Guadalupe Gómez Melis

Two methods to analyze trends in the incidence of heroin and cocaine use in Barcelona [Spain]

OBJECTIVES To describe 2 statistical methods for estimating trends in the incidence of heroin and cocaine use in Barcelona. METHODS Admissions for treatment of heroin and cocaine consumption recorded by the Barcelona Drug Information System between 1991 and 2003 were used. We selected 4,367 subjects initiating treatment for the first time for heroin use, and 2,147 for cocaine use. Two statistical techniques were employed: Reporting Delay Adjustment (RDA) and the Log-linear Model (LLM). RDA was used in subjects who initiated drug consumption between 1991 and 2003, and LLM for those who began heroin use between 1967 and 2003 and cocaine use between 1971 and 2003. In addition, for each drug and method the latency period (LP) was determined (years between first consumption and first treatment). RESULTS Comparison of the distributions of the LP for each drug revealed that heroin users initiated treatment for the first time sooner than cocaine users, regardless of the method employed. In general, the estimated incidence of heroin use in Barcelona fell progressively after 1982. In contrast, the incidence of cocaine use rose rapidly until 1998, and has been irregular since. The incidence of cocaine use began to be substantial in the early 1990s, but took several years to manifest itself as problematic. CONCLUSION The estimated incidence was underestimated by RDA compared with LLM, but the incidence of heroin use could be biased before 1991 due to changes in treatment provisions. Although the estimated incidence is relative to individuals who are admitted for treatment at some time in their life, trends in incidence can be used to plan future actions.

Dos métodos para analizar la evolución de la incidencia de consumo de heroína y cocaína en Barcelona

Objectives: To describe 2 statistical methods for estimating trends in the incidence of heroin and cocaine use in Barcelona. Methods: Admissions for treatment of heroin and cocaine consumption recorded by the Barcelona Drug Information System between 1991 and 2003 were used. We selected 4,367 subjects initiating treatment for the first time for heroin use, and 2,147 for cocaine use. Two statistical techniques were employed: Reporting Delay Adjustment (RDA) and the Log-linear Model (LLM). RDA was used in subjects who initiated drug consumption between 1991 and 2003, and LLM for those who began heroin use between 1967 and 2003 and cocaine use between 1971 and 2003. In addition, for each drug and method the latency period (LP) was determined (years between first consumption and first treatment). Results: Comparison of the distributions of the LP for each drug revealed that heroin users initiated treatment for the first time sooner than cocaine users, regardless of the method employed. In general, the estimated incidence of heroin use in Barcelona fell progressively after 1982. In contrast, the incidence of cocaine use rose rapidly until 1998, and has been irregular since. The incidence of cocaine use began to be substantial in the early 1990s, but took several years to manifest itself as problematic. Conclusion: The estimated incidence was underestimated by RDA compared with LLM, but the incidence of heroin use could be biased before 1991 due to changes in treatment provisions. Although the estimated incidence is relative to individuals who are admitted for treatment at some time in their life, trends in incidence can be used to plan future actions.

Estimation and residual analysis with R for a linear regression model with an interval-censored covariate

Interval-censored covariates are sometimes encountered in longitudinal studies and considered as possible predictors in a regression model. This paper, motivated by an AIDS study, proposes an implementation in R for the estimation of parameters and the assessment of the assumptions of a linear regression model with an interval-censored covariate. The properties of the parameters estimators and the behavior of three proposed residuals are addressed through two simulation studies. Also, guidelines are provided to check the goodness-of-fit of the fitted model in terms of the length of the censoring interval of the covariate. The methodology is illustrated with real data coming from the AIDS study. R functions and scripts are provided.

Supervivencia en pacientes con tuberculosis infectados por VIH. Estudio de los fallecimientos en los primeros nueve meses

BACKGROUND: Among the individuals with tuberculosis who are infected with HIV a high degree of lethality has been found to exist during the first few weeks following the start of tuberculosis treatment. In this study, the survival of these individuals is studied within the framework of a retrospective cohort study. METHODS: This study included 1135 subjects infected by HIV over age fifteen and residents of Barcelona who were registered by the Barcelona Tuberculosis Prevention and Control Program and were diagnoses within the 1988-1993 period. The variables analyzed were age, gender, former imprisonment, municipal district, risk group, percentage of T CD4+ lymphocytes, tuberculin test, AIDS diagnosis (as per CDC-1987), X-ray pattern, bacteriology and part of the body affected by the tuberculosis. The Cox semiparametric method, the Kaplan-Meir curves and the log-rank test were employed. RESULTS: A 77% probability of survival during the first nine months was found to exist, with wide-ranging variations among the different subgroups. The only significant variables in the Cos multivariate model were AIDS, the percentage of T CD4+ lymphocytes and their interaction. The risk of death for an individual not having AIDS and a T CD4+ lymphocyte percentage of 14% or lower was 7.69 times higher than the risk of dying for an individual not having AIDS who had a T CD4+ lymphocyte percentage of above 14%. CONCLUSIONS: The survival of those individuals having tuberculosis who are infected with HIV varies greatly. Those who died in the short term were diagnosed as having AIDS on starting the tuberculosis treatment and who also had a T CD4+ lymphocyte percentage of 14% or lower.

Selection of composite binary endpoints in clinical trials

The choice of a primary endpoint is an important issue when designing a clinical trial. It is common to use composite endpoints as a primary endpoint because it increases the number of observed events, captures more information and is expected to increase the power. However, combining events that have no similar clinical importance and have different treatment effects makes the interpretation of the results cumbersome and might reduce the power of the corresponding tests. Gómez and Lagakos proposed the ARE (asymptotic relative efficiency) method to choose between a composite or one of its components as primary endpoint comparing the efficacy of a treatment based on the times to each of these endpoints. The aim of this paper is to expand the ARE method to binary endpoints. We show that the ARE method depends on six parameters including the degree of association between components, event proportion, and effect of therapy given by the corresponding odds ratio of the single endpoints. A case study is presented to illustrate the methodology. We conclude with efficient guidelines for discerning which could be the best suited primary endpoint given anticipated parameters.