(Circulation. 2006;114:e506.)
© 2006 American Heart Association, Inc.
Correspondence |
Cardiology Department, Cantonal Hospital, Olten, Switzerland
Research Laboratories, diagene Inc, Reinach, Switzerland
We read with great interest the report by Schmermund et al1 that failed to demonstrate a difference in progression of coronary calcium (CAC) in asymptomatic, nondiseased subjects when treated with 10 mg versus 80 mg atorvastatin for 12 months. The authors expected that in 471 patients, a significantly lower progression of CAC scores and differences between groups of patients treated with 10 mg versus 80 mg atorvastatin could be observed.
The study by Schmermund et al1 was carried out in a low-risk to intermediate-risk population. Based on previous studies, it is possible that a much larger population would have been required to detect any differences. In addition, the study was not placebo-controlled but tried to discover differences between 2 groups of patients having low-density lipoprotein cholesterol reductions of 30.1% (10 mg) versus 43.1% (80 mg).
Most important, however, the authors calculated a sample size of n=190, necessary to detect a CAC difference of 10%. The authors reference Callister et al2 for their estimate of the CAC score standard deviation (SD). Callister et al2 observed SDs of mean CAC of greater than 100% (ranging from ±118% to ±203%). The SDs of the mean CAC differences within a group were between ±107% and ±212%. When we use the median of the SDs given by Callister et al (±171%), then we calculate a sample size of several thousand subjects to detect a difference of 10% (P=0.05, power of 0.90). However, Schmermund et al choose an SD of ±30% for their subsequent power calculation. This has a dramatic effect on the sample size necessary to detect such small differences. In Table 2, Schmermund et al confirmed high SDs in their own data (median, ±144%) but did not take this information into account when performing their power calculations. We do not know whether the CAC score data were normally distributed or not; the mean and median values differed greatly, however, suggesting that the data are skewed. If this assumption is correct, then it would have been more appropriate to transform the data or use nonparametric statistical tests.
Thus, in our opinion, the study by Schmermund et al does not allow one to draw the conclusion that CAC score might not be a reliable predictor of cardiac events.3 Prospective studies involving large numbers of patients will be necessary to answer this question.
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