A Meta-Analysis of Low-Density Lipoprotein Cholesterol, Non-High-Density Lipoprotein Cholesterol, and Apolipoprotein B as Markers of Cardiovascular Risk
Whether apolipoprotein B (apoB) or non-high-density lipoprotein cholesterol (HDL-C) adds to the predictive power of low-density lipoprotein cholesterol (LDL-C) for cardiovascular risk remains controversial. This meta-analysis is based on all the published epidemiological studies that contained estim...
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| Published in | Circulation Cardiovascular quality and outcomes Vol. 4; no. 3; pp. 337 - 345 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hagerstown, MD
Lippincott Williams & Wilkins
01.05.2011
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Whether apolipoprotein B (apoB) or non-high-density lipoprotein cholesterol (HDL-C) adds to the predictive power of low-density lipoprotein cholesterol (LDL-C) for cardiovascular risk remains controversial.
This meta-analysis is based on all the published epidemiological studies that contained estimates of the relative risks of non-HDL-C and apoB of fatal or nonfatal ischemic cardiovascular events. Twelve independent reports, including 233 455 subjects and 22 950 events, were analyzed. All published risk estimates were converted to standardized relative risk ratios (RRRs) and analyzed by quantitative meta-analysis using a random-effects model. Whether analyzed individually or in head-to-head comparisons, apoB was the most potent marker of cardiovascular risk (RRR, 1.43; 95% CI, 1.35 to 1.51), LDL-C was the least (RRR, 1.25; 95% CI, 1.18 to 1.33), and non-HDL-C was intermediate (RRR, 1.34; 95% CI, 1.24 to 1.44). The overall comparisons of the within-study differences showed that apoB RRR was 5.7%>non-HDL-C (P<0.001) and 12.0%>LDL-C (P<0.0001) and that non-HDL-C RRR was 5.0%>LDL-C (P=0.017). Only HDL-C accounted for any substantial portion of the variance of the results among the studies. We calculated the number of clinical events prevented by a high-risk treatment regimen of all those >70th percentile of the US adult population using each of the 3 markers. Over a 10-year period, a non-HDL-C strategy would prevent 300 000 more events than an LDL-C strategy, whereas an apoB strategy would prevent 500 000 more events than a non-HDL-C strategy.
These results further validate the value of apoB in clinical care. |
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| AbstractList | Whether apolipoprotein B (apoB) or non-high-density lipoprotein cholesterol (HDL-C) adds to the predictive power of low-density lipoprotein cholesterol (LDL-C) for cardiovascular risk remains controversial.BACKGROUNDWhether apolipoprotein B (apoB) or non-high-density lipoprotein cholesterol (HDL-C) adds to the predictive power of low-density lipoprotein cholesterol (LDL-C) for cardiovascular risk remains controversial.This meta-analysis is based on all the published epidemiological studies that contained estimates of the relative risks of non-HDL-C and apoB of fatal or nonfatal ischemic cardiovascular events. Twelve independent reports, including 233 455 subjects and 22 950 events, were analyzed. All published risk estimates were converted to standardized relative risk ratios (RRRs) and analyzed by quantitative meta-analysis using a random-effects model. Whether analyzed individually or in head-to-head comparisons, apoB was the most potent marker of cardiovascular risk (RRR, 1.43; 95% CI, 1.35 to 1.51), LDL-C was the least (RRR, 1.25; 95% CI, 1.18 to 1.33), and non-HDL-C was intermediate (RRR, 1.34; 95% CI, 1.24 to 1.44). The overall comparisons of the within-study differences showed that apoB RRR was 5.7%>non-HDL-C (P<0.001) and 12.0%>LDL-C (P<0.0001) and that non-HDL-C RRR was 5.0%>LDL-C (P=0.017). Only HDL-C accounted for any substantial portion of the variance of the results among the studies. We calculated the number of clinical events prevented by a high-risk treatment regimen of all those >70th percentile of the US adult population using each of the 3 markers. Over a 10-year period, a non-HDL-C strategy would prevent 300 000 more events than an LDL-C strategy, whereas an apoB strategy would prevent 500 000 more events than a non-HDL-C strategy.METHODS AND RESULTSThis meta-analysis is based on all the published epidemiological studies that contained estimates of the relative risks of non-HDL-C and apoB of fatal or nonfatal ischemic cardiovascular events. Twelve independent reports, including 233 455 subjects and 22 950 events, were analyzed. All published risk estimates were converted to standardized relative risk ratios (RRRs) and analyzed by quantitative meta-analysis using a random-effects model. Whether analyzed individually or in head-to-head comparisons, apoB was the most potent marker of cardiovascular risk (RRR, 1.43; 95% CI, 1.35 to 1.51), LDL-C was the least (RRR, 1.25; 95% CI, 1.18 to 1.33), and non-HDL-C was intermediate (RRR, 1.34; 95% CI, 1.24 to 1.44). The overall comparisons of the within-study differences showed that apoB RRR was 5.7%>non-HDL-C (P<0.001) and 12.0%>LDL-C (P<0.0001) and that non-HDL-C RRR was 5.0%>LDL-C (P=0.017). Only HDL-C accounted for any substantial portion of the variance of the results among the studies. We calculated the number of clinical events prevented by a high-risk treatment regimen of all those >70th percentile of the US adult population using each of the 3 markers. Over a 10-year period, a non-HDL-C strategy would prevent 300 000 more events than an LDL-C strategy, whereas an apoB strategy would prevent 500 000 more events than a non-HDL-C strategy.These results further validate the value of apoB in clinical care.CONCLUSIONSThese results further validate the value of apoB in clinical care. Whether apolipoprotein B (apoB) or non-high-density lipoprotein cholesterol (HDL-C) adds to the predictive power of low-density lipoprotein cholesterol (LDL-C) for cardiovascular risk remains controversial. This meta-analysis is based on all the published epidemiological studies that contained estimates of the relative risks of non-HDL-C and apoB of fatal or nonfatal ischemic cardiovascular events. Twelve independent reports, including 233 455 subjects and 22 950 events, were analyzed. All published risk estimates were converted to standardized relative risk ratios (RRRs) and analyzed by quantitative meta-analysis using a random-effects model. Whether analyzed individually or in head-to-head comparisons, apoB was the most potent marker of cardiovascular risk (RRR, 1.43; 95% CI, 1.35 to 1.51), LDL-C was the least (RRR, 1.25; 95% CI, 1.18 to 1.33), and non-HDL-C was intermediate (RRR, 1.34; 95% CI, 1.24 to 1.44). The overall comparisons of the within-study differences showed that apoB RRR was 5.7%>non-HDL-C (P<0.001) and 12.0%>LDL-C (P<0.0001) and that non-HDL-C RRR was 5.0%>LDL-C (P=0.017). Only HDL-C accounted for any substantial portion of the variance of the results among the studies. We calculated the number of clinical events prevented by a high-risk treatment regimen of all those >70th percentile of the US adult population using each of the 3 markers. Over a 10-year period, a non-HDL-C strategy would prevent 300 000 more events than an LDL-C strategy, whereas an apoB strategy would prevent 500 000 more events than a non-HDL-C strategy. These results further validate the value of apoB in clinical care. |
| Author | Sniderman, Allan D. McQueen, Matthew J. Contois, John H. Monroe, Howard M. Furberg, Curt D. de Graaf, Jacqueline Williams, Ken |
| Author_xml | – sequence: 1 givenname: Allan D. surname: Sniderman fullname: Sniderman, Allan D. organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario – sequence: 2 givenname: Ken surname: Williams fullname: Williams, Ken organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario – sequence: 3 givenname: John H. surname: Contois fullname: Contois, John H. organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario – sequence: 4 givenname: Howard M. surname: Monroe fullname: Monroe, Howard M. organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario – sequence: 5 givenname: Matthew J. surname: McQueen fullname: McQueen, Matthew J. organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario – sequence: 6 givenname: Jacqueline surname: de Graaf fullname: de Graaf, Jacqueline organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario – sequence: 7 givenname: Curt D. surname: Furberg fullname: Furberg, Curt D. organization: From the Mike Rosenbloom Laboratory for Cardiovascular Research, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada (A.D.S.); KenAnCo Biostatistics and University of Texas Health Science Center at San Antonio, San Antonio, TX (K.W.); Maine Standards Company, Windham, ME (J.H.C.); KenAnCo Biostatistics and Department of Mathematics, Our Lady of the Lake University, San Antonio, TX (H.M.M.); Population Health Research Institute and McMaster University, Hamilton, Ontario |
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| SubjectTerms | Apolipoproteins B - blood Atherosclerosis (general aspects, experimental research) Biological and medical sciences Biomarkers - blood Blood and lymphatic vessels Cardiology. Vascular system Cardiovascular Diseases - blood Cardiovascular Diseases - diagnosis Cardiovascular Diseases - epidemiology Cholesterol, HDL - blood Cholesterol, LDL - blood Humans Medical sciences Predictive Value of Tests Reproducibility of Results Risk Factors |
| Title | A Meta-Analysis of Low-Density Lipoprotein Cholesterol, Non-High-Density Lipoprotein Cholesterol, and Apolipoprotein B as Markers of Cardiovascular Risk |
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