How to analyze continuous and discrete repeated measures in small-sample cross-over trials?

To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data. The recommendation of which methodology to use in rare disease trials with a repeated measures cross-over design depends on the type of outcome and the number of time points the treatment has an effect on. The non-parametric marginal model testing the treatment-time-interaction effect is suitable for detecting between group differences in the shapes of the longitudinal profiles. For binary outcomes with the treatment effect on a single time point, the parametric model averaging method is recommended, while in the other cases the unmatched generalized pairwise comparison methodology is recommended. Both provide an easily interpretable effect size measure, and do not require exclusion of periods or subjects due to incompleteness.

Neutrophil extracellular trap (NET) formation characterises stable and exacerbated COPD and correlates with airflow limitation.

BACKGROUND: COPD is a progressive disease of the airways that is characterized by neutrophilic inflammation, a condition known to promote the excessive formation of neutrophil extracellular traps (NETs). The presence of large amounts of NETs has recently been demonstrated for a variety of inflammatory lung diseases including cystic fibrosis, asthma and exacerbated COPD. OBJECTIVE: We test whether excessive NET generation is restricted to exacerbation of COPD or whether it also occurs during stable periods of the disease, and whether NET presence and amount correlates with the severity of airflow limitation. PATIENTS, MATERIALS AND METHODS: Sputum samples from four study groups were examined: COPD patients during acute exacerbation, patients with stable disease, and smoking and non-smoking controls without airflow limitation. Sputum induction followed the ECLIPSE protocol. Confocal laser microscopy (CLSM) and electron microscopy were used to analyse samples. Immunolabelling and fluorescent DNA staining were applied to trace NETs and related marker proteins. CLSM specimens served for quantitative evaluation. RESULTS: Sputum of COPD patients is clearly characterised by NETs and NET-forming neutrophils. The presence of large amounts of NET is associated with disease severity (p < 0.001): over 90 % in exacerbated COPD, 45 % in stable COPD, and 25 % in smoking controls, but less than 5% in non-smokers. Quantification of NET-covered areas in sputum preparations confirms these results. CONCLUSIONS: NET formation is not confined to exacerbation but also present in stable COPD and correlates with the severity of airflow limitation. We infer that NETs are a major contributor to chronic inflammatory and lung tissue damage in COPD.