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Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study
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Original article
Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study Hein J.E.M. Janssens a,b,∗ , Paul G.J. Arts a , Bianca W.M. Schalk a , Marion C.J. Biermans a a b
Department of primary and community care, Radboud university medical center, PO Box 9101, Internal code 117, 6500 HB Nijmegen, The Netherlands Primary health care center Lobede, Lobith-Tolkamer, The Netherlands
a r t i c l e
i n f o
Article history: Accepted 23 December 2015 Available online xxx Keywords: Gout Rheumatoid arthritis Cardiovascular diseases Primary prevention Primary health care Cohort study
a b s t r a c t Objectives: To assess in one time window cardiovascular risks for both patients with gout and patients with rheumatoid arthritis in a Dutch primary care population. Methods: Retrospective matched cohort study with data from the electronic health records of 51 Dutch general practices. Participants were patients aged 30 years or older with an incident diagnosis of gout (n = 2655) or rheumatoid arthritis (n = 513), and matched non-disease controls (n = 7891 and n = 1850 respectively). At disease incidence date, patients and controls were compared for prevalence of hypertension, diabetes mellitus, hypercholesterolemia, and prior cardiovascular diseases. Patients without prior cardiovascular disease were followed for a first cardiovascular disease, and compared to controls using Kaplan-Meier survival curves and Cox proportional hazard analyses. Results: Compared to controls, gout patients suffered more from hypertension (44.8%), diabetes (20.1%), hypercholesterolemia (13.7%), and prior cardiovascular disease (30%) (P < 0.01), whereas rheumatoid arthritis patients (hypertension 28.5%; diabetes 11.7%; hypercholesterolemia 7.4%; prior cardiovascular disease 11.3%) did not (P > 0.05). After adjustment, both gout and rheumatoid arthritis patients without prior cardiovascular disease were more likely to get a cardiovascular disease: hazard ratio (95% confidence interval) 1.44 (1.18 to 1.76), and 2.06 (1.34 to 3.16) respectively. Conclusions: This primary care study indicates that gout and rheumatoid arthritis are both independent risk factors for cardiovascular diseases, rheumatoid arthritis to some greater extent, whereas gout patients at first diagnosis had already an increased cardiovascular risk profile. It gives strong arguments for implementation of both rheumatic diseases in primary care guidelines on cardiovascular risk management. © 2016 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
1. Introduction Cardiovascular diseases (CVDs) are the leading cause of death, with more than 17 million deaths per year, and a major cause of disability worldwide [1]. Therefore, case finding, screening and management of CVD needs continuous attention in daily medical practice. This applies particularly to primary health care, where patients at risk for CVD have easily access to physicians or other health workers who can manage these risks, in general or more specifically according to guidelines. Gout, an auto-inflammatory joint disease and also considered a systemic and metabolic disorder [2], has been linked to CVDs [2,3].
∗ Corresponding author. Department of primary and community care, Radboud university medical center, PO Box 9101, Internal code 117, 6500 HB Nijmegen, The Netherlands. E-mail address: [email protected] (H.J.E.M. Janssens).
It is the most prevalent inflammatory joint disease, with an estimated increasing prevalence of at least 1–2% in the general and 3–4% in the adult population [2,4]. Gout is a very painful disease characterized by joint redness, recurrent course, and involvement of the metatarso-phalangeal joint of the first toe as most affected site [2,5]. It is caused by intra-articular deposition of monosodium urate (MSU) crystals, which can be identified as the gold standard for the diagnosis by microscopic investigation of synovial fluid aspirated from the affected joint [5,6]. Despite its strong link with CVD, gout has hardly been implemented in general or specific primary care cardiovascular risk management (CVRM) as a factor to pay continuous attention to. As the severe pain will urge almost every gout patient to consult a physician and considering that ca. 90% of the patients with gout are managed in primary care [7], general practitioners (GPs) can easily identify without special efforts the vast majority of them for subsequent involvement in regular care [8]. Opposite to gout, rheumatoid arthritis (RA), another inflammatory but autoimmune systemic joint disease with a painful chronic
http://dx.doi.org/10.1016/j.jbspin.2015.12.003 1297-319X/© 2016 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
Please cite this article in press as: Janssens HJEM, et al. Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study. Joint Bone Spine (2016), http://dx.doi.org/10.1016/j.jbspin.2015.12.003
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course [9], which showed to be also a risk factor for CVDs [10–14], has already a certain established status in CVRM in primary and secondary care guidelines with a weight equally to diabetes [15]. However, despite this status, its independent association with CVD has not yet been confirmed in a primary care population. If gout turns out to be a substantial risk factor for CVD in a comparable degree to RA, implementing it in CVRM possibly with the same status as RA currently has, should be considered seriously. Gout with its high and increasing prevalence, much higher when compared to RA [16], implies absolutely many patients [4,17], and implementing it in CVRM might have in that case substantially beneficial impact on the total prevention of CVD and its burden for society [3]. This study aimed to assess the cardiovascular risk profile in primary care patients from the same population with an incident diagnosis of gout or RA, and the independent association of these rheumatic diseases with a first future CVD during one time window. 2. Methods 2.1. Design, setting and data source We designed a retrospective cohort study to assess the prevalence, the incidence and the independent risk of CVD in primary care patients aged over 30 years with gout or RA, by comparing them with matching controls. The study was conducted with data from the General Practitioner Database (GP Database) of the Department of Primary and Community Care at the Rafboud University Medical Center, Nijmegen. This database contains patients’ demographic, and GPs’ diagnosis and management information from electronic health records of general practices in the Eastern part of the Netherlands. All patients’ encounters are coded as diagnoses according to the International Classification of Primary Care (ICPC), expanded with the Dutch ICPC sub-codes [18]. These diagnoses provide a good indication of the health status of the Dutch general population, because almost all inhabitants in the Netherlands are registered with a general practice, with the GP acting as “gatekeeper” for referral to secondary health care. Practices were included if follow-up data from gout or RA patients were available during the study period from 1st January 2008 till 28 February 2014. Extracted data for this study were age, sex, practice, studied diseases, starting date of the disease, date of practice registration or deregistration, and date of death. 2.2. Patient and control selection Patients were selected for study inclusion if they had an ICPC code for gout (T92) or RA (L88 or L88.01) during the study period. At the incidence date of gout (start of the disease), i.e. the matched index date, a maximum of four controls without gout was included for each patient, matched for sex, age and practice. The same procedure was done to include controls for the RA patients, leading to two separate study groups, first a gout patient group with matched non-gout controls, and later, a RA patient group with matched nonRA controls. After that, we selected from these groups subjects who were free of prior CVD at the incidence or index date (baseline) for follow-up.
arterial disease (K92-92.01) and aortic aneurysm (K99-99.01). Hypertension (K86-87), diabetes mellitus (T90-90.02), and hypercholesterolemia (T93-93.01, T93.03), proven risk factors for CVD, were included as possibly confounding comorbidities. When the incidence date of an included disease was missing, it was set before the index date. 2.4. Statistical analysis Patients of the groups formed at the first step were compared with their respective non-disease controls for age, sex, presence of hypertension, diabetes, hypercholesterolemia, and prior CVD, using independent samples t-test for continuous variables and Chi2 analysis for categorical variables. The same comparisons were done for the subjects without prior CVD. For them, occurrence of any CVD (real end-point), practice deregistration, death by any cause or reaching end of follow-up (censored end-points) were assessed and crudely evaluated by Kaplan-Meier survival curves using log rank tests. Beside any CVD (pooled outcome), occurrence of separate CVDs was also assessed. For gout and RA patients, the crude incidence density rate (IDR) of CVD as pooled outcome was calculated by dividing the number of new cases of CVD in the first follow-up year by the sum of follow-up time of all patients during a 1-year period after index date, and expressed per 1000 patientyears with a 95% confidence interval (95% CI). Cox proportional analysis of the real end-point was performed with adjustment for age, sex, and comorbidities hypertension, diabetes, and hypercholesterolemia. All comorbidities recorded at the index date as well as during follow-up but before any end-point, were included. The results both for gout and RA were expressed as hazard ratios (HR) with 95% CI. Additional analyses were done for possible interactions of gout or RA with age, sex or comorbidities. In all analyses, statistical significance was set at a two-sided P-value ≤ 0.05. Analyses were performed using IBM SPSS Statistics version 20 as statistical package. 3. Results 3.1. Patients and characteristics As first step, 2655 patients with gout, 7891 non-gout controls, 513 RA patients, and 1850 non-RA controls were selected from 51 practices. Next, subjects with prior CVD were excluded, leaving 1859 gout patients with 6334 non-gout controls, and 455 RA patients with 1607 non-RA controls for follow-up. Gout patients without exclusion of prior CVD (Table 1) were mostly male (66.9%), whereas RA patients were mostly female (65.3%). Gout patients (mean age: 62.5 year; SD: 14.1) suffered more from hypertension (44.8%), diabetes (20.1%), hypercholesterolemia (13.7%) and prior CVD (30.0%) at the index date when compared with controls, while RA patients (mean age: 59.2 years;; SD: 14.8) did not (hypertension: 28.5%; diabetes: 11.7%; hypercholesterolemia: 7.4%; and prior CVD: 11.3%). Excluding patients with prior CVD (Table 2) did not change gender difference between gout and RA patients. Prevalence at the index date of hypertension (38.8%), diabetes (14.6%), and hypercholesterolemia (10.4%) was still higher in gout patients compared to their controls, which was, again, not seen in RA patients.
2.3. Outcome measures 3.2. Occurrence of CVD Outcomes were incidence dates of the first CVD, defined as diseases with an atherothrombotic pathophysiology, including angina pectoris (AP; K74-74.02), myocardial infarction (K75, K7676.02), heart failure (HF; K77-77.02), transient ischemic accident (K89), cerebral vascular accident (K90, K90.02-90.03), peripheral
After a mean follow-up time of 29.8 months (SD: 20.2), 8.3% of gout patients (n = 154) developed a first CVD, versus 5% non-gout controls (n = 318) after a mean time of 26.8 months (SD: 19.9). A percentage of 7.7 of RA patients (n = 35) developed a CVD versus
Please cite this article in press as: Janssens HJEM, et al. Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study. Joint Bone Spine (2016), http://dx.doi.org/10.1016/j.jbspin.2015.12.003
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Table 1 Characteristics of primary care patients with gout or RA and their controls, including individuals with cardiovascular diseases (CVD).
Sex Male Female Age (years) Mean ± SD Median (25p–75p) Comorbidities Hypertension Diabetes mellitus Hypercholesterolemia Prior CVDb Total Male Female
Gout (n = 2655)
Non-gout (n = 7891)
P-valuea
RA (n = 513)
Non-RA (n = 1850)
P-valuea
69.9 (1855) 30.1 (800)
65.3 (5153) 34.7 (2738)
< 0.01
34.7 (178) 65.3 (335)
36.3 (671) 63.7 (1179)
0.51
62.5 ± 14.1 63 (52–74)
61.6 ± 14.6 63 (50–73)
< 0.01
59.2 ± 14.8 59 (47–72)
58.4 ± 14.6 58 (47–70)
0.27
44.8 (1190) 20.1 (533) 13.7 (363)
26.0 (2052) 12.1 (952) 9.4 (743)
< 0.01 < 0.01 < 0.01
28.5 (146) 11.7 (60) 7.4 (38)
25.8 (478) 9.6 (178) 7.0 (130)
0.23 0.17 0.77
30.0 (796) 28.4 (526) 33.8 (270)
19.7 (1557) 20.4 (1050) 18.7 (5007)
< 0.01 < 0.01 < 0.01
11.3 (58) 15.7 (28) 9.0 (30)
13.1 (243) 16.5 (111) 11.2 (132)
0.27 0.80 0.24
Numbers are given as percentages, absolute numbers in parentheses, unless stated otherwise; RA: rheumatoid arthritis; prior CVD: CVD diagnosed before index date; SD: standard deviation; (p): percentile. CVD was defined as the presence of a disease code for angina pectoris, myocardial infarction, heart failure, transient ischemic accident (TIA), cerebral vascular accident (CVA), peripheral arterial disease, or aortic aneurysm. a Statistical significance: P-value ≤ 0.05. b Prior CVD: cardiovascular disease was diagnosed before the gout or RA index date.
Table 2 Primary care patients with gout or RA compared to controls without gout or RA, free of prior cardiovascular diseases (CVD) at diagnosis incidence or matched index date.
Sex Male Female Age (years) Mean ± SD Median (25p–75p) Comorbidities Hypertension Diabetes mellitus Hypercholesterolemia Occurrence of any CVD Total Male Female Occurrence of each individual CVDb Angina pectoris Myocardial infarction Heart failure TIA CVA PAD Aortic aneurysm
Gout (n = 1859)
Non-gout (n = 6334)
P-valuea
RA (n = 455)
Non-RA (n = 1607)
P-valuea
71.5 (1329) 28.5 (530)
64.8 (4103) 35.2 (2231)
< 0.01
33.0 (150) 67.0 (305)
34.8 (560) 65.2 (1047)
0.46
58.6 ± 13.5 59 (48–68)
58.9 ± 14.3 59 (48–70)
0.36
57.8 ± 14.7 57 (45–69)
56.5 ± 14.1 56 (45–67)
0.09
38.8 (722) 14.6 (271) 10.4 (193)
21.6 (1370) 9.3 (590) 7.1 (452)
< 0.01 < 0.01 < 0.01
25.9 (118) 9.2 (42) 6.2 (28)
22.8 (367) 8.5 (137) 6.0 (96)
0.17 0.64 0.89
8.3 (154) 8.2 (109) 8.5 (45)
5.0 (318) 4.7 (191) 5.7 (127)
< 0.01 < 0.01 0.02
7.7 (35) 6.7 (10) 8.2 (25)
3.4 (54) 4,1 (23) 3,0 (31)
< 0.01 0.19 < 0.01
1.0 (18) 2.0 (38) 1.7 (31) 0.8 (15) 1.6 (29) 1.5 (28) 0.9 (17)
0.8 (51) 1.2 (75) 0.9 (58) 0.7 (47) 1.0 (65) 0.6 (35) 0.4 (27)
0.50 < 0.01 < 0.01 0.78 0.06 < 0.01 0.01
0.9 (4) 1.5 (7) 1.3 (6) 1.5 (7) 2.0 (9) 0.7 (3) 0.4 (2)
0.8 (13) 0.9 (14) 0.6 (9) 0.6 (10) 0.7 (11) 0.4 (7) 0.5 (8)
0.88 0.21 0.09 0.06 0.01 0.54 0.88
Numbers are given as percentages, absolute numbers in parentheses, unless stated otherwise; RA: rheumatoid arthritis; CVD: cardiovascular diseases; SD: standard deviation; (p): percentile. CVD was defined as the presence of a disease code for angina pectoris, myocardial infarction, heart failure, transient ischemic accident (TIA), cerebral vascular accident (CVA), peripheral arterial disease (PAD), or aortic aneurysm. a Statistical significance: P-value ≤ 0.05. b The cumulated sum of various diseases defined as CVD is not necessarily equal to the pooled CVD occurrence, since one patient can develop more than one CVD.
3.4% of their controls (n = 54) after mean follow-up time of 32.6 (SD: 18.4) and 31.7 months (SD: 18.4), respectively. Frequencies of myocardial infarction, heart failure, peripheral arterial disease, and aortic aneurysm were significantly higher in gout patients than in controls. Angina pectoris and transient ischemic accident did not differ, whereas cerebral vascular accident reached near statistical significance (P = 0.06). Besides cerebral vascular accident (P = 0.01), none of the individual CVDs were more incident in RA patients when compared to their controls. The IDR per 1000 patient years of the first occurrence of a CVD was in gout patients 34.8 (95% CI: 27.0–44.9) with equal IDRs for men and women, and 31.3 (95% CI: 18.3–53.4) in RA patients, with a higher IDR for men (36.5; 95% CI: 16.2–90.1) than for women (28.1; 95% CI: 14.2–55.6). Patients (gout and RA) showed more decreasing Kaplan-Meier survival curves if
compared to their non-disease controls, with P-values of the log rank test < 0.001 (Fig. 1).
3.3. Cox proportional hazard analysis HR of CVD for gout was 1.49 (95% CI: 1.23–1.80), which remained statistically significant (HR 1.44; 95% CI: 1.18–1.76) after adjustment for age, sex and comorbidities (Table 3). There was a significant interaction (P = 0.038) between gout and age. Additional proportional hazard analysis (minus age) for the age groups “≤ 60 years” and “> 60 years” resulted in HRs of respectively 1.50 (95% CI: 1.02–2.20) and 1.23 (95% CI: 0.97–1.55). HR of CVD for RA was 2.22 (95% CI: 1.45–3.40), also still statistically significant
Please cite this article in press as: Janssens HJEM, et al. Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study. Joint Bone Spine (2016), http://dx.doi.org/10.1016/j.jbspin.2015.12.003
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Fig. 1. Kaplan-Meier curves of patients with gout or RA and their non-disease controls with survival till real or censored endpoints (both P-values of log rank test for curve differences < 0.001).
Table 3 The risk of a first cardiovascular disease (CVD) in primary care patients with gout or RA.
Hazard ratio (95% CI)a Unadjusted Adjustedb
Gout
RA
1.49 (1.23–1.80) 1.44 (1.18–1.76)
2.22 (1.45–3.40) 2.06 (1.34–3.16)
RA: rheumatoid arthritis; 95% CI: 95% confidence interval. CVD was defined as the presence of a disease code for angina pectoris, myocardial infarction, heart failure, transient ischemic accident (TIA), cerebral vascular accident (CVA), peripheral arterial disease, or aortic aneurysm. a For the Cox proportional hazard analysis, respective non-disease controls were used as reference. b Adjusted for age sex and comorbidities (hypertension, diabetes mellitus, hypercholesterolemia) when present at the index date or occurring during follow-up prior to any end-point.
after adjustment (HR 2.06; 95% CI: 1.34–3.16). For RA, no significant interactions were found. 4. Discussion This study shows a strong relationship between gout as well as RA and CVD, if both rheumatic diseases are studied simultaneously in one primary care population. We found that patients with gout had already an increased cardiovascular risk profile at the date of their incident diagnosis, as they suffered more often from hypertension, diabetes, hypercholesterolemia or prior CVD, if compared with matched controls, while RA patients did not. Both gout and RA patients without prior CVD had high CVD IDR, and the diseases were independently associated with future CVD, gout to some lesser extent (hazard ratio: 1.44) if compared to RA (hazard ratio: 2.06). In this study, subjects aged 60 years or younger might account mainly for the CVD risk in gout patients. This is, as far as we know, the first time that the cardiovascular significance of RA has been demonstrated in primary care, which provides evidence fortifying its already existing status in primary care CVRM. An essential advantage of our study was the primary health care setting, since gout patients are predominantly diagnosed and treated by GPs and RA patients at least monitored and followed by them because of high disease load or need for chronic care. This makes the results clinically relevant for a substantial group of patients. Both gout and RA were analyzed within the same population as well as in the same time window. As far as we know, this
has not been done before. It enables valid comparisons of the studied diseases, as it e.g. minimizes differences in diagnosis coding. We performed analyses for interactions and maximized correction for confounding by including hypertension, diabetes or hypercholesterolemia in the Cox proportional hazard analysis not only if these morbidities were present at the index date but also if they developed during follow-up. The GP database did not provide data of serum uric acid (an important diagnostic predictor for gout) or present MSU crystals (the gold standard for diagnosis), so classification of gout patients was based on a GP diagnosis. As misdiagnosis of gout by GPs can be substantial (turning mainly out to falsely positive diagnoses), it was possible that non-gout patients were included as gout patient [5]. This might have underestimated the found association of gout and CVD, as others showed a stronger association if the gout diagnosis was more valid, all the more if proved by the presence of MSU crystals [19,20]. We expect that the risk of RA misdiagnosis in our study was less when compared to gout, as even in primary care RA patients are much more characterized by their chronic care status and specific therapies, e.g. DMARDS [9]. Another limitation is the inability of our study to adjust for other possibly confounding variables, e.g. smoking, obesity, and renal function disorder [15] which were not recorded for all patients in the used database. However, minor impact of those variables could be expected, as other studies displayed a significant relation between gout or RA and individual CVDs even after correction for these variables [3,12,21,22]. In our previous study which had a case-control design (primary care patients with gout and controls, and CVD as a pooled outcome), we found no evidence of gout as an independent risk factor for CVD after correction for the same comorbidities plus obesity [8]. This might be due to lack of statistical power (170 patients, 340 controls). Another recent primary care study with a retrospective cohort design (8386 patients, 39,766 controls), which included only subjects aged over 50 years, has also found that gout is an independent risk factor for CVD, as we did in the present study with corresponding hazard ratios [23]. To our knowledge, our study is the first patient controlled study on CVD in primary care RA patients. In a secondary care study, IDR and hazard ratio of CVD (as pooled outcome) for RA are in the same range as we found [12]. In addition, results of more studies on the risk of future CVD in RA patients were not conflicting with our findings, but a proper comparison was difficult because of different outcome definitions [10,13]. In our gout patients without prior CVD myocardial infarction, heart failure, and peripheral arterial disease occurred more often,
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when compared to non-gout controls, and cerebral vascular accident reached near significance (P = 0.06), which is consistent with other findings [21–25]. However, some of them find higher angina pectoris incidence, whereas we did not [21,23]. We could not locate studies that focused on gout and aortic aneurysm. Our RA patients did not differ from their controls with respect to occurrence of the separate CVDs, whereas other studies found higher incidences of myocardial infarction and heart failure in them [10,11]. The higher prevalence of prior CVD, hypertension, diabetes, and hypercholesterolemia in all our gout patients at incidence date if compared to controls is in accordance with the findings of others [5,8,22] as well as with the known association of gout with the metabolic syndrome [26,27]. Prevalence of prior CVD, hypertension, diabetes, and hypercholesterolemia did not differ between RA patients and non-RA controls in our study. This was not always consistent with findings of other studies with various patient and control selections, even from different time windows [12,14]. 4.1. Mechanism There is persistent auto-inflammatory activity in the synovial fluid in gout patients, which is associated with vascular wall inflammation, atherosclerosis, and promotion of a prothrombogenic environment [28–31]. Persistent inflammation, but based on an autoimmune disorder, is described in RA patients as well as being the pathogenic mechanism of its link with CVD [32–34]. Hyperuricemia or pro-inflammatory cytokines associated e.g. with insulin resistance, metabolic syndrome or abdominal obesity could be risk factors next to persistent joint inflammation [2,35]. An additional factor hypothesized in the case of gout is the activity of xanthine oxidase, the breaking down enzyme to uric acid. Increased activity is suggested to induce production of reactive oxygen with endothelial damage and dysfunction, whereas inhibition of the enzyme improves endothelial dysfunction (e.g. in patients with the metabolic syndrome), leads to better cardiovascular outcomes [36–39] and is curative for gout [40]. Such additional mechanism could possibly explain the relatively high presence of prior CVD in gout patients, which was not seen in the RA patients in our study. In conclusion, this study shows that gout and RA are independent risk factors for CVD in the primary care patient population, RA to some greater extent, whereas at the incidence date of the diagnosis gout patients have already an increased cardiovascular risk profile. We advise to raise the awareness among GPs of the cardiovascular importance of both rheumatic diseases. The elevated risk among gout patients might be from an absolute point of view the most relevant one in primary care, because of the high disease prevalence, and the fact that ca. 90% of the patients is diagnosed and treated exclusively by GPs [7]. In conclusion, this study gives strong arguments for implementation of gout, next to RA, in primary care CVRM guidelines. Disclosure of interest The authors declare that they have no competing interest. All authors have completed the ICMJE uniform disclosure form at http://www.icmje.org/coi disclosure.pdf. Acknowledgements We wish to show our gratitude to all the general practitioners who were involved in collecting patient data for the GP-Database. We also want to thank Waling Tiersma for constructing the data sets and Hans Bor for patient and control selection, and for advising on statistical analyses. The presented research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.
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Original article
Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study Hein J.E.M. Janssens a,b,∗ , Paul G.J. Arts a , Bianca W.M. Schalk a , Marion C.J. Biermans a a b
Department of primary and community care, Radboud university medical center, PO Box 9101, Internal code 117, 6500 HB Nijmegen, The Netherlands Primary health care center Lobede, Lobith-Tolkamer, The Netherlands
a r t i c l e
i n f o
Article history: Accepted 23 December 2015 Available online xxx Keywords: Gout Rheumatoid arthritis Cardiovascular diseases Primary prevention Primary health care Cohort study
a b s t r a c t Objectives: To assess in one time window cardiovascular risks for both patients with gout and patients with rheumatoid arthritis in a Dutch primary care population. Methods: Retrospective matched cohort study with data from the electronic health records of 51 Dutch general practices. Participants were patients aged 30 years or older with an incident diagnosis of gout (n = 2655) or rheumatoid arthritis (n = 513), and matched non-disease controls (n = 7891 and n = 1850 respectively). At disease incidence date, patients and controls were compared for prevalence of hypertension, diabetes mellitus, hypercholesterolemia, and prior cardiovascular diseases. Patients without prior cardiovascular disease were followed for a first cardiovascular disease, and compared to controls using Kaplan-Meier survival curves and Cox proportional hazard analyses. Results: Compared to controls, gout patients suffered more from hypertension (44.8%), diabetes (20.1%), hypercholesterolemia (13.7%), and prior cardiovascular disease (30%) (P < 0.01), whereas rheumatoid arthritis patients (hypertension 28.5%; diabetes 11.7%; hypercholesterolemia 7.4%; prior cardiovascular disease 11.3%) did not (P > 0.05). After adjustment, both gout and rheumatoid arthritis patients without prior cardiovascular disease were more likely to get a cardiovascular disease: hazard ratio (95% confidence interval) 1.44 (1.18 to 1.76), and 2.06 (1.34 to 3.16) respectively. Conclusions: This primary care study indicates that gout and rheumatoid arthritis are both independent risk factors for cardiovascular diseases, rheumatoid arthritis to some greater extent, whereas gout patients at first diagnosis had already an increased cardiovascular risk profile. It gives strong arguments for implementation of both rheumatic diseases in primary care guidelines on cardiovascular risk management. © 2016 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
1. Introduction Cardiovascular diseases (CVDs) are the leading cause of death, with more than 17 million deaths per year, and a major cause of disability worldwide [1]. Therefore, case finding, screening and management of CVD needs continuous attention in daily medical practice. This applies particularly to primary health care, where patients at risk for CVD have easily access to physicians or other health workers who can manage these risks, in general or more specifically according to guidelines. Gout, an auto-inflammatory joint disease and also considered a systemic and metabolic disorder [2], has been linked to CVDs [2,3].
∗ Corresponding author. Department of primary and community care, Radboud university medical center, PO Box 9101, Internal code 117, 6500 HB Nijmegen, The Netherlands. E-mail address: [email protected] (H.J.E.M. Janssens).
It is the most prevalent inflammatory joint disease, with an estimated increasing prevalence of at least 1–2% in the general and 3–4% in the adult population [2,4]. Gout is a very painful disease characterized by joint redness, recurrent course, and involvement of the metatarso-phalangeal joint of the first toe as most affected site [2,5]. It is caused by intra-articular deposition of monosodium urate (MSU) crystals, which can be identified as the gold standard for the diagnosis by microscopic investigation of synovial fluid aspirated from the affected joint [5,6]. Despite its strong link with CVD, gout has hardly been implemented in general or specific primary care cardiovascular risk management (CVRM) as a factor to pay continuous attention to. As the severe pain will urge almost every gout patient to consult a physician and considering that ca. 90% of the patients with gout are managed in primary care [7], general practitioners (GPs) can easily identify without special efforts the vast majority of them for subsequent involvement in regular care [8]. Opposite to gout, rheumatoid arthritis (RA), another inflammatory but autoimmune systemic joint disease with a painful chronic
http://dx.doi.org/10.1016/j.jbspin.2015.12.003 1297-319X/© 2016 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
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course [9], which showed to be also a risk factor for CVDs [10–14], has already a certain established status in CVRM in primary and secondary care guidelines with a weight equally to diabetes [15]. However, despite this status, its independent association with CVD has not yet been confirmed in a primary care population. If gout turns out to be a substantial risk factor for CVD in a comparable degree to RA, implementing it in CVRM possibly with the same status as RA currently has, should be considered seriously. Gout with its high and increasing prevalence, much higher when compared to RA [16], implies absolutely many patients [4,17], and implementing it in CVRM might have in that case substantially beneficial impact on the total prevention of CVD and its burden for society [3]. This study aimed to assess the cardiovascular risk profile in primary care patients from the same population with an incident diagnosis of gout or RA, and the independent association of these rheumatic diseases with a first future CVD during one time window. 2. Methods 2.1. Design, setting and data source We designed a retrospective cohort study to assess the prevalence, the incidence and the independent risk of CVD in primary care patients aged over 30 years with gout or RA, by comparing them with matching controls. The study was conducted with data from the General Practitioner Database (GP Database) of the Department of Primary and Community Care at the Rafboud University Medical Center, Nijmegen. This database contains patients’ demographic, and GPs’ diagnosis and management information from electronic health records of general practices in the Eastern part of the Netherlands. All patients’ encounters are coded as diagnoses according to the International Classification of Primary Care (ICPC), expanded with the Dutch ICPC sub-codes [18]. These diagnoses provide a good indication of the health status of the Dutch general population, because almost all inhabitants in the Netherlands are registered with a general practice, with the GP acting as “gatekeeper” for referral to secondary health care. Practices were included if follow-up data from gout or RA patients were available during the study period from 1st January 2008 till 28 February 2014. Extracted data for this study were age, sex, practice, studied diseases, starting date of the disease, date of practice registration or deregistration, and date of death. 2.2. Patient and control selection Patients were selected for study inclusion if they had an ICPC code for gout (T92) or RA (L88 or L88.01) during the study period. At the incidence date of gout (start of the disease), i.e. the matched index date, a maximum of four controls without gout was included for each patient, matched for sex, age and practice. The same procedure was done to include controls for the RA patients, leading to two separate study groups, first a gout patient group with matched non-gout controls, and later, a RA patient group with matched nonRA controls. After that, we selected from these groups subjects who were free of prior CVD at the incidence or index date (baseline) for follow-up.
arterial disease (K92-92.01) and aortic aneurysm (K99-99.01). Hypertension (K86-87), diabetes mellitus (T90-90.02), and hypercholesterolemia (T93-93.01, T93.03), proven risk factors for CVD, were included as possibly confounding comorbidities. When the incidence date of an included disease was missing, it was set before the index date. 2.4. Statistical analysis Patients of the groups formed at the first step were compared with their respective non-disease controls for age, sex, presence of hypertension, diabetes, hypercholesterolemia, and prior CVD, using independent samples t-test for continuous variables and Chi2 analysis for categorical variables. The same comparisons were done for the subjects without prior CVD. For them, occurrence of any CVD (real end-point), practice deregistration, death by any cause or reaching end of follow-up (censored end-points) were assessed and crudely evaluated by Kaplan-Meier survival curves using log rank tests. Beside any CVD (pooled outcome), occurrence of separate CVDs was also assessed. For gout and RA patients, the crude incidence density rate (IDR) of CVD as pooled outcome was calculated by dividing the number of new cases of CVD in the first follow-up year by the sum of follow-up time of all patients during a 1-year period after index date, and expressed per 1000 patientyears with a 95% confidence interval (95% CI). Cox proportional analysis of the real end-point was performed with adjustment for age, sex, and comorbidities hypertension, diabetes, and hypercholesterolemia. All comorbidities recorded at the index date as well as during follow-up but before any end-point, were included. The results both for gout and RA were expressed as hazard ratios (HR) with 95% CI. Additional analyses were done for possible interactions of gout or RA with age, sex or comorbidities. In all analyses, statistical significance was set at a two-sided P-value ≤ 0.05. Analyses were performed using IBM SPSS Statistics version 20 as statistical package. 3. Results 3.1. Patients and characteristics As first step, 2655 patients with gout, 7891 non-gout controls, 513 RA patients, and 1850 non-RA controls were selected from 51 practices. Next, subjects with prior CVD were excluded, leaving 1859 gout patients with 6334 non-gout controls, and 455 RA patients with 1607 non-RA controls for follow-up. Gout patients without exclusion of prior CVD (Table 1) were mostly male (66.9%), whereas RA patients were mostly female (65.3%). Gout patients (mean age: 62.5 year; SD: 14.1) suffered more from hypertension (44.8%), diabetes (20.1%), hypercholesterolemia (13.7%) and prior CVD (30.0%) at the index date when compared with controls, while RA patients (mean age: 59.2 years;; SD: 14.8) did not (hypertension: 28.5%; diabetes: 11.7%; hypercholesterolemia: 7.4%; and prior CVD: 11.3%). Excluding patients with prior CVD (Table 2) did not change gender difference between gout and RA patients. Prevalence at the index date of hypertension (38.8%), diabetes (14.6%), and hypercholesterolemia (10.4%) was still higher in gout patients compared to their controls, which was, again, not seen in RA patients.
2.3. Outcome measures 3.2. Occurrence of CVD Outcomes were incidence dates of the first CVD, defined as diseases with an atherothrombotic pathophysiology, including angina pectoris (AP; K74-74.02), myocardial infarction (K75, K7676.02), heart failure (HF; K77-77.02), transient ischemic accident (K89), cerebral vascular accident (K90, K90.02-90.03), peripheral
After a mean follow-up time of 29.8 months (SD: 20.2), 8.3% of gout patients (n = 154) developed a first CVD, versus 5% non-gout controls (n = 318) after a mean time of 26.8 months (SD: 19.9). A percentage of 7.7 of RA patients (n = 35) developed a CVD versus
Please cite this article in press as: Janssens HJEM, et al. Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study. Joint Bone Spine (2016), http://dx.doi.org/10.1016/j.jbspin.2015.12.003
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Table 1 Characteristics of primary care patients with gout or RA and their controls, including individuals with cardiovascular diseases (CVD).
Sex Male Female Age (years) Mean ± SD Median (25p–75p) Comorbidities Hypertension Diabetes mellitus Hypercholesterolemia Prior CVDb Total Male Female
Gout (n = 2655)
Non-gout (n = 7891)
P-valuea
RA (n = 513)
Non-RA (n = 1850)
P-valuea
69.9 (1855) 30.1 (800)
65.3 (5153) 34.7 (2738)
< 0.01
34.7 (178) 65.3 (335)
36.3 (671) 63.7 (1179)
0.51
62.5 ± 14.1 63 (52–74)
61.6 ± 14.6 63 (50–73)
< 0.01
59.2 ± 14.8 59 (47–72)
58.4 ± 14.6 58 (47–70)
0.27
44.8 (1190) 20.1 (533) 13.7 (363)
26.0 (2052) 12.1 (952) 9.4 (743)
< 0.01 < 0.01 < 0.01
28.5 (146) 11.7 (60) 7.4 (38)
25.8 (478) 9.6 (178) 7.0 (130)
0.23 0.17 0.77
30.0 (796) 28.4 (526) 33.8 (270)
19.7 (1557) 20.4 (1050) 18.7 (5007)
< 0.01 < 0.01 < 0.01
11.3 (58) 15.7 (28) 9.0 (30)
13.1 (243) 16.5 (111) 11.2 (132)
0.27 0.80 0.24
Numbers are given as percentages, absolute numbers in parentheses, unless stated otherwise; RA: rheumatoid arthritis; prior CVD: CVD diagnosed before index date; SD: standard deviation; (p): percentile. CVD was defined as the presence of a disease code for angina pectoris, myocardial infarction, heart failure, transient ischemic accident (TIA), cerebral vascular accident (CVA), peripheral arterial disease, or aortic aneurysm. a Statistical significance: P-value ≤ 0.05. b Prior CVD: cardiovascular disease was diagnosed before the gout or RA index date.
Table 2 Primary care patients with gout or RA compared to controls without gout or RA, free of prior cardiovascular diseases (CVD) at diagnosis incidence or matched index date.
Sex Male Female Age (years) Mean ± SD Median (25p–75p) Comorbidities Hypertension Diabetes mellitus Hypercholesterolemia Occurrence of any CVD Total Male Female Occurrence of each individual CVDb Angina pectoris Myocardial infarction Heart failure TIA CVA PAD Aortic aneurysm
Gout (n = 1859)
Non-gout (n = 6334)
P-valuea
RA (n = 455)
Non-RA (n = 1607)
P-valuea
71.5 (1329) 28.5 (530)
64.8 (4103) 35.2 (2231)
< 0.01
33.0 (150) 67.0 (305)
34.8 (560) 65.2 (1047)
0.46
58.6 ± 13.5 59 (48–68)
58.9 ± 14.3 59 (48–70)
0.36
57.8 ± 14.7 57 (45–69)
56.5 ± 14.1 56 (45–67)
0.09
38.8 (722) 14.6 (271) 10.4 (193)
21.6 (1370) 9.3 (590) 7.1 (452)
< 0.01 < 0.01 < 0.01
25.9 (118) 9.2 (42) 6.2 (28)
22.8 (367) 8.5 (137) 6.0 (96)
0.17 0.64 0.89
8.3 (154) 8.2 (109) 8.5 (45)
5.0 (318) 4.7 (191) 5.7 (127)
< 0.01 < 0.01 0.02
7.7 (35) 6.7 (10) 8.2 (25)
3.4 (54) 4,1 (23) 3,0 (31)
< 0.01 0.19 < 0.01
1.0 (18) 2.0 (38) 1.7 (31) 0.8 (15) 1.6 (29) 1.5 (28) 0.9 (17)
0.8 (51) 1.2 (75) 0.9 (58) 0.7 (47) 1.0 (65) 0.6 (35) 0.4 (27)
0.50 < 0.01 < 0.01 0.78 0.06 < 0.01 0.01
0.9 (4) 1.5 (7) 1.3 (6) 1.5 (7) 2.0 (9) 0.7 (3) 0.4 (2)
0.8 (13) 0.9 (14) 0.6 (9) 0.6 (10) 0.7 (11) 0.4 (7) 0.5 (8)
0.88 0.21 0.09 0.06 0.01 0.54 0.88
Numbers are given as percentages, absolute numbers in parentheses, unless stated otherwise; RA: rheumatoid arthritis; CVD: cardiovascular diseases; SD: standard deviation; (p): percentile. CVD was defined as the presence of a disease code for angina pectoris, myocardial infarction, heart failure, transient ischemic accident (TIA), cerebral vascular accident (CVA), peripheral arterial disease (PAD), or aortic aneurysm. a Statistical significance: P-value ≤ 0.05. b The cumulated sum of various diseases defined as CVD is not necessarily equal to the pooled CVD occurrence, since one patient can develop more than one CVD.
3.4% of their controls (n = 54) after mean follow-up time of 32.6 (SD: 18.4) and 31.7 months (SD: 18.4), respectively. Frequencies of myocardial infarction, heart failure, peripheral arterial disease, and aortic aneurysm were significantly higher in gout patients than in controls. Angina pectoris and transient ischemic accident did not differ, whereas cerebral vascular accident reached near statistical significance (P = 0.06). Besides cerebral vascular accident (P = 0.01), none of the individual CVDs were more incident in RA patients when compared to their controls. The IDR per 1000 patient years of the first occurrence of a CVD was in gout patients 34.8 (95% CI: 27.0–44.9) with equal IDRs for men and women, and 31.3 (95% CI: 18.3–53.4) in RA patients, with a higher IDR for men (36.5; 95% CI: 16.2–90.1) than for women (28.1; 95% CI: 14.2–55.6). Patients (gout and RA) showed more decreasing Kaplan-Meier survival curves if
compared to their non-disease controls, with P-values of the log rank test < 0.001 (Fig. 1).
3.3. Cox proportional hazard analysis HR of CVD for gout was 1.49 (95% CI: 1.23–1.80), which remained statistically significant (HR 1.44; 95% CI: 1.18–1.76) after adjustment for age, sex and comorbidities (Table 3). There was a significant interaction (P = 0.038) between gout and age. Additional proportional hazard analysis (minus age) for the age groups “≤ 60 years” and “> 60 years” resulted in HRs of respectively 1.50 (95% CI: 1.02–2.20) and 1.23 (95% CI: 0.97–1.55). HR of CVD for RA was 2.22 (95% CI: 1.45–3.40), also still statistically significant
Please cite this article in press as: Janssens HJEM, et al. Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study. Joint Bone Spine (2016), http://dx.doi.org/10.1016/j.jbspin.2015.12.003
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Fig. 1. Kaplan-Meier curves of patients with gout or RA and their non-disease controls with survival till real or censored endpoints (both P-values of log rank test for curve differences < 0.001).
Table 3 The risk of a first cardiovascular disease (CVD) in primary care patients with gout or RA.
Hazard ratio (95% CI)a Unadjusted Adjustedb
Gout
RA
1.49 (1.23–1.80) 1.44 (1.18–1.76)
2.22 (1.45–3.40) 2.06 (1.34–3.16)
RA: rheumatoid arthritis; 95% CI: 95% confidence interval. CVD was defined as the presence of a disease code for angina pectoris, myocardial infarction, heart failure, transient ischemic accident (TIA), cerebral vascular accident (CVA), peripheral arterial disease, or aortic aneurysm. a For the Cox proportional hazard analysis, respective non-disease controls were used as reference. b Adjusted for age sex and comorbidities (hypertension, diabetes mellitus, hypercholesterolemia) when present at the index date or occurring during follow-up prior to any end-point.
after adjustment (HR 2.06; 95% CI: 1.34–3.16). For RA, no significant interactions were found. 4. Discussion This study shows a strong relationship between gout as well as RA and CVD, if both rheumatic diseases are studied simultaneously in one primary care population. We found that patients with gout had already an increased cardiovascular risk profile at the date of their incident diagnosis, as they suffered more often from hypertension, diabetes, hypercholesterolemia or prior CVD, if compared with matched controls, while RA patients did not. Both gout and RA patients without prior CVD had high CVD IDR, and the diseases were independently associated with future CVD, gout to some lesser extent (hazard ratio: 1.44) if compared to RA (hazard ratio: 2.06). In this study, subjects aged 60 years or younger might account mainly for the CVD risk in gout patients. This is, as far as we know, the first time that the cardiovascular significance of RA has been demonstrated in primary care, which provides evidence fortifying its already existing status in primary care CVRM. An essential advantage of our study was the primary health care setting, since gout patients are predominantly diagnosed and treated by GPs and RA patients at least monitored and followed by them because of high disease load or need for chronic care. This makes the results clinically relevant for a substantial group of patients. Both gout and RA were analyzed within the same population as well as in the same time window. As far as we know, this
has not been done before. It enables valid comparisons of the studied diseases, as it e.g. minimizes differences in diagnosis coding. We performed analyses for interactions and maximized correction for confounding by including hypertension, diabetes or hypercholesterolemia in the Cox proportional hazard analysis not only if these morbidities were present at the index date but also if they developed during follow-up. The GP database did not provide data of serum uric acid (an important diagnostic predictor for gout) or present MSU crystals (the gold standard for diagnosis), so classification of gout patients was based on a GP diagnosis. As misdiagnosis of gout by GPs can be substantial (turning mainly out to falsely positive diagnoses), it was possible that non-gout patients were included as gout patient [5]. This might have underestimated the found association of gout and CVD, as others showed a stronger association if the gout diagnosis was more valid, all the more if proved by the presence of MSU crystals [19,20]. We expect that the risk of RA misdiagnosis in our study was less when compared to gout, as even in primary care RA patients are much more characterized by their chronic care status and specific therapies, e.g. DMARDS [9]. Another limitation is the inability of our study to adjust for other possibly confounding variables, e.g. smoking, obesity, and renal function disorder [15] which were not recorded for all patients in the used database. However, minor impact of those variables could be expected, as other studies displayed a significant relation between gout or RA and individual CVDs even after correction for these variables [3,12,21,22]. In our previous study which had a case-control design (primary care patients with gout and controls, and CVD as a pooled outcome), we found no evidence of gout as an independent risk factor for CVD after correction for the same comorbidities plus obesity [8]. This might be due to lack of statistical power (170 patients, 340 controls). Another recent primary care study with a retrospective cohort design (8386 patients, 39,766 controls), which included only subjects aged over 50 years, has also found that gout is an independent risk factor for CVD, as we did in the present study with corresponding hazard ratios [23]. To our knowledge, our study is the first patient controlled study on CVD in primary care RA patients. In a secondary care study, IDR and hazard ratio of CVD (as pooled outcome) for RA are in the same range as we found [12]. In addition, results of more studies on the risk of future CVD in RA patients were not conflicting with our findings, but a proper comparison was difficult because of different outcome definitions [10,13]. In our gout patients without prior CVD myocardial infarction, heart failure, and peripheral arterial disease occurred more often,
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when compared to non-gout controls, and cerebral vascular accident reached near significance (P = 0.06), which is consistent with other findings [21–25]. However, some of them find higher angina pectoris incidence, whereas we did not [21,23]. We could not locate studies that focused on gout and aortic aneurysm. Our RA patients did not differ from their controls with respect to occurrence of the separate CVDs, whereas other studies found higher incidences of myocardial infarction and heart failure in them [10,11]. The higher prevalence of prior CVD, hypertension, diabetes, and hypercholesterolemia in all our gout patients at incidence date if compared to controls is in accordance with the findings of others [5,8,22] as well as with the known association of gout with the metabolic syndrome [26,27]. Prevalence of prior CVD, hypertension, diabetes, and hypercholesterolemia did not differ between RA patients and non-RA controls in our study. This was not always consistent with findings of other studies with various patient and control selections, even from different time windows [12,14]. 4.1. Mechanism There is persistent auto-inflammatory activity in the synovial fluid in gout patients, which is associated with vascular wall inflammation, atherosclerosis, and promotion of a prothrombogenic environment [28–31]. Persistent inflammation, but based on an autoimmune disorder, is described in RA patients as well as being the pathogenic mechanism of its link with CVD [32–34]. Hyperuricemia or pro-inflammatory cytokines associated e.g. with insulin resistance, metabolic syndrome or abdominal obesity could be risk factors next to persistent joint inflammation [2,35]. An additional factor hypothesized in the case of gout is the activity of xanthine oxidase, the breaking down enzyme to uric acid. Increased activity is suggested to induce production of reactive oxygen with endothelial damage and dysfunction, whereas inhibition of the enzyme improves endothelial dysfunction (e.g. in patients with the metabolic syndrome), leads to better cardiovascular outcomes [36–39] and is curative for gout [40]. Such additional mechanism could possibly explain the relatively high presence of prior CVD in gout patients, which was not seen in the RA patients in our study. In conclusion, this study shows that gout and RA are independent risk factors for CVD in the primary care patient population, RA to some greater extent, whereas at the incidence date of the diagnosis gout patients have already an increased cardiovascular risk profile. We advise to raise the awareness among GPs of the cardiovascular importance of both rheumatic diseases. The elevated risk among gout patients might be from an absolute point of view the most relevant one in primary care, because of the high disease prevalence, and the fact that ca. 90% of the patients is diagnosed and treated exclusively by GPs [7]. In conclusion, this study gives strong arguments for implementation of gout, next to RA, in primary care CVRM guidelines. Disclosure of interest The authors declare that they have no competing interest. All authors have completed the ICMJE uniform disclosure form at http://www.icmje.org/coi disclosure.pdf. Acknowledgements We wish to show our gratitude to all the general practitioners who were involved in collecting patient data for the GP-Database. We also want to thank Waling Tiersma for constructing the data sets and Hans Bor for patient and control selection, and for advising on statistical analyses. The presented research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.
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Please cite this article in press as: Janssens HJEM, et al. Gout and rheumatoid arthritis, both to keep in mind in cardiovascular risk management: A primary care retrospective cohort study. Joint Bone Spine (2016), http://dx.doi.org/10.1016/j.jbspin.2015.12.003