Editorial
Arthritis & Rheumatism DOI 10.1002/art.38925
Inflammation, DMARDs, lipids and cardiovascular risk in rheumatoid arthritis Katherine P. Liao, MD, MPH1 and Daniel H. Solomon, MD, MPH1,2 1
Division of Rheumatology, Immunology and Allergy Brigham and Women’s Hospital 2
Division of Pharmacoepidemiology Brigham and Women’s Hospital
Correspondence: Katherine P. Liao, MD, MPH Division of Rheumatology, Immunology and Allergy Brigham and Women’s Hospital 75 Francis St, PBB-B3 Boston, MA 02115 Ph: 617-525-8819 Fax: 617-732-5766 Email: [email protected]
FUNDING KPL is funded by the K08 AR060257 and the Harold and Duval Bowen Fund. DHS is supported by NIH (K24 AR055989). DISCLOSURES/POTENTIAL CONFLICTS Dr. Liao has no disclosures. Dr. Solomon receives research funding through Brigham and Women’s Hospital from Pfizer, Lilly, and Amgen. He is also has unpaid roles on trials funded by Pfizer and Bristol Myers Squibb. He receives royalties for unrelated work from UpToDate.
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/art.38925 © 2014 American College of Rheumatology Received: Oct 01, 2014; Accepted: Oct 14, 2014
Arthritis & Rheumatology
Efficient primary prevention requires accurate identification of at-risk groups. Management strategies can then be tested in these groups to determine their potential benefit. In the case of cardiovascular disease (CVD) and rheumatoid arthritis (RA), accurate identification of at-risk groups remains a challenging task. The risk of CVD is approximately 2-fold higher in RA compared to age- and gendermatched individuals from the general population(1, 2), and many of the factors contributing to risk have been identified. These include traditional risk factors such as hypertension, hyperlipidemia, diabetes as well as the effects of chronic systemic inflammation, a hallmark of RA(3, 4). Application to RA of commonly used CV risk calculators such as the Framingham Risk Score(5) grossly underestimates risk by 150%(6, 7). The Reynolds’ Risk Score(8) which incorporates a marker of inflammation (i.e., the Creactive protein) along with traditional risk factors was also found to underestimate CV risk in RA. Thus, a fundamental challenge to improving CV risk management in RA is accurate identification of patients who by traditional risk factors do not appear to be at elevated risk for CV events. How should we best incorporate the inflammation of RA to predict CV risk?
Inflammation is considered a major driver of the excess CV risk in RA compared to the general population(9). However, validated methods accounting for inflammation in calculations of CV risk in RA have not been developed. This is especially difficult because inflammation in RA is tightly linked with treatment, which also likely affects CV risk. Moreover, inflammation and treatment have been associated with changes in lipid levels. In the Treatment of Early Aggressive Rheumatoid Arthritis (TEAR) trial, up to 30% elevations in total cholesterol (TC) and low density lipoprotein (LDL) were observed after treatment with the tumor necrosis factor inhibitor (TNFi) etanercept in combination with methotrexate(10). This seems counter-intuitive to the results from large observational studies showing
John Wiley & Sons
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Arthritis & Rheumatology
that TNFi use was associated with a significantly reduced risk of CVD compared to methotrexate and other non-biologic disease modifying anti-rheumatic drugs (DMARDs)(11, 12).
The elevations in TC and LDL are arguably more concerning with tocilizumab where increases were observed across all clinical trials(13). The interleukin 6 receptor (IL-6R) pathway, the target of tocilizumab, was implicated as part of the causal pathway for CVD in a genetic analysis of approximately 51,000 individuals with heart disease and 136,000 controls (14, 15). The studies suggested that blocking the IL-6R pathway, the mechanism of action for tocilizumab, may reduce CV risk. With these seemingly contradictory data for tocilizumab, a major unanswered question is whether elevations in TC and LDL with tocilizumab (or other DMARDs) are clinically important and related to higher CV risk in RA.
In this context, we turn our attention to findings from Rao and colleagues presented in this issue of Arthritis & Rheumatology. In a post-hoc analysis of 3,986 subjects from five tocilizumab randomized controlled trials and extension studies, the authors tested for associations between CV events and changes in a range of laboratory markers and RA disease activity measurements. The subjects were followed for a mean of 3.7 years and notably, there were only 50 independently adjudicated CV events. The investigators found that after 24-weeks of tocilizumab treatment, there was a 16% increase in TC, 19% increase in LDL and 7% increase in high density lipoprotein (HDL). After adjusting for age and baseline lipid values, TC and LDL levels at week 24 were not associated with an increased CV event risk, but the statistical power to determine this association was limited. There was a consistent relationship between RA disease activity (DAS28) and CV events. Both at baseline and after 24 weeks on tocilizumab therapy, higher levels of DAS28 were associated with increased risk of CV events. Neither levels of IL-6, IL-6R at baseline, nor IL-6R at 24 weeks were associated with CV events.
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Arthritis & Rheumatology
While the lack of signal for CV events was reassuring, the results from this study cannot provide definitive answers regarding the safety of tocilizumab. An ongoing phase 4 randomized open label study of tocilizumab should add important safety information by examining the rates of CV events in subjects with moderate to severe RA on tocilizumab compared to etanercept (ClinicalTrials.gov identifier: NCT01331837). Additional observational studies comparing CV risk in tocilizumab versus other biologic DMARD users should also provide data to address this issue.
Other studies may shed light on the relative significance of disease activity and lipids with risk of CVD in RA. A TransAtlantic Cardiovascular risk Calculator for RA (ATTAC-RA), an international collaborative effort is underway to determine the optimal set of clinical factors predictive of CV risk using pooled data from large prospective RA cohorts with CV outcomes(16). It is possible that as the current study suggests, disease activity will be an important risk factor, while TC and LDL may be suboptimal measures to guide CV risk estimation and preventative interventions since levels appear to fluctuate with therapy in an inverse manner (13). Less routine measurements examined in other studies such as advanced lipoprotein tests may also improve the accuracy of CV risk assessment in RA. In contrast to TC and LDL, measurements such as pro-inflammatory HDL levels(17) and HDL cholesterol efflux capacity(18) show promise as markers that correlate with improvements in CV risk with reduction in inflammation. We believe that closer investigation into the underlying mechanisms by which inflammation elevates CV risk in RA and translation of these findings for use in clinical practice is a rapidly evolving important area which may have implications beyond rheumatology.
John Wiley & Sons
Page 4 of 6
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Arthritis & Rheumatology
SELECTED REFERENCES 1. Avina-Zubieta JA, Choi HK, Sadatsafavi M, Etminan M, Esdaile JM, Lacaille D. Risk of cardiovascular mortality in patients with rheumatoid arthritis: a meta-analysis of observational studies. Arthritis Rheum 2008;59(12):1690-7. 2. Solomon DH, Karlson EW, Rimm EB, Cannuscio CC, Mandl LA, Manson JE, et al. Cardiovascular morbidity and mortality in women diagnosed with rheumatoid arthritis. Circulation 2003;107(9):1303-7. 3. del Rincon I, Freeman GL, Haas RW, O'Leary DH, Escalante A. Relative contribution of cardiovascular risk factors and rheumatoid arthritis clinical manifestations to atherosclerosis. Arthritis Rheum 2005;52(11):3413-23. 4. Solomon DH, Kremer J, Curtis JR, Hochberg MC, Reed G, Tsao P, et al. Explaining the cardiovascular risk associated with rheumatoid arthritis: traditional risk factors versus markers of rheumatoid arthritis severity. Ann Rheum Dis 2010;69(11):1920-5. 5. D'Agostino RB, Sr., Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001;286(2):1807. 6. Chung CP, Oeser A, Avalos I, Gebretsadik T, Shintani A, Raggi P, et al. Utility of the Framingham risk score to predict the presence of coronary atherosclerosis in patients with rheumatoid arthritis. Arthritis Res Ther 2006;8(6):R186. 7. Crowson CS, Matteson EL, Roger VL, Therneau TM, Gabriel SE. Usefulness of risk scores to estimate the risk of cardiovascular disease in patients with rheumatoid arthritis. Am J Cardiol 2012;110(3):420-4. 8. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA 2007;297(6):6119. 9. Libby P. Role of inflammation in atherosclerosis associated with rheumatoid arthritis. Am J Med 2008;121(10 Suppl 1):S21-31. 10. Navarro-Millan I, Charles-Schoeman C, Yang S, Bathon JM, Bridges SL, Jr., Chen L, et al. Changes in lipoproteins associated with methotrexate or combination therapy in early rheumatoid arthritis: results from the treatment of early rheumatoid arthritis trial. Arthritis Rheum 2013;65(6):1430-8. 11. Bili A, Tang X, Pranesh S, Bozaite R, Morris SJ, Antohe JL, et al. Tumor necrosis factor alpha inhibitor use and decreased risk for incident coronary events in rheumatoid arthritis. Arthritis Care Res (Hoboken) 2014;66(3):355-63. 12. Dixon WG, Watson KD, Lunt M, Hyrich KL, Silman AJ, Symmons DP. Reduction in the incidence of myocardial infarction in patients with rheumatoid arthritis who respond to anti-tumor necrosis factor alpha therapy: results from the British Society for Rheumatology Biologics Register. Arthritis Rheum 2007;56(9):2905-12. 13. Robertson J, Peters MJ, McInnes IB, Sattar N. Changes in lipid levels with inflammation and therapy in RA: a maturing paradigm. Nat Rev Rheumatol 2013;9(9):513-23. 14. Hingorani AD, Casas JP. The interleukin-6 receptor as a target for prevention of coronary heart disease: a mendelian randomisation analysis. Lancet 2012;379(9822):1214-24. 15. Sarwar N, Butterworth AS, Freitag DF, Gregson J, Willeit P, Gorman DN, et al. Interleukin-6 receptor pathways in coronary heart disease: a collaborative meta-analysis of 82 studies. Lancet 2012;379(9822):1205-13. 16. Arts E. A Transatlantic Cardiovascular Risk Calculator for Rheumatoid Arthritis (ATACC-RA). Ann Rheum Dis 2014;73(S2).
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Arthritis & Rheumatology
17. McMahon M, Grossman J, FitzGerald J, Dahlin-Lee E, Wallace DJ, Thong BY, et al. Proinflammatory high-density lipoprotein as a biomarker for atherosclerosis in patients with systemic lupus erythematosus and rheumatoid arthritis. Arthritis Rheum 2006;54(8):2541-9. 18. Charles-Schoeman C, Lee YY, Grijalva V, Amjadi S, FitzGerald J, Ranganath VK, et al. Cholesterol efflux by high density lipoproteins is impaired in patients with active rheumatoid arthritis. Ann Rheum Dis 2012;71(7):1157-62.
John Wiley & Sons
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Arthritis & Rheumatism DOI 10.1002/art.38925
Inflammation, DMARDs, lipids and cardiovascular risk in rheumatoid arthritis Katherine P. Liao, MD, MPH1 and Daniel H. Solomon, MD, MPH1,2 1
Division of Rheumatology, Immunology and Allergy Brigham and Women’s Hospital 2
Division of Pharmacoepidemiology Brigham and Women’s Hospital
Correspondence: Katherine P. Liao, MD, MPH Division of Rheumatology, Immunology and Allergy Brigham and Women’s Hospital 75 Francis St, PBB-B3 Boston, MA 02115 Ph: 617-525-8819 Fax: 617-732-5766 Email: [email protected]
FUNDING KPL is funded by the K08 AR060257 and the Harold and Duval Bowen Fund. DHS is supported by NIH (K24 AR055989). DISCLOSURES/POTENTIAL CONFLICTS Dr. Liao has no disclosures. Dr. Solomon receives research funding through Brigham and Women’s Hospital from Pfizer, Lilly, and Amgen. He is also has unpaid roles on trials funded by Pfizer and Bristol Myers Squibb. He receives royalties for unrelated work from UpToDate.
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/art.38925 © 2014 American College of Rheumatology Received: Oct 01, 2014; Accepted: Oct 14, 2014
Arthritis & Rheumatology
Efficient primary prevention requires accurate identification of at-risk groups. Management strategies can then be tested in these groups to determine their potential benefit. In the case of cardiovascular disease (CVD) and rheumatoid arthritis (RA), accurate identification of at-risk groups remains a challenging task. The risk of CVD is approximately 2-fold higher in RA compared to age- and gendermatched individuals from the general population(1, 2), and many of the factors contributing to risk have been identified. These include traditional risk factors such as hypertension, hyperlipidemia, diabetes as well as the effects of chronic systemic inflammation, a hallmark of RA(3, 4). Application to RA of commonly used CV risk calculators such as the Framingham Risk Score(5) grossly underestimates risk by 150%(6, 7). The Reynolds’ Risk Score(8) which incorporates a marker of inflammation (i.e., the Creactive protein) along with traditional risk factors was also found to underestimate CV risk in RA. Thus, a fundamental challenge to improving CV risk management in RA is accurate identification of patients who by traditional risk factors do not appear to be at elevated risk for CV events. How should we best incorporate the inflammation of RA to predict CV risk?
Inflammation is considered a major driver of the excess CV risk in RA compared to the general population(9). However, validated methods accounting for inflammation in calculations of CV risk in RA have not been developed. This is especially difficult because inflammation in RA is tightly linked with treatment, which also likely affects CV risk. Moreover, inflammation and treatment have been associated with changes in lipid levels. In the Treatment of Early Aggressive Rheumatoid Arthritis (TEAR) trial, up to 30% elevations in total cholesterol (TC) and low density lipoprotein (LDL) were observed after treatment with the tumor necrosis factor inhibitor (TNFi) etanercept in combination with methotrexate(10). This seems counter-intuitive to the results from large observational studies showing
John Wiley & Sons
Page 2 of 6
Page 3 of 6
Arthritis & Rheumatology
that TNFi use was associated with a significantly reduced risk of CVD compared to methotrexate and other non-biologic disease modifying anti-rheumatic drugs (DMARDs)(11, 12).
The elevations in TC and LDL are arguably more concerning with tocilizumab where increases were observed across all clinical trials(13). The interleukin 6 receptor (IL-6R) pathway, the target of tocilizumab, was implicated as part of the causal pathway for CVD in a genetic analysis of approximately 51,000 individuals with heart disease and 136,000 controls (14, 15). The studies suggested that blocking the IL-6R pathway, the mechanism of action for tocilizumab, may reduce CV risk. With these seemingly contradictory data for tocilizumab, a major unanswered question is whether elevations in TC and LDL with tocilizumab (or other DMARDs) are clinically important and related to higher CV risk in RA.
In this context, we turn our attention to findings from Rao and colleagues presented in this issue of Arthritis & Rheumatology. In a post-hoc analysis of 3,986 subjects from five tocilizumab randomized controlled trials and extension studies, the authors tested for associations between CV events and changes in a range of laboratory markers and RA disease activity measurements. The subjects were followed for a mean of 3.7 years and notably, there were only 50 independently adjudicated CV events. The investigators found that after 24-weeks of tocilizumab treatment, there was a 16% increase in TC, 19% increase in LDL and 7% increase in high density lipoprotein (HDL). After adjusting for age and baseline lipid values, TC and LDL levels at week 24 were not associated with an increased CV event risk, but the statistical power to determine this association was limited. There was a consistent relationship between RA disease activity (DAS28) and CV events. Both at baseline and after 24 weeks on tocilizumab therapy, higher levels of DAS28 were associated with increased risk of CV events. Neither levels of IL-6, IL-6R at baseline, nor IL-6R at 24 weeks were associated with CV events.
John Wiley & Sons
Arthritis & Rheumatology
While the lack of signal for CV events was reassuring, the results from this study cannot provide definitive answers regarding the safety of tocilizumab. An ongoing phase 4 randomized open label study of tocilizumab should add important safety information by examining the rates of CV events in subjects with moderate to severe RA on tocilizumab compared to etanercept (ClinicalTrials.gov identifier: NCT01331837). Additional observational studies comparing CV risk in tocilizumab versus other biologic DMARD users should also provide data to address this issue.
Other studies may shed light on the relative significance of disease activity and lipids with risk of CVD in RA. A TransAtlantic Cardiovascular risk Calculator for RA (ATTAC-RA), an international collaborative effort is underway to determine the optimal set of clinical factors predictive of CV risk using pooled data from large prospective RA cohorts with CV outcomes(16). It is possible that as the current study suggests, disease activity will be an important risk factor, while TC and LDL may be suboptimal measures to guide CV risk estimation and preventative interventions since levels appear to fluctuate with therapy in an inverse manner (13). Less routine measurements examined in other studies such as advanced lipoprotein tests may also improve the accuracy of CV risk assessment in RA. In contrast to TC and LDL, measurements such as pro-inflammatory HDL levels(17) and HDL cholesterol efflux capacity(18) show promise as markers that correlate with improvements in CV risk with reduction in inflammation. We believe that closer investigation into the underlying mechanisms by which inflammation elevates CV risk in RA and translation of these findings for use in clinical practice is a rapidly evolving important area which may have implications beyond rheumatology.
John Wiley & Sons
Page 4 of 6
Page 5 of 6
Arthritis & Rheumatology
SELECTED REFERENCES 1. Avina-Zubieta JA, Choi HK, Sadatsafavi M, Etminan M, Esdaile JM, Lacaille D. Risk of cardiovascular mortality in patients with rheumatoid arthritis: a meta-analysis of observational studies. Arthritis Rheum 2008;59(12):1690-7. 2. Solomon DH, Karlson EW, Rimm EB, Cannuscio CC, Mandl LA, Manson JE, et al. Cardiovascular morbidity and mortality in women diagnosed with rheumatoid arthritis. Circulation 2003;107(9):1303-7. 3. del Rincon I, Freeman GL, Haas RW, O'Leary DH, Escalante A. Relative contribution of cardiovascular risk factors and rheumatoid arthritis clinical manifestations to atherosclerosis. Arthritis Rheum 2005;52(11):3413-23. 4. Solomon DH, Kremer J, Curtis JR, Hochberg MC, Reed G, Tsao P, et al. Explaining the cardiovascular risk associated with rheumatoid arthritis: traditional risk factors versus markers of rheumatoid arthritis severity. Ann Rheum Dis 2010;69(11):1920-5. 5. D'Agostino RB, Sr., Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001;286(2):1807. 6. Chung CP, Oeser A, Avalos I, Gebretsadik T, Shintani A, Raggi P, et al. Utility of the Framingham risk score to predict the presence of coronary atherosclerosis in patients with rheumatoid arthritis. Arthritis Res Ther 2006;8(6):R186. 7. Crowson CS, Matteson EL, Roger VL, Therneau TM, Gabriel SE. Usefulness of risk scores to estimate the risk of cardiovascular disease in patients with rheumatoid arthritis. Am J Cardiol 2012;110(3):420-4. 8. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA 2007;297(6):6119. 9. Libby P. Role of inflammation in atherosclerosis associated with rheumatoid arthritis. Am J Med 2008;121(10 Suppl 1):S21-31. 10. Navarro-Millan I, Charles-Schoeman C, Yang S, Bathon JM, Bridges SL, Jr., Chen L, et al. Changes in lipoproteins associated with methotrexate or combination therapy in early rheumatoid arthritis: results from the treatment of early rheumatoid arthritis trial. Arthritis Rheum 2013;65(6):1430-8. 11. Bili A, Tang X, Pranesh S, Bozaite R, Morris SJ, Antohe JL, et al. Tumor necrosis factor alpha inhibitor use and decreased risk for incident coronary events in rheumatoid arthritis. Arthritis Care Res (Hoboken) 2014;66(3):355-63. 12. Dixon WG, Watson KD, Lunt M, Hyrich KL, Silman AJ, Symmons DP. Reduction in the incidence of myocardial infarction in patients with rheumatoid arthritis who respond to anti-tumor necrosis factor alpha therapy: results from the British Society for Rheumatology Biologics Register. Arthritis Rheum 2007;56(9):2905-12. 13. Robertson J, Peters MJ, McInnes IB, Sattar N. Changes in lipid levels with inflammation and therapy in RA: a maturing paradigm. Nat Rev Rheumatol 2013;9(9):513-23. 14. Hingorani AD, Casas JP. The interleukin-6 receptor as a target for prevention of coronary heart disease: a mendelian randomisation analysis. Lancet 2012;379(9822):1214-24. 15. Sarwar N, Butterworth AS, Freitag DF, Gregson J, Willeit P, Gorman DN, et al. Interleukin-6 receptor pathways in coronary heart disease: a collaborative meta-analysis of 82 studies. Lancet 2012;379(9822):1205-13. 16. Arts E. A Transatlantic Cardiovascular Risk Calculator for Rheumatoid Arthritis (ATACC-RA). Ann Rheum Dis 2014;73(S2).
John Wiley & Sons
Arthritis & Rheumatology
17. McMahon M, Grossman J, FitzGerald J, Dahlin-Lee E, Wallace DJ, Thong BY, et al. Proinflammatory high-density lipoprotein as a biomarker for atherosclerosis in patients with systemic lupus erythematosus and rheumatoid arthritis. Arthritis Rheum 2006;54(8):2541-9. 18. Charles-Schoeman C, Lee YY, Grijalva V, Amjadi S, FitzGerald J, Ranganath VK, et al. Cholesterol efflux by high density lipoproteins is impaired in patients with active rheumatoid arthritis. Ann Rheum Dis 2012;71(7):1157-62.
John Wiley & Sons
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