PubMed · 9646957
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K F Schulz. 1998. Randomized controlled trials.. https://doi.org/10.1097/00003081-199806000-00005
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Controlled clinical trials in neuropsychopharmacology, as in numerous other clinical research domains, tend to employ a conventional parallel-groups design with repeated measurements. The hypothesis of primary interest in the relatively short-term, double-blind trials, concerns the difference between patterns or magnitudes of change from baseline. A simple two-stage approach to the analysis of such data involves calculation of an index or coefficient of change in stage 1 and testing the significance of difference between group means on the derived measure of change in stage 2. This article has the aim of introducing formulas and a computer program for sample size and/or power calculations for such two-stage analyses involving each of three definitions of change, with or without baseline scores entered as a covariate, in the presence of homogeneous or heterogeneous (autoregressive) patterns of correlation among the repeated measurements. Empirical adjustments of sample size for the projected dropout rates are also provided in the computer program.
BACKGROUND: It has been proposed that hyperlipidemia contributes to the progression of renal disease. A large trial has not been performed; however, a number of small, controlled trials have been reported. We examined the effects of antilipemic agents on glomerular filtration rate and proteinuria or albuminuria in patients with renal disease. METHODS: We used Medline, abstracts from scientific meetings, and bibliographies from recent reviews and scientific reports to locate pertinent studies. Thirteen prospective controlled trials examining the effects of antilipemic agents on renal function, proteinuria, or albuminuria were included. Studies were published as full reports or abstracts and were at least three months in duration. For five of the studies, individual patient data were obtained. Other summary data were independently extracted from the published reports by two investigators and included study quality, subject characteristics, cause of renal disease, change in serum cholesterol, blood pressure, glomerular filtration rate, proteinuria, and albuminuria. RESULTS: There was a lower rate of decline in glomerular filtration rate with treatment compared with controls (treated controls, 0.156 mL/min/month; 95% CI, 0.026 to 0. 285 mL/min/month, P = 0.008). The study results were statistically homogeneous, and in a regression analysis, the effect of treatment on glomerular filtration rate did not correlate with study quality, the percentage change in cholesterol, the type of lipid-lowering agent, or the cause of renal disease. However, longer follow-up correlated with the amount of improvement in glomerular filtration rate from treatment (P = 0.007). There was a tendency for a favorable effect of treatment on protein or albumin excretion [Ln (treatment) - Ln (control) = -0.248, 95% CI, -0.562 to 0.064, P = 0. 077]. However, these results were statistically heterogeneous between studies (P < 0.001). No obvious explanation for this heterogeneity was apparent in a regression analysis examining potential reasons for differences in study results. CONCLUSIONS: Lipid reduction may preserve glomerular filtration rate and may decrease proteinuria in patients with renal disease.
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