+ sibling according to their health status were proposed, as operational tools for distinguishing healthy from non healthy subjects; - cognitive and functional parameters have a major role in categorizing 90+ siblings for the health status; - parameters such as education and good physical abilities (500 metres walking ability, going up and down the stairs ability, high scores at hand grip and chair stand tests) are associated with a good health status (defined as “cognitive unimpairment and absence of disability”); - male nonagenarians show a more homogeneous phenotype than females, and, though far fewer in number, tend to be healthier than females; - in males the good health status is not protective for survival, confirming the male-female health survival paradox; - survival after age 90 was dependent mainly on intact cognitive status and absence of functional disabilities; - haemoglobin and creatinine levels are both associated with longevity; - the most concordant items among 90+ siblings are related to the functional status, indicating that they contain a familiar component. It is still to be investigated at what level this familiar component is determined by genetics or by environment or by the interaction between genetics, environment and chance (and at what level). Conclusions In conclusion, we could state that this study, in accordance with the main objectives of the whole GEHA project, represents one of the first attempt to identify the biological and non biological determinants of successful/unsuccessful aging and longevity. Here, the analysis was performed on 90+ siblings recruited in Northern and Central Italy and it could be used as a reference for others studies in this field on Italian population. Moreover, it contributed to the definition of “successful” and “unsuccessful” aging and categorising a very large cohort of our most elderly subjects into “successful” and “unsuccessful” groups provided an unrivalled opportunity to detect some of the basic genetic/molecular mechanisms which underpin good health as opposed to chronic disability. Discoveries in the topic of the biological determinants of healthy aging represent a real possibility to identify new markers to be utilized for the identification of subgroups of old European citizens having a higher risk to develop age-related diseases and disabilities and to direct major preventive medicine strategies for the new epidemic of chronic disease in the 21st century.

Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models

Suppose that we are interested in establishing simple, but reliable rules for predicting future t-year survivors via censored regression models. In this article, we present inference procedures for evaluating such binary classification rules based on various prediction precision measures quantified by the overall misclassification rate, sensitivity and specificity, and positive and negative predictive values. Specifically, under various working models we derive consistent estimators for the above measures via substitution and cross validation estimation procedures. Furthermore, we provide large sample approximations to the distributions of these nonsmooth estimators without assuming that the working model is correctly specified. Confidence intervals, for example, for the difference of the precision measures between two competing rules can then be constructed. All the proposals are illustrated with two real examples and their finite sample properties are evaluated via a simulation study.

Inference on Survival Data with Covariate Measurement Error - An Imputation-based Approach

We propose a new method for fitting proportional hazards models with error-prone covariates. Regression coefficients are estimated by solving an estimating equation that is the average of the partial likelihood scores based on imputed true covariates. For the purpose of imputation, a linear spline model is assumed on the baseline hazard. We discuss consistency and asymptotic normality of the resulting estimators, and propose a stochastic approximation scheme to obtain the estimates. The algorithm is easy to implement, and reduces to the ordinary Cox partial likelihood approach when the measurement error has a degenerative distribution. Simulations indicate high efficiency and robustness. We consider the special case where error-prone replicates are available on the unobserved true covariates. As expected, increasing the number of replicate for the unobserved covariates increases efficiency and reduces bias. We illustrate the practical utility of the proposed method with an Eastern Cooperative Oncology Group clinical trial where a genetic marker, c-myc expression level, is subject to measurement error.

Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

Analyzing Bivariate Survival Data with Interval Sampling and Application to Cancer Epidemiology

In medical follow-up studies, ordered bivariate survival data are frequently encountered when bivariate failure events are used as the outcomes to identify the progression of a disease. In cancer studies interest could be focused on bivariate failure times, for example, time from birth to cancer onset and time from cancer onset to death. This paper considers a sampling scheme where the first failure event (cancer onset) is identified within a calendar time interval, the time of the initiating event (birth) can be retrospectively confirmed, and the occurrence of the second event (death) is observed sub ject to right censoring. To analyze this type of bivariate failure time data, it is important to recognize the presence of bias arising due to interval sampling. In this paper, nonparametric and semiparametric methods are developed to analyze the bivariate survival data with interval sampling under stationary and semi-stationary conditions. Numerical studies demonstrate the proposed estimating approaches perform well with practical sample sizes in different simulated models. We apply the proposed methods to SEER ovarian cancer registry data for illustration of the methods and theory.