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Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis
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Original article
Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis Masako Kochi (MD)a,b, Kentaro Kohagura (MD, PhD)c,*, Yoshiki Shiohira (MD)d, Kunitoshi Iseki (MD, PhD)d,e, Yusuke Ohya (MD, PhD, FJCC)a a
Department of Cardiovascular Medicine, Nephrology and Neurology, University of the Ryukyus School of Medicine, Nishihara, Japan Yuuaikai Nanbu Hospital, Itoman, Okinawa, Japan Dialysis Unit, University of the Ryukyus Hospital, Nishihara, Japan d Yuuaikai Tomishiro Central Hospital, Tomigusuku, Okinawa, Japan e Okinawa Heart and Renal Association, Okinawa, Japan b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 5 June 2017 Received in revised form 31 July 2017 Accepted 15 August 2017 Available online xxx
Background: Rheumatoid arthritis (RA), a prototypic systemic autoimmune inflammatory condition, confers an increased risk of cardiovascular disease (CVD). Recently, chronic kidney disease (CKD) was suggested to increase the risk of CVD in RA patients, and inflammation was identified as a critical, nontraditional CKD-associated risk factor for CVD. This study aimed to examine the combined effects of CKD and CVD in RA patients. Methods: In this retrospective evaluation of 428 RA patients, the outcome of interest was the incidence of CVD. CKD was defined as an estimated glomerular filtration rate of <60 mL/min/1.73 m2 and/or positive dipstick tests for proteinuria of 3 months duration. C-reactive protein (CRP) was used as an inflammation marker, and a high CRP level was defined as a mean CRP value of 0.57 mg/dL during the first 6 months of follow-up. Patients were categorized as follows: non-CKD with low CRP, non-CKD with high CRP, CKD with low CRP, and CKD with high CRP. Results: During a median follow-up of 89 months, 67 patients (16%) had CKD, and 38 (9%) developed CVD. Using patients with non-CKD and low CRP as a reference group, the adjusted hazard ratios (HR, 95% confidence interval) for CVD were 1.88 (0.25–9.44) for patients with CKD/low CRP and 9.71 (3.27–31.97) for those with CKD/high CRP. Conclusions: The coexistence of CKD and inflammation was associated with a higher risk of CVD than either condition alone in RA patients. Inflammation might increase the risk of CVD especially in patients with CKD. © 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.
Keywords: C-reactive protein Cardiovascular disease Chronic kidney disease Inflammation Rheumatoid arthritis
Introduction Patients with rheumatoid arthritis (RA), a prototypic autoimmune disease characterized by chronic systemic inflammation, face an increased risk of cardiovascular disease (CVD) [1– 5]. Currently, the reported incidence of CVD is >50% higher among RA patients than in the general population [6,7]. Although both traditional cardiovascular (CV) risk factors and inflammation contribute to this increased CVD risk [4], the mechanism underlying this process remains unclear.
* Corresponding author at: Dialysis Unit, University Hospital of the Ryukyus, 207 Uehara, Nishihara, Okinawa 903-0215, Japan. E-mail address: [email protected] (K. Kohagura).
Chronic kidney disease (CKD), known as an independent risk factor for CVD in the general population [8–12], is a frequent comorbidity among RA patients [13,14] and was recently suggested to increase the risk of CVD in this population [15,16]. Inflammation, an atherosclerotic factor, is a manifestation of CVD [17] and is considered an untraditional CV risk factor in CKD patients [17–21]. Notably, inflammation has been described as a potential primary mediator or “missing link” to explain the tremendous burden of CVD experienced by CKD patients [18]. Despite the associations of chronic inflammation with CV mortality and morbidity in RA patients [2,22–24], it remains unclear whether inflammation also affects the mechanisms underlying the high risk of CVD in CKD among this population. The present study therefore aimed to examine the combined effects of CKD and inflammation, indicated by the
http://dx.doi.org/10.1016/j.jjcc.2017.08.008 0914-5087/© 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Kochi M, et al. Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis. J Cardiol (2017), http://dx.doi.org/10.1016/j.jjcc.2017.08.008
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marker C-reactive protein (CRP), on CVD development in RA patients. Materials and methods Participants This retrospective study of digital medical records from Tomishiro Central Hospital (Okinawa, Japan) was conducted after obtaining permission from the Ethical Committee of Tomishiro Central Hospital. Prior to accession for this study, the data from medical records were anonymized. As a baseline, we screened 487 adult patients (older than 18 years) who visited the hospital in April 2006 and met the American College of Rheumatology 1987 criteria [25]. We excluded patients with missing clinical data (n = 57) and those receiving maintenance hemodialysis (n = 2) to yield a population of 428 patients. This final population was reviewed retrospectively to determine the incidence rates of CVD, death, and loss to follow-up until the end of the study (March 31, 2014). Procedure Nurses or doctors in the outpatient department administered a lifestyle and medical history questionnaire to study participants, collected blood and urine samples, and measured blood pressure levels. CKD was defined as an estimated glomerular filtration rate (eGFR) of <60 mL/min/1.73 m2 and/or the presence of proteinuria for 3 months, according to the criteria of the Japanese Society of Nephrology [26]. The following risk factors for CVD were defined: hypertension, more than two resting blood pressure measurements of 140 mmHg systolic and/or 90 mmHg diastolic or treatment with antihypertensive agents; diabetes mellitus, at least two measured fasting plasma glucose levels 126 mg/dL, a 2-h plasma glucose level 200 mg/ dL, or treatment with hypoglycemic agents; and dyslipidemia, a low-density lipoprotein cholesterol level 140 mg/dL, highdensity lipoprotein cholesterol level <40 mg/dL, triglyceride level 150 mg/dL, or treatment with specific lipid-lowering agents, according to the criteria of the Japan Atherosclerosis Society [27]. The clinical characteristics of RA were assessed based on medical records. These parameters included the disease duration and the continuous use of anti-rheumatic medication, including methotrexate (MTX), other disease modifying anti-rheumatic drugs (DMARDs: bucillamine, sulfasalazine, D-penicillamine, auranofin, actarit, mizoribine, tacrolimus, and leflunomide), biological agents, corticosteroids, and nonsteroidal anti-inflammatory drugs (NSAIDs), for 6 months during the interval between the first and third CRP measurements. The eGFR was calculated using the Japanese Society of Nephrology formula [28]: eGFR (mL/min/1.73 m2) = 194 serum creatinine 1.094 age 0.287(0.739, if female). The serum creatinine level was measured using an enzymatic method (Sekisui Medical, Tokyo, Japan). Proteinuria was defined as a dipstick urinalysis score of 1+ or higher (Eiken Chemical, Tokyo, Japan). CRP levels were measured using the Nanopia CRP test, which was based on a latex agglutination immunoassay method (Sekisui Medical) and had a normal assay range of 3 mg/L. Blood glucose, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglyceride levels were determined using a HITACHI 7170 autoanalyzer (Hitachi, Tokyo, Japan). Rheumatoid factor was measured using a latex agglutination test (Mitsubishi Kagaku Iatron, Tokyo, Japan).
Subgroups by CKD and CRP data CRP is an acute-phase reactant protein produced in response to many inflammatory conditions. Given the chronic inflammatory nature of RA, however, we used the mean CRP values during the first 6 months of follow-up to diagnose a sustained inflammatory state. Accordingly, we measured CRP at three time points, at baseline and at 3 (range: 2–4 months), and 6 months (range: 5–7 months) from the baseline, and calculated the mean CRP value for each patient. A high mean CRP value was defined as exceeding their median values, whereas a low value was defined as below their median values. Patients were subsequently categorized into four groups according to the CKD status and CRP value to examine the combined effect of these parameters: non-CKD with low CRP, non-CKD with high CRP, CKD with low CRP, and CKD with high CRP. Outcome For this analysis, the primary outcomes were hospitalization for fatal or nonfatal coronary heart disease (CHD), congestive heart failure (CHF), or stroke. The diagnostic accuracy of our review of the medical records was confirmed using the following criteria. CHD diagnoses were based on the following information: presence of chest pain, abnormal cardiac enzymes, evolving diagnostic electrocardiogram changes, and/or morphologic changes, including local asynergistic cardiac wall motion on echocardiography. CHF was defined according to the Framingham criteria [29]. Stroke was defined as the sudden onset of an inconclusive and focal neurologic deficit persisting for >24 h, and new findings on brain computed tomography or magnetic resonance imaging. Statistical analysis Student's unpaired t test (parametric distributions) or the Mann–Whitney test (nonparametric distributions) was used as appropriate for the comparative analyses of CKD subgroups. Parametric analyses to determine intergroup differences in discrete variables among the four CKD/CRP subgroups were conducted using an analysis of variance, followed by the Tukey– Kramer post hoc test. Nonparametric analyses were conducted using the Kruskal–Wallis test with the Steel–Dwass test. Cumulative event-free survival rates were calculated using the Kaplan– Meier method, and intergroup differences were assessed using the log-rank test. Patients were censored from this analysis at the time of an event (including death), loss to follow-up, or the end of follow-up, whichever came first. A Cox proportional hazard analysis was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD development in both crude and adjusted models. We further calculated the HRs for CVD among the CKD/CRP subgroups. The following covariates were included in the adjusted models: age (10-year increments), sex, and traditional CV risk factors, including CVD history (yes/no), hypertension (yes/no), diabetes mellitus (yes/no), dyslipidemia (yes/no), and smoking status (ever/never). The effects of interactions between CKD and high CRP on CVD were tested by entering the two independent variables and their product term into the same model, and beginning the time intervals for the cumulative event-free survival curves and Cox proportional hazard analysis after the third CRP measurement. Statistical analyses were performed using the JMP software package (SAS Institute Inc., Cary, NC, USA). Continuous data are expressed as means standard deviations, whereas skewed distributions are presented as medians with 25th and 75th percentiles. A p-value < 0.05 was considered statistically significant.
Please cite this article in press as: Kochi M, et al. Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis. J Cardiol (2017), http://dx.doi.org/10.1016/j.jjcc.2017.08.008
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Table 1 Baseline clinical characteristics of patients according to the CKD subgroups.
Age, years Female, n (%) Serum creatinine (mg/dL) eGFR, mL/min/1.73 m2 Proteinuria, n (%) CRP, mg/dL Comorbid condition CVD history, n (%) Hypertension, n (%) Diabetes mellitus, n (%) Dyslipidemia, n (%) Overweight, n (%) Smoking, n (%) RA-related Disease duration of RA, years Rheumatoid factor postive, n (%) Current methotrexate, n (%) Other DMARDs, n (%) Current biological agent, n (%) Current corticosteroids, n (%) Current NSAIDs, n (%)
All patients (n = 428)
CKD (n = 67)
Non-CKD (n = 361)
p value
59.7 (13.4) 354 (83) 0.67 (0.31) 80.5 (21.6) 17 (4) 0.57 (0.18,1.51)
71.6 (9.9) 48 (72) 1.05 (0.62) 51.4 (19.2) 17 (25) 0.75 (0.27,1.85)
57.5 (12.8) 306 (85) 0.60 (0.11) 85.9 (17.3) 0 (0) 0.54 (0.16,14.4)
<0.001 0.009 <0.001 <0.001 <0.001 0.02
16 (4) 212 (50) 51 (12) 129 (30) 118 (28) 44 (10)
2 (3) 53 (79) 15 (22) 24 (36) 19 (28) 6 (9)
14 (4) 159 (44) 36 (10) 105 (29) 99 (27) 38 (11)
0.72 <0.001 0.004 0.27 0.88 0.70
6 (3,11) 353 (82) 215 (50) 291 (68) 33 (8) 41 (56) 191 (45)
7 (3,15) 55 (82) 21 (31) 46 (69) 2 (3) 35 (52) 24 (36)
6 (3,11) 298 (83) 194 (54) 245 (68) 31 (9) 206 (57) 167 (46)
0.20 0.93 <0.001 0.90 0.11 0.46 0.11
CKD, chronic kidney disease; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; RA, rheumatoid arthritis; DMARDs, disease modifying anti-rheumatic drugs; NSAIDs, nonsteroidal anti-inflammatory drugs. Data are expressed as mean standard deviation, medians (25th, 75th), or number (%).
Results Baseline characteristics according to CKD subgroup Table 1 summarizes the baseline patient characteristics according to CKD subgroups. The mean baseline patient age was 59.7 years, and 354 (83%) patients were female. The mean eGFR was 80.5 mL/min/1.73 m2, and the CKD prevalence was 16% (n = 67). The median of the mean individual CRP values during the first 6 months of follow-up was 0.57 mg/dL. Patients with CKD were significantly older, predominantly male, and had higher prevalence rates of hypertension and diabetes mellitus, compared to patients without CKD. Furthermore, patients with CKD had significantly higher CRP values, compared to those with non-CKD, as well as a significantly lower prevalence of MTX use. Outcomes according to CKD subgroup
were significantly older and had higher prevalence rates of hypertension, diabetes mellitus, and rheumatoid factor positivity, a higher frequency of current other DMARD use, and a longer disease duration, compared to patients in the non-CKD with low CRP group. However, no patients in the CKD with high CRP group were currently using biological agents. Among patients with CKD, those with low and high CRP levels did not differ regarding age and eGFR levels, whereas among patients without CKD, those with a high CRP level had a higher eGFR level, compared to those with a low CRP level. The CRP levels in the low and high CRP subgroups did not differ with respect to CKD status. Among patients with CKD, those with high CRP had a higher prevalence of proteinuria, compared to those with low CRP. The prevalence of current MTX use was lower in the CKD with low CRP and CKD with high CRP groups than in the non-CKD with high CRP group, and the prevalence of current NSAID use was lower in the CKD with low CRP group, compared to the non-CKD with high CRP group.
The median follow-up duration after the third CRP measurement was 89 months. During this period, 30 patients (7%) died from any cause, 29 (6.8%) were lost to follow-up, and 66 (15%) switched hospitals and could not continue the follow-up evaluations. A total of 38 patients (9%) developed CVD during this period, and Fig. 1 presents the cumulative event-free survival curves according to CKD subgroup. During the follow-up period, patients with CKD had a significantly lower cumulative event-free survival rate, compared to those without CKD (p < 0.0001, log-rank test). Baseline characteristics according to CKD and CRP subgroups In this study, the median of mean individual CRP values during the first 6 months of follow-up was 0.57 mg/dL, and high and low CRP values were accordingly defined as 0.57 mg/L and <0.57 mg/ L, respectively. The patients were subsequently divided into four CKD/CRP subgroups as described previously, with 188 (44%), 173 (40%), 26 (6%), and 41 (10%) in the non-CKD with low CRP, non-CKD with high CRP, CKD with low CRP, and CKD with high CRP groups, respectively. The baseline patient characteristics of each subgroup are summarized in Table 2. Patients in the CKD with high CRP group
Fig. 1. Cumulative event-free survival curves according to the CKD subgroups. The cumulative event-free survival rate was significantly lower among patients with CKD, compared to those without CKD (p < 0.0001, Kaplan–Meier method, log-rank test). CKD, chronic kidney disease; CVD, cardiovascular disease.
Please cite this article in press as: Kochi M, et al. Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis. J Cardiol (2017), http://dx.doi.org/10.1016/j.jjcc.2017.08.008
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Table 2 Baseline clinical characteristics of patients according to the CKD and CRP subgroups. Non-CKD with low CRPa (n = 188)
Non-CKD with high CRPb (n = 173)
59.7 (13.4) 354 (83) 0.67 (0.31) 80.5 (21.6) 17 (4) 0.57 (0.18, 1.51)
55.9 (12.5) 162 (86) 0.62 (0.11) 83.2 (14.2) 0 (0) 0.16 (0.06, 0.32)
16 (4) 212 (50) 51 (12) 129 (30) 44 (10) 6 (3,11) 353 (82) 215 (50) 291 (68) 33 (8) 241 (56) 191 (45)
All patients (n = 428) Age, years Female, n (%) Serum creatinine (mg/dL) eGFR, mL/min/1.73 m2 proteinuria, n (%) CRPa, mg/dL Comorbid condition CVD history, n (%) Hypertension, n (%) Diabetes mellitus, n (%) Dyslipidemia, n (%) Smoking, n (%) RA-related Disease duration of RA, years Rheumatoid factor postive, n (%) Current methotrexate, n (%) Other DMARDsb, n (%) Current biological agent, n (%) Current corticosteroids, n (%) Current nonsteroidal anti-inflammatory drugs, n (%)
CKD with low CRP (n = 26)
CKD with high CRP (n = 41)
p value
59.2c (13.0) 144 (83) 0.58c (0.11) 88.8c (19.7) 0 (0) 1.65c (0.88, 2.88)
72.7c,d (10.5) 18 (69) 1.03c,d (0.27) 47.6c,d (10.3) 3c,d (12) 0.16d (0.08, 0.40)
70.9c,d (9.5) 30 (73) 1.06c,d (0.76) 53.8c,d (22.9) 14c,d,e (34) 1.63c, e (0.66, 3.20)
<0.0001 0.06 <0.001 <0.0001 <0.0001 <0.0001
8 (4.3) 74 (39) 15 (8.0) 51 (27) 18 (9.6)
6 (3.5) 85 (49) 21 (12.1) 54 (42) 20 (11.6)
0 (0) 20c,d (77) 3 (11.5) 13 (50) 2 (7.7)
2 (4.9) 33c,d (80) 12c,d (29.3) 11 (27) 4 (9.8)
0.72 <0.0001 0.002 0.11 0.89
5 (2.3,11) 145 (77) 93 (49) 119 (63) 12 (6.4) 86 (46) 25 (40)
6 (3,12.5) 153c (88) 101 (58) 126 (73) 19 (11) 120c (69) 92 (53)
5.5 (2,9.8) 17d (65) 9d (35) 13d (50) 2 (7.7) 9d (35) 7d (27)
9c (5.5,16) 38c,e (93) 12c,d (29) 33c,e (80) 0d (0) 26e (63) 17 (41)
0.004 0.002 0.002 0.01 0.09 <0.0001 0.02
CKD, chronic kidney disease; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; CVD, cardiovascular disease; RA, rheumatoid arthritis; DMARDs, disease modifying anti-rheumatic drugs. Data are expressed as mean standard deviation, medians (25th, 75th), or number (%). a Low CRP was defined as < 0.57 mg/dL on the basis of the mean CRP values during the first 6 months of follow-up. b High CRP was defined as 0.57 mg/dL on the basis of the mean CRP values during the first 6 months of follow-up. c p < 0.05vs non CKD with low CRP. d p < 0.05vs non CKD with high CRP. e p < 0.05vs CKD with low CRP.
Outcome according to CKD and CRP subgroups Fig. 2 presents the cumulative event-free survival curves for each of the CKD and CRP subgroups. The cumulative event-free survival rate was significantly lower among patients in the CKD with high CRP group, compared with the other groups (p < 0.0001, log-rank test). Predictors of CVD As shown in Table 3, CVD development correlated significantly with age, CKD, high CRP, CVD history, hypertension, and smoking
status. In the multivariate analysis, both CKD and high CRP remained significantly associated with an increased risk of CVD, even after adjusting for traditional CV risk factors. Risk of CVD according to CKD and CRP subgroups Fig. 3 presents the HRs for the association of CVD incidence with CKD/CRP subgroup, determined using Cox proportional hazard models. After setting the non-CKD with low CRP group as the reference, a non-CKD with high CRP status was associated with an increasing risk of CVD, even after adjusting for traditional risk factors (HR, 3.51; 95% CI: 1.42–10.01; p = 0.006); however, a CKD
Fig. 2. Cumulative event-free survival curves for CKD and CRP subgroups. The cumulative event-free survival rate was significantly lower among patients with CKD and a high CRP level, compared with other groups (p < 0.0001, Kaplan–Meier method and log-rank test). CKD, chronic kidney disease; CRP, C-reactive protein; CVD, cardiovascular disease.
Please cite this article in press as: Kochi M, et al. Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis. J Cardiol (2017), http://dx.doi.org/10.1016/j.jjcc.2017.08.008
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Table 3 Univariate and multivariate analysis of predictors of CVD development. Univariate
Variable
Age (10-year increment) Male vs. female CKD High CRP a CVD history Hypertension Diabetes Dyslipidemia Smoking
Multivariate adjusted
HR (95%CI)
p-value
HR (95%CI)
p-value
2.17 (1.62–2.95) 1.53 (0.68–3.11) 3.88 (1.96–7.42) 4.00 (1.93–9.37) 8.46 (3.60–17.67) 3.92 (1.88–9.17) 1.75 (0.71–3.75) 1.21 (0.60–2.32) 2.58 (1.10–5.36)
<0.0001 0.28 <0.0001 0.0001 <0.0001 <0.0001 0.21 0.59 0.03
1.73 (1.22–2.50) 0.54 (0.20–1.33) 2.61 (1.18–5.63) 3.95 (1.85–9.49) 6.42 (2.47–15.58) 1.53 (0.67–3.85) 0.67 (0.26–1.50) 0.98 (0.48–1.94) 5.07 (1.75–13.72)
0.002 0.19 0.02 0.0002 0.0003 0.32 0.34 0.96 0.004
HR, hazard ratio; CI, confidence interval; CKD, chronic kidney disease; CRP, C-reactive protein; CVD, cardiovascular disease. High CRP was defined as 0.57 mg/dL on the basis of the mean CRP values during the first 6 months of follow-up.
a
Fig. 3. Hazard ratios of CVD development by CKD and CRP status. Hazard ratios were adjusted by age (10-year increment), sex, CVD history, hypertension, diabetes, dyslipidemia, and smoking status. The CVD prevalence was significantly higher among subjects with CKD and a high CRP level, compared to the reference values (non-CKD, low CRP). CVD, cardiovascular disease; CKD, chronic kidney disease; CRP, C-reactive protein.
with low CRP status did not have a statistically significant influence on CVD incidence (HR, 1.88; 95% CI: 0.25–9.44; p = 0.49). Patients in the CKD with high CRP group had an approximately 10-fold higher risk of CVD relative to the reference group (HR, 9.71; 95% CI: 3.27– 31.97; p < 0.0001). Notably, the increased risk of CKD-associated CVD was only statistically prevalent among patients with high CRP levels. The CKD with high CRP group had a significantly higher HR for CVD development, compared with all other groups (p < 0.0001, p = 0.02, and p = 0.01 vs. the non-CKD with low CRP, non-CKD
with high CRP, and CKD with low CRP groups, respectively). However, no interaction was observed between CKD and a high CRP level (p = 0.67). As shown in Table 4, patients in the CKD with high CRP group exhibited higher prevalence rates of both cardiac and stroke events, compared with the other subgroups. Discussion In this study of patients with RA, we identified CKD as a significant risk factor for CVD development. Furthermore, patients
Table 4 CVD development according to CKD and CRP subgroups. Non-CKD with low CRP (n = 188) CVD, n (%) Cardiac events, n (%) Coronary heart disease, n (%) Congestive heart failure, n (%) Stroke Ischemic stroke, n (%) Hemorrhagic stroke, n (%)
6 4 3 1 2 0 2
(3.2) (2.1) (1.6) (0.5) (1.1) (0) (1.1)
Non-CKD with high CRP (n = 173) 18 (10.4) 10 (5.8) 8 (4.6) 2 (1.2) 8 (4.6) 5 (2.9) 3 (1.7)
CKD with low CRP (n = 26) 2 2 1 1 0 0 0
(7.8) (7.8) (3.9) (3.9) (0) (0) (0)
CKD with high CRP (n = 41) 12 (29.2) 8 (19.5) 7 (17.1) 1 (2.4) 4 (9.7) 3 (7.3) 1 (2.4)
CKD, chronic kidney disease; CRP, C-reactive protein; CVD, cardiovascular disease.
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with CKD and inflammation, as determined by CRP levels, faced a particularly high risk of CVD development. A few studies previously investigated the association between CKD and CVD in patients with RA [15,16,30]. Our observation of a higher incidence of CVD among patients with CKD aligned with the findings of those earlier studies. Although other mechanisms might contribute to this association, inflammation may play a critical role in the progression of CVD in RA patients with CKD. As in previous studies [31–33], patients with CKD in our study had higher CRP levels relative to those without CKD. Reports of patients with CKD have indicated an increase in the oxidative stress-induced production of inflammatory mediators [34], along with reduced urinary excretion of these products [35]. A previous study demonstrated positive, dose-dependent relationships of an elevated CRP level with blood pressure, glucose, and lipid levels, and body mass index among patients with CKD [33]. Accordingly, these confounding factors might influence the relationship between inflammation and higher risk of CVD in CKD patients. Alternatively, inflammation can promote atherosclerosis by inducing endothelial activation and dysfunction [36,37], and may therefore act as a non-traditional risk factor to direct the development of CVD in CKD patients [18–20]. Notably, the risk of CVD in CKD is further increased among patients with elevated CRP levels. A previous study demonstrated that an elevated CRP level was associated with an approximately two-fold increase in CV mortality among patients with CKD [20]. These findings suggest that the interaction between CKD and inflammation affects the risk of CVD among patients with RA. However, we did not observe a significant interaction between CKD and a high CRP level, suggesting that inflammation had a merely additive effect on the link between CKD and CVD development in patients with RA. Our findings were supported by a previous study in which both elevated CRP and CKD were predictive of CV events, but did not exert a synergistic effect in a community-based population [38]. Our findings may have important clinical implications. First, they suggest that an evaluation of traditional CV risk factors may be insufficient to determine the CVD risk among patients with RA. Rather, a simple evaluation of the CKD status, using measurements of both eGFR and proteinuria, could provide a more reliable stratification of the total CV risk. In particular, our findings emphasize that RA patients with CKD, if accompanied by chronically elevated CRP levels, have a greatly increased risk of experiencing a CV event in the subsequent 10-year period. Second, our results suggest that insufficient control of RA disease activity may induce CVD, particularly in patients with CKD, as the latter had a profound impact on CV events in patients with concomitantly elevated CRP levels. A previous large cohort study demonstrated that MTX use, in addition to good disease activity control, was significantly associated with a favorable CV outcome among patients with RA [39,40]. Therefore, strong RA disease activity control may improve the CV outcomes of patients, particularly those with CKD. In accordance with this hypothesis, a previous study reported that more strict RA control, mediated by intensive treatment, reduced the risk of incident CVD [41– 44]. Further prospective studies are warranted to address this important issue. This study had some limitations. First, we did not consider changes in various factors, including medication use, traditional risk factor control status, and RA disease activity, over the course of the study, and these undefined factors might have affected the results. However, the presence of CKD and a high CRP level predicted future CVD development, regardless of variations in patients’ clinical conditions. Second, our study was retrospective, and CV events were diagnosed based on medical records. Although we reviewed patients’ medical records and re-evaluated their
diagnostic accuracy, the incidence of CV events might have been underestimated; for example, CV events that required management at admission may have been omitted. The resulting underestimation might have complicated our analysis of the differences in CV event incidence between the groups. Third, we used only CRP as an inflammatory marker and did not have access to other data regarding other inflammatory markers (e.g. interleukin 6, tumor necrotizing factor-alpha). However, CRP is a commonly used biomarker of systemic inflammation and has been associated with an increased risk of CVD in patients with RA [22,23,45]. Fourth, the patient cohort comprised a relatively small number of patients from a single center in Japan. We therefore cannot exclude the possibility that our multivariate model was overfitted because of the small number of outcome events. Therefore, caution must be exercised when extrapolating our results, and large-scale, multicenter cohort studies are needed to confirm our findings. Conclusions Inflammation was associated with the heightened risk of CVD and the concomitant CKD further augmented the risk, although the sole effect of CKD on the risk of CVD was marginal. Therefore, inflammation might underlie much of the relationship between CKD and CVD in patients with RA. Further studies are warranted to evaluate the effects of therapies targeting CKD and inflammation on CV outcomes in patients with RA. Acknowledgments The authors are grateful to the nursing staff, medical assistant staff, nephrologists, and rheumatologists in Tomishiro Central Hospital. We are also grateful to the following doctors who gave invaluable advice and support: A. Higa and Y. Uezu. Funding There are no funding sources to be disclosed. Conflict of interest The authors declare that there is no conflict of interest. References [1] Meune C, Touzé E, Trinquart L, Allanore Y. Trends in cardiovascular mortality in patients with rheumatoid arthritis over 50 years: a systematic review and meta-analysis of cohort studies. Rheumatology (Oxford) 2009;48:1309–13. [2] Maradit-Kremers H, Nicola PJ, Crowson CS, Ballman KV, Gabriel SE. Cardiovascular death in rheumatoid arthritis: a population-based study. Arthritis Rheum 2005;52:722–32. [3] Lévy L, Fautrel B, Barnetche T, Schaeverbeke T. Incidence and risk of fatal myocardial infarction and stroke events in rheumatoid arthritis patients. A systematic review of the literature. Clin Exp Rheumatol 2008;26:673–9. [4] Solomon DH, Kremer J, Curtis JR, Hochberg MC, Reed G, Tsao P, Wang Y, Kang JP, Ning M, Wu JH, Ruan YF, Yu RH, Long DY, Tang RB, Sang CH, et al. Explaining the cardiovascular risk associated with rheumatoid arthritis: traditional risk factors versus markers of rheumatoid arthritis severity. Ann Rheum Dis 2010;69:1920–5. [5] Wen SN, Liu N, Li SN, Salim M, Yan Q, Wu XY, Wang Y, Kang JP, Ning M, Wu JH, Ruan YF, Yu RH, Long DY, Tang RB, Sang CH, et al. Catheter ablation of atrial fibrillation in patients with rheumatoid arthritis. J Cardiol 2015;66:320–5. [6] Aviña-Zubieta JA, Choi HK, Sadatsafavi M, Etminan M, Esdaile JM, Lacaille D. Risk of cardiovascular mortality in patients with rheumatoid arthritis: a metaanalysis of observational studies. Arthritis Rheum 2008;59:1690–7. [7] Peters MJ, van Halm VP, Voskuyl AE, Smulders YM, Boers M, Lems WF, Visser M, Stehouwer CD, Dekker JM, Nijpels G, Heine R, Dijkmans BA, Nurmohamed MT. Does rheumatoid arthritis equal diabetes mellitus as an independent risk factor for cardiovascular disease?. A prospective study. Arthritis Rheum 2009;61:1571–9. [8] Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296–305.
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JJCC-1547; No. of Pages 7 Journal of Cardiology xxx (2017) xxx–xxx
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Original article
Chronic kidney disease, inflammation, and cardiovascular disease risk in rheumatoid arthritis Masako Kochi (MD)a,b, Kentaro Kohagura (MD, PhD)c,*, Yoshiki Shiohira (MD)d, Kunitoshi Iseki (MD, PhD)d,e, Yusuke Ohya (MD, PhD, FJCC)a a
Department of Cardiovascular Medicine, Nephrology and Neurology, University of the Ryukyus School of Medicine, Nishihara, Japan Yuuaikai Nanbu Hospital, Itoman, Okinawa, Japan Dialysis Unit, University of the Ryukyus Hospital, Nishihara, Japan d Yuuaikai Tomishiro Central Hospital, Tomigusuku, Okinawa, Japan e Okinawa Heart and Renal Association, Okinawa, Japan b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 5 June 2017 Received in revised form 31 July 2017 Accepted 15 August 2017 Available online xxx
Background: Rheumatoid arthritis (RA), a prototypic systemic autoimmune inflammatory condition, confers an increased risk of cardiovascular disease (CVD). Recently, chronic kidney disease (CKD) was suggested to increase the risk of CVD in RA patients, and inflammation was identified as a critical, nontraditional CKD-associated risk factor for CVD. This study aimed to examine the combined effects of CKD and CVD in RA patients. Methods: In this retrospective evaluation of 428 RA patients, the outcome of interest was the incidence of CVD. CKD was defined as an estimated glomerular filtration rate of <60 mL/min/1.73 m2 and/or positive dipstick tests for proteinuria of 3 months duration. C-reactive protein (CRP) was used as an inflammation marker, and a high CRP level was defined as a mean CRP value of 0.57 mg/dL during the first 6 months of follow-up. Patients were categorized as follows: non-CKD with low CRP, non-CKD with high CRP, CKD with low CRP, and CKD with high CRP. Results: During a median follow-up of 89 months, 67 patients (16%) had CKD, and 38 (9%) developed CVD. Using patients with non-CKD and low CRP as a reference group, the adjusted hazard ratios (HR, 95% confidence interval) for CVD were 1.88 (0.25–9.44) for patients with CKD/low CRP and 9.71 (3.27–31.97) for those with CKD/high CRP. Conclusions: The coexistence of CKD and inflammation was associated with a higher risk of CVD than either condition alone in RA patients. Inflammation might increase the risk of CVD especially in patients with CKD. © 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.
Keywords: C-reactive protein Cardiovascular disease Chronic kidney disease Inflammation Rheumatoid arthritis
Introduction Patients with rheumatoid arthritis (RA), a prototypic autoimmune disease characterized by chronic systemic inflammation, face an increased risk of cardiovascular disease (CVD) [1– 5]. Currently, the reported incidence of CVD is >50% higher among RA patients than in the general population [6,7]. Although both traditional cardiovascular (CV) risk factors and inflammation contribute to this increased CVD risk [4], the mechanism underlying this process remains unclear.
* Corresponding author at: Dialysis Unit, University Hospital of the Ryukyus, 207 Uehara, Nishihara, Okinawa 903-0215, Japan. E-mail address: [email protected] (K. Kohagura).
Chronic kidney disease (CKD), known as an independent risk factor for CVD in the general population [8–12], is a frequent comorbidity among RA patients [13,14] and was recently suggested to increase the risk of CVD in this population [15,16]. Inflammation, an atherosclerotic factor, is a manifestation of CVD [17] and is considered an untraditional CV risk factor in CKD patients [17–21]. Notably, inflammation has been described as a potential primary mediator or “missing link” to explain the tremendous burden of CVD experienced by CKD patients [18]. Despite the associations of chronic inflammation with CV mortality and morbidity in RA patients [2,22–24], it remains unclear whether inflammation also affects the mechanisms underlying the high risk of CVD in CKD among this population. The present study therefore aimed to examine the combined effects of CKD and inflammation, indicated by the
http://dx.doi.org/10.1016/j.jjcc.2017.08.008 0914-5087/© 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.
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marker C-reactive protein (CRP), on CVD development in RA patients. Materials and methods Participants This retrospective study of digital medical records from Tomishiro Central Hospital (Okinawa, Japan) was conducted after obtaining permission from the Ethical Committee of Tomishiro Central Hospital. Prior to accession for this study, the data from medical records were anonymized. As a baseline, we screened 487 adult patients (older than 18 years) who visited the hospital in April 2006 and met the American College of Rheumatology 1987 criteria [25]. We excluded patients with missing clinical data (n = 57) and those receiving maintenance hemodialysis (n = 2) to yield a population of 428 patients. This final population was reviewed retrospectively to determine the incidence rates of CVD, death, and loss to follow-up until the end of the study (March 31, 2014). Procedure Nurses or doctors in the outpatient department administered a lifestyle and medical history questionnaire to study participants, collected blood and urine samples, and measured blood pressure levels. CKD was defined as an estimated glomerular filtration rate (eGFR) of <60 mL/min/1.73 m2 and/or the presence of proteinuria for 3 months, according to the criteria of the Japanese Society of Nephrology [26]. The following risk factors for CVD were defined: hypertension, more than two resting blood pressure measurements of 140 mmHg systolic and/or 90 mmHg diastolic or treatment with antihypertensive agents; diabetes mellitus, at least two measured fasting plasma glucose levels 126 mg/dL, a 2-h plasma glucose level 200 mg/ dL, or treatment with hypoglycemic agents; and dyslipidemia, a low-density lipoprotein cholesterol level 140 mg/dL, highdensity lipoprotein cholesterol level <40 mg/dL, triglyceride level 150 mg/dL, or treatment with specific lipid-lowering agents, according to the criteria of the Japan Atherosclerosis Society [27]. The clinical characteristics of RA were assessed based on medical records. These parameters included the disease duration and the continuous use of anti-rheumatic medication, including methotrexate (MTX), other disease modifying anti-rheumatic drugs (DMARDs: bucillamine, sulfasalazine, D-penicillamine, auranofin, actarit, mizoribine, tacrolimus, and leflunomide), biological agents, corticosteroids, and nonsteroidal anti-inflammatory drugs (NSAIDs), for 6 months during the interval between the first and third CRP measurements. The eGFR was calculated using the Japanese Society of Nephrology formula [28]: eGFR (mL/min/1.73 m2) = 194 serum creatinine 1.094 age 0.287(0.739, if female). The serum creatinine level was measured using an enzymatic method (Sekisui Medical, Tokyo, Japan). Proteinuria was defined as a dipstick urinalysis score of 1+ or higher (Eiken Chemical, Tokyo, Japan). CRP levels were measured using the Nanopia CRP test, which was based on a latex agglutination immunoassay method (Sekisui Medical) and had a normal assay range of 3 mg/L. Blood glucose, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglyceride levels were determined using a HITACHI 7170 autoanalyzer (Hitachi, Tokyo, Japan). Rheumatoid factor was measured using a latex agglutination test (Mitsubishi Kagaku Iatron, Tokyo, Japan).
Subgroups by CKD and CRP data CRP is an acute-phase reactant protein produced in response to many inflammatory conditions. Given the chronic inflammatory nature of RA, however, we used the mean CRP values during the first 6 months of follow-up to diagnose a sustained inflammatory state. Accordingly, we measured CRP at three time points, at baseline and at 3 (range: 2–4 months), and 6 months (range: 5–7 months) from the baseline, and calculated the mean CRP value for each patient. A high mean CRP value was defined as exceeding their median values, whereas a low value was defined as below their median values. Patients were subsequently categorized into four groups according to the CKD status and CRP value to examine the combined effect of these parameters: non-CKD with low CRP, non-CKD with high CRP, CKD with low CRP, and CKD with high CRP. Outcome For this analysis, the primary outcomes were hospitalization for fatal or nonfatal coronary heart disease (CHD), congestive heart failure (CHF), or stroke. The diagnostic accuracy of our review of the medical records was confirmed using the following criteria. CHD diagnoses were based on the following information: presence of chest pain, abnormal cardiac enzymes, evolving diagnostic electrocardiogram changes, and/or morphologic changes, including local asynergistic cardiac wall motion on echocardiography. CHF was defined according to the Framingham criteria [29]. Stroke was defined as the sudden onset of an inconclusive and focal neurologic deficit persisting for >24 h, and new findings on brain computed tomography or magnetic resonance imaging. Statistical analysis Student's unpaired t test (parametric distributions) or the Mann–Whitney test (nonparametric distributions) was used as appropriate for the comparative analyses of CKD subgroups. Parametric analyses to determine intergroup differences in discrete variables among the four CKD/CRP subgroups were conducted using an analysis of variance, followed by the Tukey– Kramer post hoc test. Nonparametric analyses were conducted using the Kruskal–Wallis test with the Steel–Dwass test. Cumulative event-free survival rates were calculated using the Kaplan– Meier method, and intergroup differences were assessed using the log-rank test. Patients were censored from this analysis at the time of an event (including death), loss to follow-up, or the end of follow-up, whichever came first. A Cox proportional hazard analysis was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD development in both crude and adjusted models. We further calculated the HRs for CVD among the CKD/CRP subgroups. The following covariates were included in the adjusted models: age (10-year increments), sex, and traditional CV risk factors, including CVD history (yes/no), hypertension (yes/no), diabetes mellitus (yes/no), dyslipidemia (yes/no), and smoking status (ever/never). The effects of interactions between CKD and high CRP on CVD were tested by entering the two independent variables and their product term into the same model, and beginning the time intervals for the cumulative event-free survival curves and Cox proportional hazard analysis after the third CRP measurement. Statistical analyses were performed using the JMP software package (SAS Institute Inc., Cary, NC, USA). Continuous data are expressed as means standard deviations, whereas skewed distributions are presented as medians with 25th and 75th percentiles. A p-value < 0.05 was considered statistically significant.
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Table 1 Baseline clinical characteristics of patients according to the CKD subgroups.
Age, years Female, n (%) Serum creatinine (mg/dL) eGFR, mL/min/1.73 m2 Proteinuria, n (%) CRP, mg/dL Comorbid condition CVD history, n (%) Hypertension, n (%) Diabetes mellitus, n (%) Dyslipidemia, n (%) Overweight, n (%) Smoking, n (%) RA-related Disease duration of RA, years Rheumatoid factor postive, n (%) Current methotrexate, n (%) Other DMARDs, n (%) Current biological agent, n (%) Current corticosteroids, n (%) Current NSAIDs, n (%)
All patients (n = 428)
CKD (n = 67)
Non-CKD (n = 361)
p value
59.7 (13.4) 354 (83) 0.67 (0.31) 80.5 (21.6) 17 (4) 0.57 (0.18,1.51)
71.6 (9.9) 48 (72) 1.05 (0.62) 51.4 (19.2) 17 (25) 0.75 (0.27,1.85)
57.5 (12.8) 306 (85) 0.60 (0.11) 85.9 (17.3) 0 (0) 0.54 (0.16,14.4)
<0.001 0.009 <0.001 <0.001 <0.001 0.02
16 (4) 212 (50) 51 (12) 129 (30) 118 (28) 44 (10)
2 (3) 53 (79) 15 (22) 24 (36) 19 (28) 6 (9)
14 (4) 159 (44) 36 (10) 105 (29) 99 (27) 38 (11)
0.72 <0.001 0.004 0.27 0.88 0.70
6 (3,11) 353 (82) 215 (50) 291 (68) 33 (8) 41 (56) 191 (45)
7 (3,15) 55 (82) 21 (31) 46 (69) 2 (3) 35 (52) 24 (36)
6 (3,11) 298 (83) 194 (54) 245 (68) 31 (9) 206 (57) 167 (46)
0.20 0.93 <0.001 0.90 0.11 0.46 0.11
CKD, chronic kidney disease; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; RA, rheumatoid arthritis; DMARDs, disease modifying anti-rheumatic drugs; NSAIDs, nonsteroidal anti-inflammatory drugs. Data are expressed as mean standard deviation, medians (25th, 75th), or number (%).
Results Baseline characteristics according to CKD subgroup Table 1 summarizes the baseline patient characteristics according to CKD subgroups. The mean baseline patient age was 59.7 years, and 354 (83%) patients were female. The mean eGFR was 80.5 mL/min/1.73 m2, and the CKD prevalence was 16% (n = 67). The median of the mean individual CRP values during the first 6 months of follow-up was 0.57 mg/dL. Patients with CKD were significantly older, predominantly male, and had higher prevalence rates of hypertension and diabetes mellitus, compared to patients without CKD. Furthermore, patients with CKD had significantly higher CRP values, compared to those with non-CKD, as well as a significantly lower prevalence of MTX use. Outcomes according to CKD subgroup
were significantly older and had higher prevalence rates of hypertension, diabetes mellitus, and rheumatoid factor positivity, a higher frequency of current other DMARD use, and a longer disease duration, compared to patients in the non-CKD with low CRP group. However, no patients in the CKD with high CRP group were currently using biological agents. Among patients with CKD, those with low and high CRP levels did not differ regarding age and eGFR levels, whereas among patients without CKD, those with a high CRP level had a higher eGFR level, compared to those with a low CRP level. The CRP levels in the low and high CRP subgroups did not differ with respect to CKD status. Among patients with CKD, those with high CRP had a higher prevalence of proteinuria, compared to those with low CRP. The prevalence of current MTX use was lower in the CKD with low CRP and CKD with high CRP groups than in the non-CKD with high CRP group, and the prevalence of current NSAID use was lower in the CKD with low CRP group, compared to the non-CKD with high CRP group.
The median follow-up duration after the third CRP measurement was 89 months. During this period, 30 patients (7%) died from any cause, 29 (6.8%) were lost to follow-up, and 66 (15%) switched hospitals and could not continue the follow-up evaluations. A total of 38 patients (9%) developed CVD during this period, and Fig. 1 presents the cumulative event-free survival curves according to CKD subgroup. During the follow-up period, patients with CKD had a significantly lower cumulative event-free survival rate, compared to those without CKD (p < 0.0001, log-rank test). Baseline characteristics according to CKD and CRP subgroups In this study, the median of mean individual CRP values during the first 6 months of follow-up was 0.57 mg/dL, and high and low CRP values were accordingly defined as 0.57 mg/L and <0.57 mg/ L, respectively. The patients were subsequently divided into four CKD/CRP subgroups as described previously, with 188 (44%), 173 (40%), 26 (6%), and 41 (10%) in the non-CKD with low CRP, non-CKD with high CRP, CKD with low CRP, and CKD with high CRP groups, respectively. The baseline patient characteristics of each subgroup are summarized in Table 2. Patients in the CKD with high CRP group
Fig. 1. Cumulative event-free survival curves according to the CKD subgroups. The cumulative event-free survival rate was significantly lower among patients with CKD, compared to those without CKD (p < 0.0001, Kaplan–Meier method, log-rank test). CKD, chronic kidney disease; CVD, cardiovascular disease.
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Table 2 Baseline clinical characteristics of patients according to the CKD and CRP subgroups. Non-CKD with low CRPa (n = 188)
Non-CKD with high CRPb (n = 173)
59.7 (13.4) 354 (83) 0.67 (0.31) 80.5 (21.6) 17 (4) 0.57 (0.18, 1.51)
55.9 (12.5) 162 (86) 0.62 (0.11) 83.2 (14.2) 0 (0) 0.16 (0.06, 0.32)
16 (4) 212 (50) 51 (12) 129 (30) 44 (10) 6 (3,11) 353 (82) 215 (50) 291 (68) 33 (8) 241 (56) 191 (45)
All patients (n = 428) Age, years Female, n (%) Serum creatinine (mg/dL) eGFR, mL/min/1.73 m2 proteinuria, n (%) CRPa, mg/dL Comorbid condition CVD history, n (%) Hypertension, n (%) Diabetes mellitus, n (%) Dyslipidemia, n (%) Smoking, n (%) RA-related Disease duration of RA, years Rheumatoid factor postive, n (%) Current methotrexate, n (%) Other DMARDsb, n (%) Current biological agent, n (%) Current corticosteroids, n (%) Current nonsteroidal anti-inflammatory drugs, n (%)
CKD with low CRP (n = 26)
CKD with high CRP (n = 41)
p value
59.2c (13.0) 144 (83) 0.58c (0.11) 88.8c (19.7) 0 (0) 1.65c (0.88, 2.88)
72.7c,d (10.5) 18 (69) 1.03c,d (0.27) 47.6c,d (10.3) 3c,d (12) 0.16d (0.08, 0.40)
70.9c,d (9.5) 30 (73) 1.06c,d (0.76) 53.8c,d (22.9) 14c,d,e (34) 1.63c, e (0.66, 3.20)
<0.0001 0.06 <0.001 <0.0001 <0.0001 <0.0001
8 (4.3) 74 (39) 15 (8.0) 51 (27) 18 (9.6)
6 (3.5) 85 (49) 21 (12.1) 54 (42) 20 (11.6)
0 (0) 20c,d (77) 3 (11.5) 13 (50) 2 (7.7)
2 (4.9) 33c,d (80) 12c,d (29.3) 11 (27) 4 (9.8)
0.72 <0.0001 0.002 0.11 0.89
5 (2.3,11) 145 (77) 93 (49) 119 (63) 12 (6.4) 86 (46) 25 (40)
6 (3,12.5) 153c (88) 101 (58) 126 (73) 19 (11) 120c (69) 92 (53)
5.5 (2,9.8) 17d (65) 9d (35) 13d (50) 2 (7.7) 9d (35) 7d (27)
9c (5.5,16) 38c,e (93) 12c,d (29) 33c,e (80) 0d (0) 26e (63) 17 (41)
0.004 0.002 0.002 0.01 0.09 <0.0001 0.02
CKD, chronic kidney disease; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; CVD, cardiovascular disease; RA, rheumatoid arthritis; DMARDs, disease modifying anti-rheumatic drugs. Data are expressed as mean standard deviation, medians (25th, 75th), or number (%). a Low CRP was defined as < 0.57 mg/dL on the basis of the mean CRP values during the first 6 months of follow-up. b High CRP was defined as 0.57 mg/dL on the basis of the mean CRP values during the first 6 months of follow-up. c p < 0.05vs non CKD with low CRP. d p < 0.05vs non CKD with high CRP. e p < 0.05vs CKD with low CRP.
Outcome according to CKD and CRP subgroups Fig. 2 presents the cumulative event-free survival curves for each of the CKD and CRP subgroups. The cumulative event-free survival rate was significantly lower among patients in the CKD with high CRP group, compared with the other groups (p < 0.0001, log-rank test). Predictors of CVD As shown in Table 3, CVD development correlated significantly with age, CKD, high CRP, CVD history, hypertension, and smoking
status. In the multivariate analysis, both CKD and high CRP remained significantly associated with an increased risk of CVD, even after adjusting for traditional CV risk factors. Risk of CVD according to CKD and CRP subgroups Fig. 3 presents the HRs for the association of CVD incidence with CKD/CRP subgroup, determined using Cox proportional hazard models. After setting the non-CKD with low CRP group as the reference, a non-CKD with high CRP status was associated with an increasing risk of CVD, even after adjusting for traditional risk factors (HR, 3.51; 95% CI: 1.42–10.01; p = 0.006); however, a CKD
Fig. 2. Cumulative event-free survival curves for CKD and CRP subgroups. The cumulative event-free survival rate was significantly lower among patients with CKD and a high CRP level, compared with other groups (p < 0.0001, Kaplan–Meier method and log-rank test). CKD, chronic kidney disease; CRP, C-reactive protein; CVD, cardiovascular disease.
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Table 3 Univariate and multivariate analysis of predictors of CVD development. Univariate
Variable
Age (10-year increment) Male vs. female CKD High CRP a CVD history Hypertension Diabetes Dyslipidemia Smoking
Multivariate adjusted
HR (95%CI)
p-value
HR (95%CI)
p-value
2.17 (1.62–2.95) 1.53 (0.68–3.11) 3.88 (1.96–7.42) 4.00 (1.93–9.37) 8.46 (3.60–17.67) 3.92 (1.88–9.17) 1.75 (0.71–3.75) 1.21 (0.60–2.32) 2.58 (1.10–5.36)
<0.0001 0.28 <0.0001 0.0001 <0.0001 <0.0001 0.21 0.59 0.03
1.73 (1.22–2.50) 0.54 (0.20–1.33) 2.61 (1.18–5.63) 3.95 (1.85–9.49) 6.42 (2.47–15.58) 1.53 (0.67–3.85) 0.67 (0.26–1.50) 0.98 (0.48–1.94) 5.07 (1.75–13.72)
0.002 0.19 0.02 0.0002 0.0003 0.32 0.34 0.96 0.004
HR, hazard ratio; CI, confidence interval; CKD, chronic kidney disease; CRP, C-reactive protein; CVD, cardiovascular disease. High CRP was defined as 0.57 mg/dL on the basis of the mean CRP values during the first 6 months of follow-up.
a
Fig. 3. Hazard ratios of CVD development by CKD and CRP status. Hazard ratios were adjusted by age (10-year increment), sex, CVD history, hypertension, diabetes, dyslipidemia, and smoking status. The CVD prevalence was significantly higher among subjects with CKD and a high CRP level, compared to the reference values (non-CKD, low CRP). CVD, cardiovascular disease; CKD, chronic kidney disease; CRP, C-reactive protein.
with low CRP status did not have a statistically significant influence on CVD incidence (HR, 1.88; 95% CI: 0.25–9.44; p = 0.49). Patients in the CKD with high CRP group had an approximately 10-fold higher risk of CVD relative to the reference group (HR, 9.71; 95% CI: 3.27– 31.97; p < 0.0001). Notably, the increased risk of CKD-associated CVD was only statistically prevalent among patients with high CRP levels. The CKD with high CRP group had a significantly higher HR for CVD development, compared with all other groups (p < 0.0001, p = 0.02, and p = 0.01 vs. the non-CKD with low CRP, non-CKD
with high CRP, and CKD with low CRP groups, respectively). However, no interaction was observed between CKD and a high CRP level (p = 0.67). As shown in Table 4, patients in the CKD with high CRP group exhibited higher prevalence rates of both cardiac and stroke events, compared with the other subgroups. Discussion In this study of patients with RA, we identified CKD as a significant risk factor for CVD development. Furthermore, patients
Table 4 CVD development according to CKD and CRP subgroups. Non-CKD with low CRP (n = 188) CVD, n (%) Cardiac events, n (%) Coronary heart disease, n (%) Congestive heart failure, n (%) Stroke Ischemic stroke, n (%) Hemorrhagic stroke, n (%)
6 4 3 1 2 0 2
(3.2) (2.1) (1.6) (0.5) (1.1) (0) (1.1)
Non-CKD with high CRP (n = 173) 18 (10.4) 10 (5.8) 8 (4.6) 2 (1.2) 8 (4.6) 5 (2.9) 3 (1.7)
CKD with low CRP (n = 26) 2 2 1 1 0 0 0
(7.8) (7.8) (3.9) (3.9) (0) (0) (0)
CKD with high CRP (n = 41) 12 (29.2) 8 (19.5) 7 (17.1) 1 (2.4) 4 (9.7) 3 (7.3) 1 (2.4)
CKD, chronic kidney disease; CRP, C-reactive protein; CVD, cardiovascular disease.
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with CKD and inflammation, as determined by CRP levels, faced a particularly high risk of CVD development. A few studies previously investigated the association between CKD and CVD in patients with RA [15,16,30]. Our observation of a higher incidence of CVD among patients with CKD aligned with the findings of those earlier studies. Although other mechanisms might contribute to this association, inflammation may play a critical role in the progression of CVD in RA patients with CKD. As in previous studies [31–33], patients with CKD in our study had higher CRP levels relative to those without CKD. Reports of patients with CKD have indicated an increase in the oxidative stress-induced production of inflammatory mediators [34], along with reduced urinary excretion of these products [35]. A previous study demonstrated positive, dose-dependent relationships of an elevated CRP level with blood pressure, glucose, and lipid levels, and body mass index among patients with CKD [33]. Accordingly, these confounding factors might influence the relationship between inflammation and higher risk of CVD in CKD patients. Alternatively, inflammation can promote atherosclerosis by inducing endothelial activation and dysfunction [36,37], and may therefore act as a non-traditional risk factor to direct the development of CVD in CKD patients [18–20]. Notably, the risk of CVD in CKD is further increased among patients with elevated CRP levels. A previous study demonstrated that an elevated CRP level was associated with an approximately two-fold increase in CV mortality among patients with CKD [20]. These findings suggest that the interaction between CKD and inflammation affects the risk of CVD among patients with RA. However, we did not observe a significant interaction between CKD and a high CRP level, suggesting that inflammation had a merely additive effect on the link between CKD and CVD development in patients with RA. Our findings were supported by a previous study in which both elevated CRP and CKD were predictive of CV events, but did not exert a synergistic effect in a community-based population [38]. Our findings may have important clinical implications. First, they suggest that an evaluation of traditional CV risk factors may be insufficient to determine the CVD risk among patients with RA. Rather, a simple evaluation of the CKD status, using measurements of both eGFR and proteinuria, could provide a more reliable stratification of the total CV risk. In particular, our findings emphasize that RA patients with CKD, if accompanied by chronically elevated CRP levels, have a greatly increased risk of experiencing a CV event in the subsequent 10-year period. Second, our results suggest that insufficient control of RA disease activity may induce CVD, particularly in patients with CKD, as the latter had a profound impact on CV events in patients with concomitantly elevated CRP levels. A previous large cohort study demonstrated that MTX use, in addition to good disease activity control, was significantly associated with a favorable CV outcome among patients with RA [39,40]. Therefore, strong RA disease activity control may improve the CV outcomes of patients, particularly those with CKD. In accordance with this hypothesis, a previous study reported that more strict RA control, mediated by intensive treatment, reduced the risk of incident CVD [41– 44]. Further prospective studies are warranted to address this important issue. This study had some limitations. First, we did not consider changes in various factors, including medication use, traditional risk factor control status, and RA disease activity, over the course of the study, and these undefined factors might have affected the results. However, the presence of CKD and a high CRP level predicted future CVD development, regardless of variations in patients’ clinical conditions. Second, our study was retrospective, and CV events were diagnosed based on medical records. Although we reviewed patients’ medical records and re-evaluated their
diagnostic accuracy, the incidence of CV events might have been underestimated; for example, CV events that required management at admission may have been omitted. The resulting underestimation might have complicated our analysis of the differences in CV event incidence between the groups. Third, we used only CRP as an inflammatory marker and did not have access to other data regarding other inflammatory markers (e.g. interleukin 6, tumor necrotizing factor-alpha). However, CRP is a commonly used biomarker of systemic inflammation and has been associated with an increased risk of CVD in patients with RA [22,23,45]. Fourth, the patient cohort comprised a relatively small number of patients from a single center in Japan. We therefore cannot exclude the possibility that our multivariate model was overfitted because of the small number of outcome events. Therefore, caution must be exercised when extrapolating our results, and large-scale, multicenter cohort studies are needed to confirm our findings. Conclusions Inflammation was associated with the heightened risk of CVD and the concomitant CKD further augmented the risk, although the sole effect of CKD on the risk of CVD was marginal. Therefore, inflammation might underlie much of the relationship between CKD and CVD in patients with RA. Further studies are warranted to evaluate the effects of therapies targeting CKD and inflammation on CV outcomes in patients with RA. Acknowledgments The authors are grateful to the nursing staff, medical assistant staff, nephrologists, and rheumatologists in Tomishiro Central Hospital. We are also grateful to the following doctors who gave invaluable advice and support: A. Higa and Y. Uezu. Funding There are no funding sources to be disclosed. Conflict of interest The authors declare that there is no conflict of interest. References [1] Meune C, Touzé E, Trinquart L, Allanore Y. Trends in cardiovascular mortality in patients with rheumatoid arthritis over 50 years: a systematic review and meta-analysis of cohort studies. Rheumatology (Oxford) 2009;48:1309–13. [2] Maradit-Kremers H, Nicola PJ, Crowson CS, Ballman KV, Gabriel SE. Cardiovascular death in rheumatoid arthritis: a population-based study. Arthritis Rheum 2005;52:722–32. [3] Lévy L, Fautrel B, Barnetche T, Schaeverbeke T. Incidence and risk of fatal myocardial infarction and stroke events in rheumatoid arthritis patients. A systematic review of the literature. Clin Exp Rheumatol 2008;26:673–9. [4] Solomon DH, Kremer J, Curtis JR, Hochberg MC, Reed G, Tsao P, Wang Y, Kang JP, Ning M, Wu JH, Ruan YF, Yu RH, Long DY, Tang RB, Sang CH, et al. Explaining the cardiovascular risk associated with rheumatoid arthritis: traditional risk factors versus markers of rheumatoid arthritis severity. Ann Rheum Dis 2010;69:1920–5. [5] Wen SN, Liu N, Li SN, Salim M, Yan Q, Wu XY, Wang Y, Kang JP, Ning M, Wu JH, Ruan YF, Yu RH, Long DY, Tang RB, Sang CH, et al. Catheter ablation of atrial fibrillation in patients with rheumatoid arthritis. J Cardiol 2015;66:320–5. [6] Aviña-Zubieta JA, Choi HK, Sadatsafavi M, Etminan M, Esdaile JM, Lacaille D. Risk of cardiovascular mortality in patients with rheumatoid arthritis: a metaanalysis of observational studies. Arthritis Rheum 2008;59:1690–7. [7] Peters MJ, van Halm VP, Voskuyl AE, Smulders YM, Boers M, Lems WF, Visser M, Stehouwer CD, Dekker JM, Nijpels G, Heine R, Dijkmans BA, Nurmohamed MT. Does rheumatoid arthritis equal diabetes mellitus as an independent risk factor for cardiovascular disease?. A prospective study. Arthritis Rheum 2009;61:1571–9. [8] Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296–305.
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