Longitudinal case analysis in atopic dermatitis.

The current knowledge on atopic dermatitis comes mainly from cross-sectional studies, which are not suited to establish time-courses or causal links in complex diseases. As an alternative approach, the method of longitudinal case analysis by the autoregressive integrated moving average (ARIMA) method has been introduced to investigate the pathogenesis of atopic dermatitis. The method was applied to the investigation of 2 patients suffering from severe and moderate atopic dermatitis. Disease activity, peripheral blood parameters (differential blood count, lymphocyte subpopulations, immunoglobulin E, eosinophilic cationic protein, soluble interleukin-2 receptor), mental stress and environmental factors were determined daily for 50 days. Both patients showed a positive correlation between CD4+ and CD25+ T-cells, a negative correlation between CD16/56+ natural killer cells and CD4+ T-cells, a negative correlation between eosinophils and polymorphonuclear leukocytes, and a time-shifted positive correlation of up to 2 days between scores quantifying mental stress and disease activity. A positive correlation between T-cells and polymorphonuclear leukocytes, CD4+ T-cells and the CD45RA+ subtype, as well as a negative correlation between stress and eosinophils, sports and eosinophils, and sports and disease activity were found only in one patient with more severe atopic dermatitis. In conclusion, longitudinal time-series analysis might represent an interesting and adequate method to generate and test new hypotheses on biomedical problems which cannot be addressed by cross-sectional studies.