In biomarker-disease association studies, the long-term average level of a biomarker is often considered the optimal measure of exposure. Long-term average levels may not be accurately measured from a single sample, however, because of systematic temporal variation. For example, serum 25-hydroxyvitamin D (25(OH)D) concentrations may fluctuate because of seasonal variation in sun exposure. Association studies of 25(OH)D and cancer risk have used different strategies to minimize bias from such seasonal variation, including adjusting for date of sample collection (DOSC), often after matching on DOSC, and/or using season-specific cutpoints to assign subjects to exposure categories. To evaluate and understand the impact of such strategies on potential bias, the authors simulated a population in which 25(OH)D levels varied between individuals and by season, and disease risk was determined by long-term average 25(OH)D. Ignoring temporal variation resulted in bias toward the null. When cutpoints that did not account for DOSC were used, adjustment for DOSC sometimes resulted in bias away from the null. Using season- or month-specific cutpoints reduced bias toward the null and did not cause bias away from the null. To avoid potential bias away from the null, using season- or month-specific cutpoints may be preferable to adjusting for DOSC.

Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM.

No abstract

Detrended Fluctuation Analysis (DFA) measures the complexity of a glucose time series obtained by means of a Continuous Glucose Monitoring System (CGMS) and has proven to be a sensitive marker of glucoregulatory dysfunction. Furthermore, some authors have observed a crossover point in the DFA, signalling a change of dynamics, arguably dependent on the beta-insular function. We investigate whether the characteristics of this crossover point have any influence on the risk of developing type 2 diabetes mellitus (T2DM). To this end we recruited 206 patients at increased risk of T2DM (because of obesity, essential hypertension, or a first-degree relative with T2DM). A CGMS time series was obtained, from which the DFA and the crossover point were calculated. Patients were then followed up every 6 months for a mean of 17.5 months, controlling for the appearance of T2DM diagnostic criteria. The time to crossover point was a significant predictor risk of developing T2DM, even after adjusting for other variables. The angle of the crossover was not predictive by itself but became significantly protective when the model also considered the crossover point. In summary, both a delay and a blunting of the crossover point predict the development of T2DM.

In a recent article in Pediatrics, by Kirkland et al.,1 reference is made to only 36 cases of acute suppurative thyroiditis in children. Two years ago we made a review of the literature due to two unusual cases evaluated by us, one is a 1½-year-old Negro Dominican boy2 who presented two recurrent episodes of acute suppurative thyroiditis and a 7-year-old Puerto Rican girl who presented acute suppurative strumitis, for she suffered from chronic lymphocytic thyroiditis with superimposed suppuration.