- Email: [email protected]
Left Ventricular Mass Assessment by Real-Time Three-Dimensional Echocardiography
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The American Journal of Cardiology (www.AJConline.org)
ing— executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/ASNC Committee to Revise the 1995 Guidelines for the Clinical Use of Cardiac Radionuclide Imaging). J Am Coll Cardiol 2003;42:1318 –1333. Management of stable angina pectoris. Recommendations of the Task Force of the European Society of Cardiology. Eur Heart J 1997;18:394 – 413. Tandogan I, Yetkin E, Ileri M, Ortapamuk H, Yanik A, Cehreli S, Duru E. Diagnosis of coronary artery disease with Tl-201 SPECT in patients with left bundle branch block: importance of alternative interpretation approaches for left anterior descending coronary lesions. Angiology 2001;52:103–108. Higgins JP, Williams G, Nagel JS, Higgins JA. Left bundle-branch block artifact on single photon emission computed tomography with technetium Tc 99m (Tc-99m) agents: mechanisms and a method to decrease falsepositive interpretations. Am Heart J 2006; 152:619 – 626. Duncan AM, Francis DP, Gibson DG, Henein MY. Differentiation of ischemic from nonischemic cardiomyopathy during dobutamine stress by left ventricular long-axis function: additional effect of left bundle-branch block. Circulation 2003;108:1214 –1220. Tandogan I, Yetkin E, Yanik A, Ulusoy FV, Temizhan A, Cehreli S, Sasmaz A. Comparison of thallium-201 exercise SPECT and dobutamine stress echocardiography for diagnosis of coronary artery disease in patients with left bundle branch block. Int J Cardiovasc Imaging 2001;17:339 –345. Geleijnse ML, Vigna C, Kasprzak JD, Rambaldi R, Salvatori MP, Elhendy A, Cornel JH, Fioretti PM, Roelandt JR. Usefulness and limitations of dobutamine-atropine stress echocardiography for the diagnosis of coronary artery disease in patients with left bundle branch block. A multicentre study. Eur Heart J 2000; 21:1666 –1673. Candell-Riera J, Oller-Martinez G, PereztolValdes O, Castell-Conesa J, Aguade-Bruix S, Soler-Peter M, Simo M, Santana-Boado C, Soler-Soler J. Usefulness of myocardial perfusion SPECT in patients with left bundle branch block and previous myocardial infarction. Heart 2003;89:1039. Vigna C, Stanislao M, De Rito V, Russo A, Santoro T, Fusilli S, Valle G, Natali R, Fanelli R, Lotrionte M, et al. Inaccuracy of dipyridamole echocardiography or scintigraphy for the diagnosis of coronary artery disease in patients with both left bundle branch block and left ventricular dysfunction. Int J Cardiol 2006;110: 116 –118. Yanik A, Yetkin E, Senen K, Atak R, Ileri M, Kural T, Goksel S. Value of dobutamine stress echocardiography for diagnosis of coronary artery disease in patients with left bundle branch blockage. Coron Artery Dis 2000;11:545–548. Kroenke K, Mangelsdorf AD. Common symptoms in ambulatory care: incidence, evaluation, therapy, and outcome. Am J Med 1989; 86:262– 266. Pryor DB, Harrell FE Jr, Lee KL, Califf RM, Rosati RA. Estimating the likelihood of significant coronary artery disease. Am J Med 1983;75:771–780.
18. Chaitman BR, Bourassa MG, Davis K, Rogers WJ, Tyras DH, Berger R, Kennedy JW, Fisher L, Judkins MP, Mock MB, Killip T. Angiographic prevalence of high risk coronary artery disease in patient subsets (CASS). Circulation 1981;64:360 –367. 19. Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary artery disease. N Engl J Med 1979; 300:1350 –1358. 20. Detry JR, Kapita BM, Cosyns J, Sottiain B, Brasseur LA, Roussea MF. Diagnostic value of history and maximal exercise electrocardiography in men and women suspected of coronary artery disease. Circulation 1977;56:756 –761. doi:10.1016/j.amjcard.2006.12.002
Left Ventricular Mass Assessment by Real-Time Three-Dimensional Echocardiography We read with interest the report titled “Comparison of Real-Time ThreeDimensional Echocardiography to Magnetic Resonance Imaging for Assessment of Left Ventricular Mass” by van den Bosch et al,1 who used real-time 3-dimensional echocardiography (RT3DE) to estimate left ventricular (LV) mass and compared the results with those obtained using magnetic resonance imaging, the present gold standard for the estimation of LV mass. We do not agree with the investigators’ statement that RT3DE has not been used in the past for the evaluation of abnormally shaped left ventricles. This method has indeed been used for the evaluation of abnormally shaped left and right ventricles. Mor-Avi et al,2 who studied patients with abnormal left ventricles secondary to coronary artery disease, dilated cardiomyopathies, myocardial infarction, and aortic and mitral valvular heart disease, found a better correlation of this method with magnetic resonance imaging for the estimation of LV mass. Right ventricles with normal and abnormal shapes were studied in 16 patients by Vogel et al,3 who found RT3DE an unsatisfactory tool for right ventricular mass calculation despite obtaining good-quality images in all 16 patients. In the present study,1 however, the investigators obtained good- and moderate-quality images in only 70% of their patients (45% with good-quality images and 25% with moderate-quality). Given that all patients were in sinus rhythm and had a mean heart rate of 67 ⫾ 7.7 beats/min, this would limit the ability of RT3DE to find application in a real-world population, because only 70% of patients (prob-
ably fewer) would benefit from its use in the population studied. The low interobserver variability for LV mass reported by the investigators is rather illusory. Given that variability between 2 observers is always greater for patients compared with normal subjects,4,5 contemporary published research reports interobserver variability of 12.5% (range 1% to 26%) for normal subjects.6 Most of the patients had some kind of operative procedure (thus explaining the poor yield of good-quality images of only 45%), we are compelled to think that no difference in interobserver variability represents an underestimation, because observers would have fewer than half the total number of good-quality images to delineate and extrapolate, when necessary, the endocardial and epicardial borders. Despite the advent of matrix-array transducers and enhanced techniques for signal compression, low image resolution, low frame rates, and the need to extrapolate endocardial and epicardial borders are factors that could force even experienced observers to err with accurate semiautomatic border delineation. Anurag Singh, MD Koteswara R. Pothineni, MD, MPH Sadik R. Panwar, MBBS Birmingham, Alabama 3 March 2006
1. Van den Bosch AE, Robbers-Visser D, Krenning BJ, McGhie JS, Helbing WA, Meijboom FJ, Roos-Hesselink JW. Comparison of realtime three-dimensional echocardiography to magnetic resonance imaging for assessment of left ventricular mass. Am J Cardiol 2006;97: 113–117. 2. Mor-Avi V, Sugeng L, Weinert L, MacEneaney P, Caiani EG, Koch R, Salgo IS, Lang RM. Fast measurement of left ventricular mass with real-time three-dimensional echocardiography: comparison with magnetic resonance imaging. Circulation 2004;110:1814 – 1818. 3. Vogel M, Gutberlet M, Dittrich S, Hosten N, Lange PE. Comparison of transthoracic three dimensional echocardiography with magnetic resonance imaging in the assessment of right ventricular volume and mass. Heart 1997;78: 127–130. 4. Gottdiener JS, Livengood SV, Meyer PS, Chase GA. Should echocardiography be performed to assess effects of antihypertensive therapy? Test-retest reliability of echocardiography for measurement of left ventricular mass and function. J Am Coll Cardiol 1995;25:424 – 430. 5. Kitchener HF, Keep LL, Morin G, Chitin MD, Schiller NB. Echocardiography in serial evaluation of left ventricular systolic and diastolic function: importance of image acquisition,
Readers Comments
1181
quantitation, and physiologic variability in clinical and investigational applications. J Am Soc Echocardiogr 1991;4:203–214. 6. Caiani EG, Corsi C, Sugeng L, MacEneaney P, Weinert L, Mor-Avi V, Lang RM. Improved quantification of left ventricular mass based on endocardial and epicardial surface detection with real time three dimensional echocardiography. Heart 2006;92:213–219. doi:10.1016/j.amjcard.2006.03.072
Statin Use and Age at Death: Evidence of a Flawed Analysis We read with great interest the recently published report by Mehta et al1 on the effects of statin use on mortality. The report addresses a very important clinical issue. It must be expected that the results might have a major impact on future treatment recommendations, particularly for elderly subjects with elevated lipid levels. It is therefore crucial that the published results rest on sound scientific method and analysis driven by clarity and rigor. In our opinion, however, the study had severe methodologic problems in its design and analysis that call into question the validity and applicability of the results and conclusion. First, the study population was not clearly defined. Apparently, it consisted of all eligible veterans who at some point in time from January 1, 1996, to March 31, 2004, were associated with 10 health centers. If this is correct, it is unclear what the investigators presented in Table 3, which supposedly lists baseline characteristics for the study population. At what date, for example, was age computed? Second, the sampling scheme of the study seems not to have been addressed adequately in the analysis. To become registered as a user of statins, a patient must obviously first survive into the study period and then have a prescription recorded before loss to follow-up or death. Either the investigators did not consider this aspect in the analysis, or they did not describe it in sufficient detail to allow critical appraisal. To illustrate the potential effects of ignoring the sampling scheme, we conducted a simulation study, in which a given treatment has no effect on mortality. As in Mehta et al’s1 study, the mortality followed a Weibull distribution for a population with a constant birth process, and the incidence rate of (chronic) drug use increased linearly with age for ages ⬎35 years, whereas the incidence rate was zero for ages ⬍35 years. Users of the drug were assumed to present prescriptions every 2 months after the onset of treatment, and everyone resided within the capture area throughout their entire
Figure 1. Distribution of age at death stratified on observed treatment status within an 8-year period. Simulated data with no treatment effect, but incidence of treatment onset increases with age.
lives. Subjects were classified as treated if filled prescriptions were observed within the 8-year period. At the start of the observation period (“baseline”), the difference in mean age between treated and untreated subjects closely resembled the mean difference in age at death, coinciding with the results of Mehta et al.1 The 2 histograms of age at death in all who died in the observation period for the 2 groups are shown in Figure 1. Not only was the mean age at death greater in treated patients, the distribution was also narrower for the treated patients, as in the study by Mehta et al.1 It should be noted that if the incidence rate of treatment onset were to decrease with age, the mean lifetimes between the 2 groups would be reversed (i.e., those who were treated would apparently now live for a shorter period). In other words, histograms based on this type of data merely reflect the difference in age distribution between treated and untreated subjects, absent other factors, and the difference observed by Mehta et al1 can therefore not be taken as evidence of improved survival due to statin treatment. Although ignoring the sampling scheme invalidates the study in itself, several other problems deserve to be mentioned, the most severe being the use of forward selection algorithms. It is well known in statistical research that this method cannot but create biased estimates with inflated statistical significance, because by definition, it uses statistical significance for the inclusion of covariates.2,3 Furthermore, as a general rule, the timing of measurements was not described, hindering the valid interpretation of results. When was comedication measured? Before, during, or after treatment with st-
atins, or at any time, as with statins? What was meant by posttreatment change in untreated individuals? For these questions and several others, Mehta et al1 provided no useful information. It is unfortunate that Mehta et al1 missed the opportunity to use a unique body of data to provide a scientifically sound answer to a pressing clinical question. Instead of using proved epidemiologic methods, they seem to have relied on computer-intensive analysis of a massive data set without considering how the methods fit the research questions posed. From our point of view, some variant of a nested case-control study or a retrospective cohort study might well have contributed definitive and valuable insight into the real benefits of treatment with statins in the elderly. Although Mehta et al1 suggested that the sheer amount of data led to unbiased estimates and can compensate for analytical shortcuts, we respectfully submit that methodologic problems only become propounded when data are very numerous. We consider the study by Mehta et al1 excellent proof of this rule. Henrik Støvring, PhD, MSc Dorte Gilså Hansen, PhD, MD Lene Jarlbæk, MD, PhD Helle Wallach Kildemoes, MPH, MA Jørgen Lous, MD Morten Andersen, PhD, MD Odense, Denmark 10 January 2007
1. Mehta JL, Bursac Z, Hauer-Jensen M, Fort C, Fink LM. Comparison of mortality rates in statin users versus nonstatin users in a United States veteran population. Am J Cardiol 2006;98:923–928. 2. Miller AJ. Selection of subsets of regression variables. J R Stat Soc A 1984;147:389 – 425.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
The American Journal of Cardiology (www.AJConline.org)
ing— executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/ASNC Committee to Revise the 1995 Guidelines for the Clinical Use of Cardiac Radionuclide Imaging). J Am Coll Cardiol 2003;42:1318 –1333. Management of stable angina pectoris. Recommendations of the Task Force of the European Society of Cardiology. Eur Heart J 1997;18:394 – 413. Tandogan I, Yetkin E, Ileri M, Ortapamuk H, Yanik A, Cehreli S, Duru E. Diagnosis of coronary artery disease with Tl-201 SPECT in patients with left bundle branch block: importance of alternative interpretation approaches for left anterior descending coronary lesions. Angiology 2001;52:103–108. Higgins JP, Williams G, Nagel JS, Higgins JA. Left bundle-branch block artifact on single photon emission computed tomography with technetium Tc 99m (Tc-99m) agents: mechanisms and a method to decrease falsepositive interpretations. Am Heart J 2006; 152:619 – 626. Duncan AM, Francis DP, Gibson DG, Henein MY. Differentiation of ischemic from nonischemic cardiomyopathy during dobutamine stress by left ventricular long-axis function: additional effect of left bundle-branch block. Circulation 2003;108:1214 –1220. Tandogan I, Yetkin E, Yanik A, Ulusoy FV, Temizhan A, Cehreli S, Sasmaz A. Comparison of thallium-201 exercise SPECT and dobutamine stress echocardiography for diagnosis of coronary artery disease in patients with left bundle branch block. Int J Cardiovasc Imaging 2001;17:339 –345. Geleijnse ML, Vigna C, Kasprzak JD, Rambaldi R, Salvatori MP, Elhendy A, Cornel JH, Fioretti PM, Roelandt JR. Usefulness and limitations of dobutamine-atropine stress echocardiography for the diagnosis of coronary artery disease in patients with left bundle branch block. A multicentre study. Eur Heart J 2000; 21:1666 –1673. Candell-Riera J, Oller-Martinez G, PereztolValdes O, Castell-Conesa J, Aguade-Bruix S, Soler-Peter M, Simo M, Santana-Boado C, Soler-Soler J. Usefulness of myocardial perfusion SPECT in patients with left bundle branch block and previous myocardial infarction. Heart 2003;89:1039. Vigna C, Stanislao M, De Rito V, Russo A, Santoro T, Fusilli S, Valle G, Natali R, Fanelli R, Lotrionte M, et al. Inaccuracy of dipyridamole echocardiography or scintigraphy for the diagnosis of coronary artery disease in patients with both left bundle branch block and left ventricular dysfunction. Int J Cardiol 2006;110: 116 –118. Yanik A, Yetkin E, Senen K, Atak R, Ileri M, Kural T, Goksel S. Value of dobutamine stress echocardiography for diagnosis of coronary artery disease in patients with left bundle branch blockage. Coron Artery Dis 2000;11:545–548. Kroenke K, Mangelsdorf AD. Common symptoms in ambulatory care: incidence, evaluation, therapy, and outcome. Am J Med 1989; 86:262– 266. Pryor DB, Harrell FE Jr, Lee KL, Califf RM, Rosati RA. Estimating the likelihood of significant coronary artery disease. Am J Med 1983;75:771–780.
18. Chaitman BR, Bourassa MG, Davis K, Rogers WJ, Tyras DH, Berger R, Kennedy JW, Fisher L, Judkins MP, Mock MB, Killip T. Angiographic prevalence of high risk coronary artery disease in patient subsets (CASS). Circulation 1981;64:360 –367. 19. Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary artery disease. N Engl J Med 1979; 300:1350 –1358. 20. Detry JR, Kapita BM, Cosyns J, Sottiain B, Brasseur LA, Roussea MF. Diagnostic value of history and maximal exercise electrocardiography in men and women suspected of coronary artery disease. Circulation 1977;56:756 –761. doi:10.1016/j.amjcard.2006.12.002
Left Ventricular Mass Assessment by Real-Time Three-Dimensional Echocardiography We read with interest the report titled “Comparison of Real-Time ThreeDimensional Echocardiography to Magnetic Resonance Imaging for Assessment of Left Ventricular Mass” by van den Bosch et al,1 who used real-time 3-dimensional echocardiography (RT3DE) to estimate left ventricular (LV) mass and compared the results with those obtained using magnetic resonance imaging, the present gold standard for the estimation of LV mass. We do not agree with the investigators’ statement that RT3DE has not been used in the past for the evaluation of abnormally shaped left ventricles. This method has indeed been used for the evaluation of abnormally shaped left and right ventricles. Mor-Avi et al,2 who studied patients with abnormal left ventricles secondary to coronary artery disease, dilated cardiomyopathies, myocardial infarction, and aortic and mitral valvular heart disease, found a better correlation of this method with magnetic resonance imaging for the estimation of LV mass. Right ventricles with normal and abnormal shapes were studied in 16 patients by Vogel et al,3 who found RT3DE an unsatisfactory tool for right ventricular mass calculation despite obtaining good-quality images in all 16 patients. In the present study,1 however, the investigators obtained good- and moderate-quality images in only 70% of their patients (45% with good-quality images and 25% with moderate-quality). Given that all patients were in sinus rhythm and had a mean heart rate of 67 ⫾ 7.7 beats/min, this would limit the ability of RT3DE to find application in a real-world population, because only 70% of patients (prob-
ably fewer) would benefit from its use in the population studied. The low interobserver variability for LV mass reported by the investigators is rather illusory. Given that variability between 2 observers is always greater for patients compared with normal subjects,4,5 contemporary published research reports interobserver variability of 12.5% (range 1% to 26%) for normal subjects.6 Most of the patients had some kind of operative procedure (thus explaining the poor yield of good-quality images of only 45%), we are compelled to think that no difference in interobserver variability represents an underestimation, because observers would have fewer than half the total number of good-quality images to delineate and extrapolate, when necessary, the endocardial and epicardial borders. Despite the advent of matrix-array transducers and enhanced techniques for signal compression, low image resolution, low frame rates, and the need to extrapolate endocardial and epicardial borders are factors that could force even experienced observers to err with accurate semiautomatic border delineation. Anurag Singh, MD Koteswara R. Pothineni, MD, MPH Sadik R. Panwar, MBBS Birmingham, Alabama 3 March 2006
1. Van den Bosch AE, Robbers-Visser D, Krenning BJ, McGhie JS, Helbing WA, Meijboom FJ, Roos-Hesselink JW. Comparison of realtime three-dimensional echocardiography to magnetic resonance imaging for assessment of left ventricular mass. Am J Cardiol 2006;97: 113–117. 2. Mor-Avi V, Sugeng L, Weinert L, MacEneaney P, Caiani EG, Koch R, Salgo IS, Lang RM. Fast measurement of left ventricular mass with real-time three-dimensional echocardiography: comparison with magnetic resonance imaging. Circulation 2004;110:1814 – 1818. 3. Vogel M, Gutberlet M, Dittrich S, Hosten N, Lange PE. Comparison of transthoracic three dimensional echocardiography with magnetic resonance imaging in the assessment of right ventricular volume and mass. Heart 1997;78: 127–130. 4. Gottdiener JS, Livengood SV, Meyer PS, Chase GA. Should echocardiography be performed to assess effects of antihypertensive therapy? Test-retest reliability of echocardiography for measurement of left ventricular mass and function. J Am Coll Cardiol 1995;25:424 – 430. 5. Kitchener HF, Keep LL, Morin G, Chitin MD, Schiller NB. Echocardiography in serial evaluation of left ventricular systolic and diastolic function: importance of image acquisition,
Readers Comments
1181
quantitation, and physiologic variability in clinical and investigational applications. J Am Soc Echocardiogr 1991;4:203–214. 6. Caiani EG, Corsi C, Sugeng L, MacEneaney P, Weinert L, Mor-Avi V, Lang RM. Improved quantification of left ventricular mass based on endocardial and epicardial surface detection with real time three dimensional echocardiography. Heart 2006;92:213–219. doi:10.1016/j.amjcard.2006.03.072
Statin Use and Age at Death: Evidence of a Flawed Analysis We read with great interest the recently published report by Mehta et al1 on the effects of statin use on mortality. The report addresses a very important clinical issue. It must be expected that the results might have a major impact on future treatment recommendations, particularly for elderly subjects with elevated lipid levels. It is therefore crucial that the published results rest on sound scientific method and analysis driven by clarity and rigor. In our opinion, however, the study had severe methodologic problems in its design and analysis that call into question the validity and applicability of the results and conclusion. First, the study population was not clearly defined. Apparently, it consisted of all eligible veterans who at some point in time from January 1, 1996, to March 31, 2004, were associated with 10 health centers. If this is correct, it is unclear what the investigators presented in Table 3, which supposedly lists baseline characteristics for the study population. At what date, for example, was age computed? Second, the sampling scheme of the study seems not to have been addressed adequately in the analysis. To become registered as a user of statins, a patient must obviously first survive into the study period and then have a prescription recorded before loss to follow-up or death. Either the investigators did not consider this aspect in the analysis, or they did not describe it in sufficient detail to allow critical appraisal. To illustrate the potential effects of ignoring the sampling scheme, we conducted a simulation study, in which a given treatment has no effect on mortality. As in Mehta et al’s1 study, the mortality followed a Weibull distribution for a population with a constant birth process, and the incidence rate of (chronic) drug use increased linearly with age for ages ⬎35 years, whereas the incidence rate was zero for ages ⬍35 years. Users of the drug were assumed to present prescriptions every 2 months after the onset of treatment, and everyone resided within the capture area throughout their entire
Figure 1. Distribution of age at death stratified on observed treatment status within an 8-year period. Simulated data with no treatment effect, but incidence of treatment onset increases with age.
lives. Subjects were classified as treated if filled prescriptions were observed within the 8-year period. At the start of the observation period (“baseline”), the difference in mean age between treated and untreated subjects closely resembled the mean difference in age at death, coinciding with the results of Mehta et al.1 The 2 histograms of age at death in all who died in the observation period for the 2 groups are shown in Figure 1. Not only was the mean age at death greater in treated patients, the distribution was also narrower for the treated patients, as in the study by Mehta et al.1 It should be noted that if the incidence rate of treatment onset were to decrease with age, the mean lifetimes between the 2 groups would be reversed (i.e., those who were treated would apparently now live for a shorter period). In other words, histograms based on this type of data merely reflect the difference in age distribution between treated and untreated subjects, absent other factors, and the difference observed by Mehta et al1 can therefore not be taken as evidence of improved survival due to statin treatment. Although ignoring the sampling scheme invalidates the study in itself, several other problems deserve to be mentioned, the most severe being the use of forward selection algorithms. It is well known in statistical research that this method cannot but create biased estimates with inflated statistical significance, because by definition, it uses statistical significance for the inclusion of covariates.2,3 Furthermore, as a general rule, the timing of measurements was not described, hindering the valid interpretation of results. When was comedication measured? Before, during, or after treatment with st-
atins, or at any time, as with statins? What was meant by posttreatment change in untreated individuals? For these questions and several others, Mehta et al1 provided no useful information. It is unfortunate that Mehta et al1 missed the opportunity to use a unique body of data to provide a scientifically sound answer to a pressing clinical question. Instead of using proved epidemiologic methods, they seem to have relied on computer-intensive analysis of a massive data set without considering how the methods fit the research questions posed. From our point of view, some variant of a nested case-control study or a retrospective cohort study might well have contributed definitive and valuable insight into the real benefits of treatment with statins in the elderly. Although Mehta et al1 suggested that the sheer amount of data led to unbiased estimates and can compensate for analytical shortcuts, we respectfully submit that methodologic problems only become propounded when data are very numerous. We consider the study by Mehta et al1 excellent proof of this rule. Henrik Støvring, PhD, MSc Dorte Gilså Hansen, PhD, MD Lene Jarlbæk, MD, PhD Helle Wallach Kildemoes, MPH, MA Jørgen Lous, MD Morten Andersen, PhD, MD Odense, Denmark 10 January 2007
1. Mehta JL, Bursac Z, Hauer-Jensen M, Fort C, Fink LM. Comparison of mortality rates in statin users versus nonstatin users in a United States veteran population. Am J Cardiol 2006;98:923–928. 2. Miller AJ. Selection of subsets of regression variables. J R Stat Soc A 1984;147:389 – 425.