Sudden unexplained infant death in 20 regions in Europe: case control study.

BACKGROUND: After striking changes in rates of sudden unexplained infant death (SIDS) around 1990, four large case-control studies were set up to re-examine the epidemiology of this syndrome. The European Concerted Action on SIDS (ECAS) investigation was planned to bring together data from these and new studies to give an overview of risk factors for the syndrome in Europe. METHODS: We undertook case-control studies in 20 regions. Data for more than 60 variables were extracted from anonymised records of 745 SIDS cases and 2411 live controls. Logistic regression was used to calculate odds ratios (ORs) for every factor in isolation, and to construct multivariate models. FINDINGS: Principal risk factors were largely independent. Multivariately significant ORs showed little evidence of intercentre heterogeneity apart from four outliers, which were eliminated. Highly significant risks were associated with prone sleeping (OR 13.1 [95% CI 8.51-20.2]) and with turning from the side to the prone position (45.4 [23.4-87.9]). About 48% of cases were attributable to sleeping in the side or prone position. If the mother smoked, significant risks were associated with bed-sharing, especially during the first weeks of life (at 2 weeks 27.0 [13.3-54.9]). This OR was partly attributable to mother's consumption of alcohol. Mother's alcohol consumption was significant only when baby bed-shared all night (OR increased by 1.66 [1.16-2.38] per drink). For mothers who did not smoke during pregnancy, OR for bed-sharing was very small (at 2 weeks 2.4 [1.2-4.6]) and only significant during the first 8 weeks of life. About 16% of cases were attributable to bed-sharing and roughly 36% to the baby sleeping in a separate room. INTERPRETATION: Avoidable risk factors such as those associated with inappropriate infants' sleeping position, type of bedding used, and sleeping arrangements strongly suggest a basis for further substantial reductions in SIDS incidence rates.

The analysis of complex patterns of longitudinal binary response: an example of transient dysphagia following radiotherapy.

In many clinical trials, treatment is given in phases and the prevalence of symptoms is recorded longitudinally. As a result, complex non-linear response patterns may be observed as the prevalence of symptoms changes as a consequence of treatment. In such cases, although profiles of the marginal response over time give an informative description of the data, they do not allow a formal treatment comparison or adjustment for covariates of interest. Here we analyse previously reported data on transient dysphagia in patients with non-small-cell lung cancer treated with radiotherapy. We use a generalized estimating equation approach for repeated measurement binary response to give robust standard errors taking account of the dependence of observations taken on the same subject, alongside a natural cubic spline to represent the complex shape of the marginal response. This provides a reasonable model for the marginal response and allows unbiased estimation of an apparent treatment difference. The effect of different choices for the working correlation matrix is discussed, as is the modelling of treatment group differences that vary over time. We conclude that these models provide a powerful tool for the analysis of such data that can now be applied using generally accessible software.

Is there a general tendency for CD4 lymphocyte decline to speed up during human immunodeficiency virus infection? Evidence from the Italian Seroconversion Study.

It has been suggested that the rate of CD4 cell decline accelerates in parallel with decreasing numbers of cells; however, the statistical literature suggests the opposite. CD4 cells were counted about every 6 months in a cohort of 1264 human immunodeficiency virus-infected subjects (the Italian Seroconversion Study cohort). Kaplan-Meier analysis was used to estimate the time for CD4 cells to decline by 100 cells/mm3, conditional on reaching predefined levels. In addition, CD4 cell counts were modeled as a function of time since seroconversion in individuals with > or = 5 counts. Kaplan-Meier survival times for a 100 cell/mm3 decrease in CD4 cells increased as lower counts were reached (log rank test, P < .001). The shape of the overall fitted curve of the CD4 cell counts does not suggest an increasing rate of decline. Data from the Italian Seroconversion Study cohort do not show a general tendency for accelerating CD4 cell decline in association with lower counts.