Author/Authors :
E. M. Hauge، نويسنده , , Le. Mosekilde، نويسنده , , F. Melsen، نويسنده , , M. Frydenberg، نويسنده ,
Abstract :
In osteoporosis research, bone histomorphometry plays an important role in documenting the biological effects and possible side-effects of new drug treatments. To ensure that the study is properly scaled, it is important to be concerned with the risk of type II error; that is, the risk of failing to detect a real difference. We therefore calculated the necessary sample size in bone histomorphometric studies according to a specified difference of 15% between two groups. The calculations were based on variance components estimated from three different studies: women with a distal fracture of the forearm (n = 22); patients with pituitary insufficiency (n = 21); and patients with primary hyperparathyroidism (n = 21). Using a significance level of 0.05 and a risk of type II error of 0.20, the statistical power of two different designs was compared: a single biopsy design comparing the responses in two groups after the treatment; and a paired biopsy design in which individual differences (posttreatment minus baseline) were calculated before the comparison of the two groups. We found that the mineral apposition rate, wall thickness, and erosion depth are statistically powerful indices that, in the single biopsy design, require no more than N = 25 in each group to detect differences of 15% between the groups. Bone volume, erosion surface, osteoid surface, mineralizing surface, and activation frequency need group sizes of 100–600 individuals to find a 15% difference to be statistically significant. However, the effect of bisphosphonate treatment, for instance, is large enough to reduce the group size to 20 individuals concerning activation frequency. The remodeling balance reaches extreme group sizes of several thousand for a 15% difference to be statistically significant, but for a 5 μm (approximately 150%) improvement, about 100 individuals are required in the single biopsy design. An analysis of the components of variance showed that the variation between individuals is small and often negligible compared with the variation within individuals, and sample sizes needed for the paired biopsy design are therefore larger than those for the single biopsy design. In conclusion, the most cost-effective histomorphometric study design within a randomized clinical trial appears to be a single biopsy design comparing posttreatment biopsies with scaling performed according to the statistical power of the indices of interest.
Keywords :
Bone histomorphometry , Method evaluation , study design , Variancecomponents , osteoporosis , Metabolic bonediseases.