To the Editor:
The recent editorial by Greenland and colleagues1 highlights the utility of cardiac risk prediction algorithms and points to several important advantages and disadvantages of existing risk equations based on the Framingham Heart Study. Although the excellent observational data obtained from Framingham may be useful for absolute risk estimation, it may not be the best source of information to estimate risk reduction. We propose that better models for estimating the benefits of an intervention can be derived from the vast pool of data found in recently published interventional trials.2 3 4
These studies have demonstrated both the safety and efficacy of HMG-CoA reductase inhibitors in tens of thousands of subjects followed up for years and include all relevant risk factor profiles. In these studies, the risk factor distributions were expanded by design to enhance their generalizability. A key feature of these large trials is that they provide reasonable numbers of clinically relevant events so that the cardioprotective effect of the therapeutic intervention can be accurately estimated.
This last issue highlights a limitation in the estimation of risk reduction from observational cohort data. Existing models assume that the risk associated with a population-based level of some risk factor (eg, LDL cholesterol) is the same as the risk in an individual who achieves that level via therapy. This assumption may be incorrect. For instance, application of the Framingham equations5 to estimate risk reduction due to LDL change in the WOSCOPS (West of Scotland Coronary Prevention Study) population underestimates the observed risk reduction due to statin therapy.
This study and a related one6 also demonstrated that baseline risk in WOSCOPS placebo subjects was comparable to Framingham-predicted risk. This suggests that prediction models based on interventional trials can be used both for estimation of baseline risk and for estimation of risk reduction due to therapy. Risk equations from the large clinical trials can represent a significant advance in determining the risks and benefits of treatment.
- Copyright © 1999 by American Heart Association
Greenland P, Grundy S, Pasternak RC, Lenfant C. Problems on the pathway from risk assessment to risk reduction. Circulation. 1998;97:1761–1762.
Sacks FM, Pfeffer MA, Moye LA, Rouleau JL, Rutherford JD, Cole TG, Brown L, Warnica JW, Arnold JM, Wun CC, Davis BR, Braunwald E. The effect of pravastatin on coronary events after myocardial infarction in subjects with average cholesterol levels: Cholesterol and Recurrent Events Trial Investigators. N Engl J Med. 1996;335:1001–1009.
Downs JR, Clearfield M, Weis S, Whitney E, Shapiro DR, Beere PA, Langendorfer A, Stein EA, Kruyer W, Gotto AM Jr. Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels: Results of AFCAPS/TexCAPS: Air Force/Texas Coronary Atherosclerosis Prevention Study. JAMA. 1998;279:1615–1622.
The West of Scotland Coronary Prevention Study Group. Influence of pravastatin and plasma lipids on clinical events in the West of Scotland Coronary Prevention Trial. Circulation. 1998;97:1440–1445.