Do We Need a Disease-Specific Cardiovascular Risk Calculator for Patients With Rheumatoid Arthritis?

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1 ARTHRITIS & RHEUMATOLOGY Vol. 67, No. 8, August 2015, pp DOI /art VC 2015, American College of Rheumatology EDITORIAL Do We Need a Disease-Specific Cardiovascular Risk Calculator for Patients With Rheumatoid Arthritis? Deborah P. M. Symmons Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death in low-, middle-, and highincome countries. Risk factors for ASCVD within the general population include increasing age, male sex, smoking, hypertension, dyslipidemia, and diabetes. These are referred to as traditional risk factors (TRFs). More recently recognized (novel) risk factors include a family history of premature ASCVD events, obesity, physical inactivity, a raised high-sensitivity C-reactive protein (hscrp) level, poor renal function, and microalbuminuria. Many of the TRFs are modifiable and it is generally accepted that the intensity of preventive efforts should be matched to the estimated absolute risk of ASCVD in the individual patient (1 3). The preferred way of assigning an absolute risk to an individual is by using a cardiovascular risk calculator, such as the Reynolds Risk Score (RRS) and the Framingham Risk Score (FRS) (4,5), both widely used in the US, the System for Cardiac Operative Risk Evaluation (SCORE) calculator (6), which is widely used in Europe, or the QRisk2 calculator (7), which was developed and has been adopted in the UK (8). QRisk2 is the only one of these calculators to incorporate RA as an independent risk factor. The RRS, however, does incorporate measurement of the hscrp level. All of these calculators assign a group average risk to the individual patient, in the form of a percentage risk of having an event (a fatal or nonfatal ASCVDeventintheRRSandFRS,CVDdeathinthe SCORE, or fatal or nonfatal myocardial infarction [MI] or stroke in QRisk2) over the next 10 years. Deborah P. M. Symmons, MD, FFPH, FRCP: NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester University Hospitals NHS Foundation Trust and Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, UK. Address correspondence to Deborah P. M. Symmons, MD, FFPH, FRCP, Centre for Musculoskeletal Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK. deborah.symmons@manchester.ac.uk. Submitted for publication April 1, 2015; accepted in revised form May 12, A new set of pooled cohort equations has recently been developed in a large pooled US cohort of non- Hispanic African American and non-hispanic white subjects, ages years, who were free of ASCVD at baseline. These equations assign a 10-year risk of a first ASCVD event (nonfatal MI, coronary heart disease [CHD] related death, fatal or nonfatal stroke) (9). The most recent US guidelines have recommended lowering the risk threshold at which statin treatment should be considered, to a 10-year risk of an ASCVD event of $7.5% (10). Of course, no patient can have 7.5% of an ASCVD event; a patient either has an event or does not have an event. It has to be remembered that preventive measures can only be successful in those individuals who were destined to have an event. It has been known for many years that patients with established rheumatoid arthritis (RA) have an increased risk of ASCVD-related mortality and morbidity as compared with the general population. A metaanalysis of 24 mortality studies in RA published between 1970 and 2005 reported a weighted, combined all-cause standardized mortality ratio (met-smr) of 1.50 (95% confidence interval [95% CI] ), with similar increases in the SMRs for CHD (met-smr 1.59, 95% CI ) and stroke (met-smr 1.52, 95% CI ) (11). There is also evidence of increased frequencies of nonfatal CVD-related morbidities in patients with RA (12). Although studies of both fatal and nonfatal ASCVD have suggested that accelerated atherosclerosis begins around the time of, or before, the onset of symptoms of RA, in moderate-sized inception cohorts the excess risk may not be detectable, statistically, until at least 10 years after symptom onset (13). The reason for the increased risk of ASCVD in patients with RA has been intensively studied in recent years. Many of the TRFs are increased in prevalence and severity in RA. For example, smoking is a known risk factor for the development of RA, in particular rheumatoid factor (RF) and anti citrullinated protein antibody (ACPA) positive RA; therefore, not surprisingly, the 1990

2 EDITORIAL 1991 prevalence of smoking is higher in RA patients than in the general population (14). Smokers with RA have a worse prognosis in terms of RF titers, disability, radiologic joint damage, and treatment response, all of which may be associated with increased risk of ASCVD. The prevalence of hypertension is increased in RA patients compared with the general population, a finding that is underrecognized (15). Several drugs used in the treatment of RA (e.g., steroids, leflunomide, cyclosporine, nonsteroidal antiinflammatory drugs) may increase blood pressure. The prevalence of diabetes in patients with RA is ;75% higher than in the general population (14). The prevalence of more recently recognized CVD risk factors in the general population, such as obesity, the metabolic syndrome, and physical inactivity, are also increased in patients with RA. Inflammation, such as is seen in active RA, is associated with suppression of total cholesterol and low-density lipoprotein (LDL) cholesterol levels and a proportionately greater suppression of HDL cholesterol levels, resulting in a disadvantageous atherogenic index (total cholesterol: HDL cholesterol ratio). Thus, hyperlipidemia (high total cholesterol or LDL cholesterol levels) appears to be less commoninrapatientscomparedwithnon-rasubjects, but dyslipidemia (alterations of individual lipid components and their ratios, as defined by specific criteria) may affect up to one-half of all RA patients under hospital care (16). The total cholesterol:hdl cholesterol ratio has been shown to be a better CV risk predictor than individual lipid components in patients with RA, since lipid ratios are less likely to be influenced by disease activity or diseasemodifying treatment. Successful suppression of disease activity in RA has beneficial effects on lipid levels and the total cholesterol:hdl cholesterol ratio. Thus, the minimum steps in primary prevention of ASCVD in patients with RA should be the assessment of TRFs and the application of a population-derived CV risk calculator ideally using a population comprising subjects most closely resembling the background population of the RA patients. For the reasons outlined above, the European League Against Rheumatism guidelines for CV risk management in patients with RA recommend using a risk calculator that incorporates the levels of total cholesterol and HDL cholesterol (17). It can also be argued that lipid levels are best assessed at a time of stable disease activity. A number of studies have examined the performance of general population based CV risk calculators in patients with RA. Crowson et al, in the Mayo clinic population, found that the FRS underestimated CV risk, particularly in the highest and lowest deciles of predicted risk (18). Arts and colleagues examined the performance of 4 risk calculators (the FRS, SCORE, QRisk2, and RRS) in an inception cohort of 1,050 RA patients from Nijmegen, The Netherlands who were followed up for a mean of 9.5 years (149 ASCVD events). Although the numbers of observed events and numbers of predicted events ascertained using the FRS were similar, the authors concluded that the FRS, RRS, and SCORE algorithms tended to underestimate CV risk, whereas the QRisk2 algorithm (which incorporates a multiplication factor of 1.4 for risk in all patients with RA) tended to overestimate risk (19). It is clear that TRFs alone do not account for the increased risk of ASCVD in RA. Disease-specific factors such as systemic inflammation and autoimmunity also play a role. Results from a number of studies have suggested that the excess ASCVD-related mortality in RA may be confined to, or at least substantially higher, in patients who are RF positive and/or ACPA positive (20). Importantly several studies have demonstrated an association between markers of cumulative RA disease activity (21,22) and the subsequent development of ASCVD. Other markers of disease severity, such as physical disability, destructive changes on joint radiographs, rheumatoid nodules, vasculitis, rheumatoid lung disease, and corticosteroid use, are all statistically significantly associated with increased risk of CVD events and/or death, even after adjustment for TRFs. However, disease duration alone does not seem to be associated with an increased risk of CVD, and patients whose disease is in sustained remission have the same CVD risk as that in non-ra subjects, after controlling for TRFs (21,22). These observations raise 2 questions. The first question is, if disease activity were optimally controlled, would CV risk in RA revert to that in the general population, i.e., would any excess risk of ASCVD in RA then be entirely explained by TRFs? The observation that successful treatment of RA patients with tumor necrosis factor inhibitors and methotrexate is associated with a significant decrease in the number of ASCVD events (23) supports this hypothesis. ASCVD-related age- and sex-standardized mortality rates are falling with time in patients with RA (20,24,25), with particularly pronounced declines since the year 2000, which is around the time that biologic agents were introduced and the treat-to-target strategy became widely adopted (20,25). SMRs have, however, remained elevated and stable (i.e., the mortality rates in RA are falling in parallel with those in the general population). In the only study confined to RA patients in whom disease onset occurred since the year 2000, investigators found an SMR of 1.19 (95% CI ) in the first 7 years of disease, a finding that is encouraging (20). However, given that it can be up to 10

3 1992 SYMMONS years from symptom onset before the CVD-related mortality experience in RA patients and the general population begins to diverge, it is probably too early to tell whether improved disease management will reduce the disease-specific excess risk of ASCVD. The second question is whether it is possible to improve the assignment of individual CV risk in RA patients by adding disease-specific factors to TRFs in a disease-specific risk prediction model. There is no evidence that TRFs should be managed any differently in patients with RA than in the general population. Statins are at least as effective in reducing lipid levels in RA patients as in non-ra controls and have no greater risk of side effects (26). The goal of disease management in all patients with RA is to minimize disease activity and there is, as yet, no evidence that even more aggressive therapy specifically to target CV risk, as opposed to joint disease, would be of benefit. Therefore, the main purpose of an RA-specific CV risk calculator would be to improve the accuracy of prediction around the thresholds that guide the intensity of management of TRFs. There are a number of well-recognized steps in incorporating new risk factors into existing models of CV risk prediction (27). In addition to demonstrating that the new risk factor is a predictor of ASCVD events, independent of TRFs, it is also important to show that the modified risk engine improves the agreement between the observed and the predicted number of events in each decile of risk. Moreover, it is important to show that the improvements are seen in those categories in which it will make a difference to the quality of risk management. To develop such a modified prediction tool requires access to a large representative cohort of patients followed up prospectively and, most importantly, with an adequate number of ASCVD events. If the new tool is to be advocated for general use, then it should be validated in cohorts other than the cohort in which it was developed. We are beginning to see attempts to produce adapted CV risk algorithms for use in patients with RA (28), including the algorithm developed by Solomon and colleagues using data derived from the CORRONA registry, as reported in this issue of Arthritis & Rheumatology (29). Arts et al, in a cohort comprising 1,016 patients with incident RA who experienced 103 ASCVD events, were unable to improve on the performance of the SCORE calculator, either by reweighting the TRFs or introducing RA-specific predictors (28). Solomon et al studied 23,605 patients with prevalent RA who had undergone at least 2 physician visits and who were free of CVD at the first visit (29). During a mean followup of 2.9 years, 437 patients had an ASCVD event (incident MI or stroke or CV-related death). Unfortunately, CORRONA does not collect the variables needed for the FRS or pooled cohorts equation (in particular, actual cholesterol or blood pressure measurements). This means that we do not know whether the TRF calculator developed performs as well as general population algorithms in this cohort. Solomon et al started by developing a risk score using those TRFs that were available (age, sex, diabetes, and presence or absence of hyperlipidemia, hypertension, and tobacco use). Baseline RA-specific measures found to improve their TRF model were disease activity measured by the Clinical Disease Activity Index (30) (dichotomized at a score of 10), modified Health Assessment Questionnaire disability index (dichotomized at a score of 0.5) (31), daily prednisone use (any versus none), and disease duration (dichotomized at a duration of 10 years). They found that when using the 2013 CV risk prediction categories of,7.5% and $7.5% for 10-year risk of an ASCVD event (10), 10.8% of patients (n 5 1,573) who were classified in the $7.5% 10-year risk category using their TRF models were classified in the,7.5% risk category with the expanded model, and 8.7% of patients (n 5 783) classified as being at,7.5% risk of a CV event in their TRF model were classified as being at $7.5% risk with their expanded model (see Table 4 in ref. 29). Thus, the addition of disease-specific factors in their CV risk prediction model would result in fewer patients being considered for statin therapy. The next vital steps for the development of this model would be to test it in independent cohorts preferably ones that have available lipid and blood pressure measurements (in order to incorporate comparison with a general population algorithm) and a longer period of followup (to test the assumption that the risk of ASCVD events is constant with time). Some physicians advocate screening for subclinical atherosclerosis in all patients with RA, rather than developing risk prediction algorithms based on TRFs and/or RA disease specific CVD risk factors. Several screening methods are available, including measuring endothelial dysfunction, arterial stiffness, carotid intima-media thickness, carotid plaque, and coronary artery calcification. All of these have been shown to be, on average, worse in RA patients than in the general population. However, most of these methods are not advocated for use in the general population, and there is no agreement about what threshold levels would be used to initiate treatment, or whether treatment would be effective. Carotid ultrasound is the closest to being considered for routine practice (32). Bilateral carotid plaques are associated with future acute coronary syndrome (ACS) in patients with RA, with a rate of ACS of 1.1 (95% CI ) per 100 person-years in RA patients with no carotid plaques and 4.3 (95% CI ) in those with bilateral plaques (33). However,

4 EDITORIAL 1993 plaques were found predominantly in patients with moderate-to-high CV risk according to the modified SCORE, and it is debatable whether it would be costeffective to screen all RA patients without first performing a conventional risk assessment. In summary, it is unclear whether there is a need for disease-specific ASCVD risk calculators for patients with RA. We already advocate minimizing disease activity in all RA patients. This in itself should reduce CV risk. The challenge is to manage TRFs in RA patients optimally. We may serve our patients better by assessing these TRFs in the context of proven general population risk calculators possibly with a multiplication factor, such as in the QRisk2 using readily available measures, rather than requiring additional tests (such as measures of disease activity and autoantibody tests) before the risk of ASCVD can be calculated and addressed. 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