Abstract

The testosterone circadian rhythm has been reported extensively in the literature and has been described by a cosine function. Typically, these data are measured at frequent and regular (e.g., hourly) intervals. However, modeling circadian rhythm with data collected sparsely at irregular intervals and/or data that are not collected at the same time in all individuals has not been reported. The population nonlinear mixed-effects approach can handle such data and also allows covariates to be incorporated into the model. Frequent hourly testosterone concentration data available in the literature for young and elderly healthy volunteers were analyzed first. In the elderly, blunted or completely absent circadian rhythm has been reported, but a full circadian model was significantly better than a model containing one or no circadian component. Therefore, data from both the elderly and young were modeled together, and age was included as a categorical variable (young or elderly). Consistent with literature, the rhythm-adjusted mean testosterone concentrations was lower, and the deviation from the mean, especially to the maximum daily value, was less than half in the elderly (7%) compared to young subjects (16%). The testosterone concentration data measured infrequently and at varying intervals in young normal men and hypogonadal men were evaluated next. Although not measured at regular frequency in each individual, the data were obtained at different clock times for different subjects. Since for population mixed-effects analysis, data from all subjects are pooled, there was enough information to profile the 24-hour circadian cycle. In healthy young subjects, the mean Cnadir, Cpeak, Tnadir, and Tpeak values estimated from the model were 420 ng/dL, 577 ng/dL, 21:42 hours, and 0600 hours, respectively, and were similar to the parameters obtained for the frequently sampled young subjects. In hypogonadal men (testosterone concentrations < 300 ng/dL), the mean testosterone concentrations were much lower than the healthy young or elderly men, and a straight-line model was the best descriptor (i.e., no circadian rhythm was detected). It was also shown that with the application of a transdermal testosterone system, the mean testosterone concentrations in the treated men were within the 95% confidence interval for healthy young men. The results presented here suggest that the advantages of the analysis approach--namely, handling of covariates and handling of sparse, infrequently collected data--can be used in characterizing testosterone circadian rhythm or the lack of it.

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