J CUmEpUaubl Vol. 45, No. 12, pp. 1451-1452,1992 Printed in GreatBritain
0895-4356/92$5.00+ 0.00 Pmgmon Press Ltd
Letters to the Editors ESTIMATING THE BENEFITS OF CHOLESTEROL LOWERING ARE RISK FACTORS FOR CORONARY HEART DISEASE MULTIPLICATIVE? In his recent paper [l], Silberberg reconsidered the relationship between hypercholesterolemia and two other major coronary heart disease (CHD) risk factors (cigarette smoking and hypertension) using previously published CHD death rates from the screenee population of the Multiple Risk Factor Intervention Trial [2,3]. It was concluded that “the risk of CHD death associated with high serum cholesterol and the two other major risk factors is greater than additive, but it is largely the use of the multiple logistic model which has led to the notion that these effects are multiplicative: analyses so based may have overestimated the benefits of cholesterol lowering in smokers and hypertensives” [ 11. Although a distinction was carefully drawn between statistical interaction and biological synergism [l], the possible importance of misclassification bias in the interpretation of these data was not discussed. Random misclassification of exposures in studies such as this 6-year prospective study of 356,222 men between the ages of 35 and 57 years is to some extent inevitable [4].Furthermore, the authors of the previous report cautioned that while some of the subjects were already receiving treatment at the time of the screening, others received risk factor intervention subsequent to screening [3]. In most instances, random misclasstication of exposures biases relative risk estimates towards one. And, larger relative risk estimates may be more severely affected by misclassification than smaller ones, with a disproportionate impact on risk estimates across exposure categories [!il. Thus, the true (unbiased) relationship between these major CHD risk factors may in fact be multiplicative even though tests for goodness-of-
fit applied to data from some large prospective studies may suggest that submultiplicative or additive models are preferable. Ideally, multivariable regression methods for estimating attributable risk should be applied to determine the potential benefits of risk factor reduction alone or in combination [6,7]. The logistic model has been successfully used for this purpose and we recently proposed an alternative procedure that utilizes an additive model [A. bWJ3N s. CCKJGHLIN Department of Medicine Georgetown University School of Medicine Washington, DC 2ooo7 U.S.A. REFERENCES 1. Silbcrbcrg JS. Bstimating the benefits of cholesterol lowering: Am risk factors for coronary heart disease multiplicative? J CUn Epl&mlol 1990.43: 875-879. 2. Stamlcr J, Wentworth D, Ncaton ID, for the MRFIT Remarch Croup. Is the relationship between mrum cholesterol and risk of premature death from coronary heart disease continuous and graded?JAMA 1986;256: 2823-2828. 3. Martin MJ, Jull9 SB, Browner WS et al. Serum cholesterol, blocd pressure, and mortality: Implications from a cohort of 361,662 men. Lanmt 1986; 11: 933-936. 4. Coughlin SS. Mis&&ication Bias in a Multivariate Sctti& Coronary Heart Disease Risk Factors. Masters thesis. San Dieno state univcrsitv, 1984. 5. Glad& B, Rog& WJ. Misclassifi&tion and the design of cnviromnental studies. Am J E@anbl 1979; 109: 607616. WE, Helms MI et crl.Logistic 6. Deubner DC, Wiion model estimation of death attributable to risk factors for cardiovawlar disease in Evans County, Georgia. Am J Epldanbl 1980; 112: 135-143. I. Coughlin SS, Nass CC, Pickle LW et al. Regression methods for estimating attributable risk in populationbased case-control studies: A comparison of additive and multiplicative models. Am J Epidemloll991; 133: 305-313.
E&ors’ Note-In accordance with Journal policy, this letter was sent to Dr Silbcrbcrg for a response. He preferred not to reply. 1451
0895-4356/92$5.00+ 0.00 Pmgmon Press Ltd
Letters to the Editors ESTIMATING THE BENEFITS OF CHOLESTEROL LOWERING ARE RISK FACTORS FOR CORONARY HEART DISEASE MULTIPLICATIVE? In his recent paper [l], Silberberg reconsidered the relationship between hypercholesterolemia and two other major coronary heart disease (CHD) risk factors (cigarette smoking and hypertension) using previously published CHD death rates from the screenee population of the Multiple Risk Factor Intervention Trial [2,3]. It was concluded that “the risk of CHD death associated with high serum cholesterol and the two other major risk factors is greater than additive, but it is largely the use of the multiple logistic model which has led to the notion that these effects are multiplicative: analyses so based may have overestimated the benefits of cholesterol lowering in smokers and hypertensives” [ 11. Although a distinction was carefully drawn between statistical interaction and biological synergism [l], the possible importance of misclassification bias in the interpretation of these data was not discussed. Random misclassification of exposures in studies such as this 6-year prospective study of 356,222 men between the ages of 35 and 57 years is to some extent inevitable [4].Furthermore, the authors of the previous report cautioned that while some of the subjects were already receiving treatment at the time of the screening, others received risk factor intervention subsequent to screening [3]. In most instances, random misclasstication of exposures biases relative risk estimates towards one. And, larger relative risk estimates may be more severely affected by misclassification than smaller ones, with a disproportionate impact on risk estimates across exposure categories [!il. Thus, the true (unbiased) relationship between these major CHD risk factors may in fact be multiplicative even though tests for goodness-of-
fit applied to data from some large prospective studies may suggest that submultiplicative or additive models are preferable. Ideally, multivariable regression methods for estimating attributable risk should be applied to determine the potential benefits of risk factor reduction alone or in combination [6,7]. The logistic model has been successfully used for this purpose and we recently proposed an alternative procedure that utilizes an additive model [A. bWJ3N s. CCKJGHLIN Department of Medicine Georgetown University School of Medicine Washington, DC 2ooo7 U.S.A. REFERENCES 1. Silbcrbcrg JS. Bstimating the benefits of cholesterol lowering: Am risk factors for coronary heart disease multiplicative? J CUn Epl&mlol 1990.43: 875-879. 2. Stamlcr J, Wentworth D, Ncaton ID, for the MRFIT Remarch Croup. Is the relationship between mrum cholesterol and risk of premature death from coronary heart disease continuous and graded?JAMA 1986;256: 2823-2828. 3. Martin MJ, Jull9 SB, Browner WS et al. Serum cholesterol, blocd pressure, and mortality: Implications from a cohort of 361,662 men. Lanmt 1986; 11: 933-936. 4. Coughlin SS. Mis&&ication Bias in a Multivariate Sctti& Coronary Heart Disease Risk Factors. Masters thesis. San Dieno state univcrsitv, 1984. 5. Glad& B, Rog& WJ. Misclassifi&tion and the design of cnviromnental studies. Am J E@anbl 1979; 109: 607616. WE, Helms MI et crl.Logistic 6. Deubner DC, Wiion model estimation of death attributable to risk factors for cardiovawlar disease in Evans County, Georgia. Am J Epldanbl 1980; 112: 135-143. I. Coughlin SS, Nass CC, Pickle LW et al. Regression methods for estimating attributable risk in populationbased case-control studies: A comparison of additive and multiplicative models. Am J Epidemloll991; 133: 305-313.
E&ors’ Note-In accordance with Journal policy, this letter was sent to Dr Silbcrbcrg for a response. He preferred not to reply. 1451
