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(Circulation. 1998;97:946-952.)
© 1998 American Heart Association, Inc.


Clinical Investigation and Reports

Cholesterol Reduction Yields Clinical Benefit

Impact of Statin Trials

A. Lawrence Gould, PhD; Jacques E. Rossouw, MD; Nancy C. Santanello, MD, MSc; Joseph F. Heyse, PhD; ; Curt D. Furberg, MD

From Merch Research Laboratories, West Point, Pa (A.L.G., N.C.S., J.F.H.); NIH, Bethesda, Md (J.E.R.); and Bowman Gray School of Medicine, Winston-Salem, NC (C.D.F.).

Correspondence to A. Lawrence Gould, Merck Research Laboratories, BL3–2, West Point, PA 19486. E-mail goulda{at}merck.com


*    Abstract
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*Abstract
down arrowIntroduction
down arrowMethods
down arrowResults
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
Background—We determined the effect of incorporating the results of eight recently published trials of Hmg CoA reductase inhibitors ("statins") on the conclusions from our previously published meta-analysis regarding the clinical benefit of cholesterol lowering.

Methods and Results—We used the same analytic approach as in our previous investigation, separating the specific effects of cholesterol lowering from the effects attributable to the different types of intervention studied. The reductions in coronary heart disease (CHD) and total mortality risk observed for the statins fell near the predictions from our earlier meta-analysis. Including the statin trial findings into the calculations led to a prediction that for every 10 percentage points of cholesterol lowering, CHD mortality risk would be reduced by 15% (P<.001), and total mortality risk would be reduced by 11% (P<.001), as opposed to the values of 13% and 10%, respectively, reported previously. Cholesterol lowering in general and by the statins in particular does not increase non-CHD mortality risk.

Conclusions—Adding the results from the statin trials confirmed our original conclusion that lowering cholesterol is clinically beneficial. The relationships (slope) between cholesterol lowering and reduction in CHD and total mortality risk became stronger, and the standard error of the estimated slopes decreased by about half. Use of statins does not increase non-CHD mortality risk. The effect of the statins on CHD and total mortality risk can be explained by their lipid-lowering ability and appears to be directly proportional to the degree to which they lower lipids.


Key Words: cholesterol • meta-analysis • mortality


*    Introduction
up arrowTop
up arrowAbstract
*Introduction
down arrowMethods
down arrowResults
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
Reports on the outcome of a number of trials of Hmg CoA reductase inhibitors ("statins") have appeared1 2 3 4 5 6 7 8 since the publication of our meta-analysis demonstrating that net decreases in total serum cholesterol attributable to an intervention translate linearly to net decreases in total mortality risk and coronary heart disease (CHD) mortality risk.9 The statins represent an especially effective class of lipid-lowering drugs that were not included in the meta-analysis. We report here (1) the consistency of findings from the statin trials with the predictions based on nonstatin interventions from our earlier meta-analysis and (2) updated estimates (and standard errors) of the effects of cholesterol reduction and therapy class incorporating this new information.


*    Methods
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up arrowAbstract
up arrowIntroduction
*Methods
down arrowResults
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
We used the same methods as in our original meta-analysis,9 adding the results from eight trials of statins that were published since the meta-analysis appeared and considering additional models exploring the effect of the statin findings. Table 1Down lists the findings from the studies included in the analyses, with the findings from the eight additional trials italicized. Tables 3Down and 4Down of the published meta-analysis inadvertently excluded the Scottish study10 ; the "original" findings presented here include that study and do not differ materially from the original results.


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Table 1. Study Set


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Table 3. CHD Mortality: Estimates of Effect of Cholesterol Reduction and Influential Interventions Using the Original Study Set and After Adding Published Statin Trial Findings


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Table 4. Total Mortality: Estimates of Effect of Cholesterol Reduction and Influential Interventions Using the Original Study Set and After Adding Published Statin Trial Findings

The findings for the various causes of mortality were analyzed by use of a series of models (Table 2Down) involving separate intercepts for each of the intervention classes and either a common slope for all the interventions or separate slopes for the statins and nonstatins. The same approach was used in our earlier meta-analysis, although many fewer models were needed because fewer intervention classes were studied. These models provide a way to address such questions as, (1) Does the risk of CHD or total mortality decrease steadily as net cholesterol reduction improves, or is there even more (or less) risk reduction with large reductions in total cholesterol? (2) Is the reduction in CHD and total mortality risk realized with 2 or more years of statin therapy consistent with what might be expected from their ability to lower cholesterol, or is there some specific attribute of statins as a class that confers extra benefit? (3) Do the statins have any specific effects on non-CHD mortality?


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Table 2. Models Used to Analyze Mortality Findings

Models in Table 2Up that set the intercept to zero for a particular class of interventions as, for example, model 3 does for "other/diet" say that the intervention has no specific effect on the degree of risk reduction. This means that if the intervention has the same effect on cholesterol reduction as a concurrent control, then it has the same effect on risk reduction. This would not be true, and the intercept would not be zero, if the intervention were inherently toxic, when there would be an excess of adverse events on the intervention, including mortality, even if the intervention and control reduced cholesterol equally. The "Appendix" describes the process for identifying appropriate models. The significance levels (probability values) reported in the "Results" section were determined by use of the hierarchical testing scheme. The "Appendix" also illustrates how these significance levels are calculated.

We report here the findings for CHD, non-CHD, and total mortality. As in the original analysis, statistical significance refers to two-sided tests with {alpha}=0.05. The figures illustrate the analytic findings by plotting the observed log odds ratios for event occurrence in each trial on the y axis against the net reduction in cholesterol caused by the intervention on the x axis, with the predicted lines relating risk reduction to net cholesterol reduction for each type of intervention when appropriate. Larger studies, with many patients and many events, are represented with larger symbols on the figures because they estimate the log odds ratio more precisely than smaller studies and thus have a larger influence on the estimates of slope and intercepts; the symbol area is proportional to the variance of the log odds ratio.


*    Results
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up arrowAbstract
up arrowIntroduction
up arrowMethods
*Results
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
CHD Mortality
The only significant factors affecting CHD mortality risk reduction are net cholesterol reduction, with the same slope for all interventions, and an intercept term for hormone interventions (model 8, P=.011 to .013) in all but the primary prevention trials, which did not include hormone interventions. Our previous meta-analysis gave the same result. The facts that the intercept for statins is zero in this model and that a common slope applies for all interventions implies that (1) there is no evidence to conclude that CHD mortality risk reduction is anything other than proportional to net reduction in total cholesterol even when the cholesterol reduction is large and (2) that statins as a class or individually do not appear to have any specific effects on CHD mortality risk.

Table 3Up summarizes the computational results and gives the results from our original meta-analysis9 for comparison. Fig 1Down displays the relationship between cholesterol reduction and CHD mortality risk reduction. The slope becomes slightly more pronounced when the statin trial results are included (slope=-0.0166 versus -0.0138, a nonsignificant difference). However, the results from the statin trials fall about where the original meta-analysis would have predicted. The trials whose findings deviate most from the prediction lines (ACAPS, MARS, and MAAS) are small atheroma trials with few deaths.



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Figure 1. Observed log odds ratios and predicted lines relating log odds ratios for coronary heart disease (CHD) mortality to net improvement in percent total serum cholesterol reduction. Dashed lines present the relationships predicted from the data in our earlier meta-analysis9 ; solid line presents the relationship based on all the data included in the analysis reported here.

Total Mortality
The only significant factors affecting total mortality risk reduction are net cholesterol reduction, same slope for all interventions, and whether the intervention was a fibrate or a hormone (model 6, P<.01) when all trials and all unifactorial trials are considered, net cholesterol reduction and whether the intervention was a hormone (model 8, P<.01) when the unifactorial secondary prevention trials are considered, and net cholesterol reduction and whether the intervention was a fibrate for the primary prevention trials (model 9, P=.038) The fibrate effect loses significance (P<.05) when the WHO trial results are excluded. These findings are the same as for our previous meta-analysis, except for the primary prevention trials in which the original analysis did not reveal a significant effect of net cholesterol reduction. As with CHD mortality, there is no evidence for anything other than proportionality of total mortality risk reduction to net total cholesterol reduction, and statins as a class do not appear to have any specific effects on total mortality risk.

Table 4Up summarizes the computational results and, for comparison, the results from the original meta-analysis. Fig 2Down displays the relationship between cholesterol reduction and total mortality risk reduction. The statin trial results increase the slope slightly from what was reported in the original meta-analysis. As with CHD mortality, the results from the statin trials fall about where the original meta-analysis would have predicted.



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Figure 2. Observed log odds ratios and predicted lines relating log odds ratios for total mortality to net improvement in percent total serum cholesterol reduction. Dashed lines present the relationships predicted from the data in our earlier meta-analysis9 ; solid line presents the relationship based on all the data included in the analysis reported here. CHD indicates coronary heart disease.

Non-CHD Mortality
There is no relationship between degree of cholesterol reduction and non-CHD mortality risk. As our earlier meta-analysis found, higher risk of non-CHD mortality is associated with the use of a fibrate or a hormone (model 10; all trials, all unifactorial trials, P=.022) or just the use of a hormone (model 12; unifactorial secondary prevention trials, P=.022) or a fibrate (model 11; primary prevention trials, P=.013). The fibrate effect loses significance (P>.05) when the WHO trial results are omitted. Table 5Down summarizes the computational results and, for comparison, the results from our original meta-analysis. Fig 3Down displays the results, including the findings from the statin trials.


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Table 5. Non-CHD Mortality: Estimates of Effect of Cholesterol Reduction and Influential Interventions Using the Original Study Set and After Adding Published Statin Trial Findings



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Figure 3. Observed log odds ratios and predicted lines relating log odds ratios for non–coronary heart disease (CHD) mortality to net improvement in percent total serum cholesterol reduction. Dashed lines present the relationships predicted from the data in our earlier meta-analysis9 ; solid line presents the relationship based on all the data included in the analysis reported here.

Statin Slopes
The slope of the relationship between cholesterol reduction and mortality risk reduction is the same for statins and nonstatins. The computations for the models fitting separate slopes for statins and nonstatins that included all of the trials gave the same estimates and standard errors for the statin slopes as the computations including only the statin trials. The slopes for statins and nonstatins and their standard errors obtained by fitting models 7 (hormone intercept and separate slopes) and 8 (hormone intercept and common slope) to the unifactorial trials (without WHO) are given in Table 6Down. A simple test for a difference between the statin and nonstatin slopes—eg, (0.0125-0.0081)/{surd} = 0.0044/0.0046 <1 —confirms the conclusion of the maximum likelihood analyses that the relationship of mortality risk reduction to cholesterol reduction can be explained adequately by a common slope for statins and nonstatins.


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Table 6. Slope Relating Cholesterol Reduction and Mortality Risk Reduction


*    Discussion
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
*Discussion
down arrowAppendix 1
down arrowReferences
 
The cholesterol reductions produced by the statins studied in the trials listed in Table 1Up lead to reductions in CHD and total mortality risk that are close to the predictions from our original meta-analysis for nonfibrate, nonhormone interventions.

Including the data from the statin trials in the analyses provides a clinically modest improvement in the slopes relating CHD and total mortality to net cholesterol reduction. A net reduction in total serum cholesterol of 10 percentage points translates to an expected 15% reduction in CHD mortality risk and an expected 11% reduction in total mortality risk when the statin trial data are included, as opposed to the 13% and 10% reductions, respectively, predicted by the original meta-analysis.

The estimated effects of fibrates and hormones remain essentially unchanged: Hormones and fibrates (at least clofibrate and gemfibrozil) remain significantly associated with increased total mortality risk when the analysis includes all the trials or all the unifactorial trials. Only hormones are associated with increased risk when the analysis includes just the secondary prevention trials (all unifactorial) or, as in our earlier analysis, when the WHO trial data are omitted from the calculations.

Statin Effects
The analyses summarized in Tables 3 through 5UpUpUp establish clearly that the mortality risk reduction realized over periods of 2 years and longer in the statin trials is a consequence of the reduction in cholesterol. These analyses exclude trials of less than 2 years' duration and so cannot address possible shorter-term effects of statins on events such as plaque stabilization. The statins used in these trials do not increase non-CHD mortality risk. The rate of reduction in total or CHD mortality risk with increasing net decrease in serum cholesterol is the same for statins and nonstatins. Statins reduce CHD and total mortality risk more than other currently available therapies because they reduce cholesterol levels more effectively without increasing non-CHD mortality.


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Table 7. Times Log Likelihoods for the Models Fitted to the Data


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Table 8. Computation of Significance Levels for Models Presented in Tables 3Up and 4Up Applied to Unifactorial Trials


*    Appendix 1
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
up arrowDiscussion
*Appendix 1
down arrowReferences
 
The models in Table 2Up are naturally ordered in the sense that some models are special cases of others. For example, a model that includes a single slope for all interventions is a special case of a model that allows for separate slopes for statins and nonstatins because the separate slopes could be equal. Consequently, model 2 is a special case of model 1, model 4 is a special case of model 3, etc. Likewise, a model that includes some but not all of the intercept terms that another model includes is a special case of the model with more terms (the extra terms could be zero), so for example, models 3, 5, and 7 are special cases of model 1. This natural ordering of the models provides a way to identify appropriate models via conventional likelihood ratio tests. Table 7Up contains values of -2 times the logarithm of the likelihood for various models. The tests reported in this article all concern whether a simpler model describes the observed outcomes as well as a more complex model of which the simpler model is a special case. The additional factors of the more complex model are unlikely to be important if a simpler model describes the observed outcomes as well. Tests proceed by taking the difference between the values in Table 7Up corresponding to pairs of models differing only in the effects of interest and comparing the difference to a central {chi}2 table with degrees of freedom equal to the difference between the numbers of parameters in the models.

Table 8Up illustrates the calculation of the significance levels reported in Tables 3Up and 4Up for the unifactorial trials. The resulting significance levels apply to the model as a whole relative to any simpler model. Separate evaluations of individual parameters can be carried out in the usual way in terms of the ratio estimate/standard error.


*    Footnotes
 
The opinions expressed in this manuscript are those of the authors and do not necessarily reflect the views of the National Institutes of Health.

Received August 15, 1997; revision received November 14, 1997; accepted November 18, 1997.


*    References
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
up arrowDiscussion
up arrowAppendix 1
*References
 
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