Abstract
Objective. Previously thought to involve primarily the microvasculature, systemic sclerosis (SSc) has been increasingly linked to macrovascular disease. Cardiovascular (CV) and cerebrovascular disease are responsible for 20–30% of mortality in SSc, but few studies have shown an independent association between SSc and stroke. We assessed whether SSc was an independent risk factor for ischemic stroke.
Methods. We conducted a retrospective cohort study using the national Veterans Affairs (VA) administrative database containing records from 1999 to 2014. We obtained data for all patients with a diagnosis of SSc as well as 2 controls per SSc patient matched on sex, race, smoking status, and VA site. All patients were followed until development of ischemic stroke, death, or last encounter. We used a Cox proportional hazard regression model to estimate risk of ischemic stroke, with adjustments for CV comorbidities (hypertension, diabetes, atrial fibrillation, non-cerebrovascular atherosclerotic disease, hyperlipidemia), baseline medication use (aspirin, nonsteroidal antiinflammatory drugs), and Medicare enrollment.
Results. Among 4545 individuals with SSc (83% male, mean age 60.9 yrs), the incidence rate of ischemic stroke was 15.3 per 1000 person-years (vs 12.2 in the control cohort), with an unadjusted HR 1.28 (95% CI 1.11–1.47). The adjusted HR was 1.21 (95% CI 1.05–1.40) after adjusting for baseline CV risk factors, medications, and Medicare enrollment.
Conclusion. SSc is independently associated with a higher risk of ischemic stroke among US veterans. Patients with SSc represent a population likely to benefit from targeted stroke screening or prevention therapies.
Systemic sclerosis (SSc; or scleroderma) is a rare multisystem autoimmune disease characterized by collagen deposition in the skin and internal organs as well as endothelial damage leading to vasculopathy. Vascular manifestations, including Raynaud phenomenon, digital ischemia, pulmonary arterial hypertension, and scleroderma renal crisis are the consequences of endothelial injury and obliteration of the microvascular lumen1,2. Although previously thought to be primarily a disease of microvasculature, SSc has been increasingly linked to macrovascular disease in the form of coronary and cerebrovascular disease3,4. Owing to improvement in the treatment of many end-organ manifestations of SSc such as scleroderma renal crisis and pulmonary hypertension, atherosclerotic diseases are now responsible for 20–30% of mortality in SSc3.
Several studies have associated SSc with increased risk of atherosclerotic disease as evidenced by both physiologic measurements of atherosclerosis such as carotid intima-media thickness (IMT)5,6 and population-based studies outside of the United States7,8,9,10,11,12. Three matched cohort studies have demonstrated an increased risk of ischemic stroke in SSc7,8,11, but the studies were relatively small (< 100 ischemic strokes among SSc patients). It is unclear whether any association between SSc and atherosclerotic disease would persist in a US population enriched for traditional atherosclerotic risk factors including male sex.
As the largest healthcare system in the United States, providing care to over 5 million veterans nationwide, the Veterans Affairs (VA) Health System provides a unique opportunity to evaluate the prevalence and risk factors associated with developing cerebrovascular disease in individuals with SSc. We examined the risk of developing ischemic stroke in individuals with SSc among a large cohort of US veterans.
MATERIALS AND METHODS
This study was approved by the San Francisco VA Medical Center and University of California, San Francisco internal review boards (#16-21058); waiver of informed consent was granted because of the features of the study.
Data source
The VA Corporate Data Warehouse contains data elements extracted from the national VA electronic medical record such as outpatient and inpatient use with associated diagnostic and procedure codes, laboratory results, and pharmacy data. Data were accessed through the VA Informatics and Computing Infrastructure (VINCI) platform13. We conducted a retrospective cohort study to determine whether SSc disease status (exposure) is associated with ischemic stroke (outcome). Our study included all patient data from October 1, 1999, to September 30, 2014.
Inclusion and exclusion criteria
We included patients with both prevalent and incident SSc. Cases were required to have at least 1 encounter with an associated International Classification of Diseases, 9th revision (ICD-9) diagnosis code of 710.1. Although there are currently no widely accepted administrative case definitions of SSc, diagnostic codes from administrative data have been previously demonstrated to have a specificity of 94.9% for SSc, when compared to chart review14.
Patients were excluded before matching if they were < 18 years of age at the time of their first encounter, or had an ICD-9 diagnosis code for morphea (701.0), eosinophilic fasciitis (728.89), or nephrogenic systemic fibrosis (710.8), which are known clinical mimics of SSc and likely indicate misdiagnosis of SSc and/or inaccurate coding15 (1602 cases). Cases with a diagnosis of ischemic stroke or transient ischemic attack (TIA) prior to their reference date (327 cases) and those with only 1 encounter (141 cases) were excluded prior to matching.
Matching
Two controls were matched to each case using a nearest neighbor matching algorithm without replacement, using a Mahalanobis distance metric for date of birth and duration of VA enrollment, defined as the time interval between first and last encounter. Exact matching was performed for categorical variables (sex, race, baseline smoking status, VA site). If patients received care at multiple VA sites, the site with the plurality of encounters was chosen.
The reference date for cases was defined as the earliest encounter with an SSc diagnosis code. The reference date for controls was determined after they were matched to a case, by computing the time interval between the first encounter and reference date for the respective case, and adding that interval to the date of first encounter of the control. The goal of this procedure was to match cases and controls on the amount of time they had to accumulate comorbid conditions after they started receiving care through the VA (Figure 1).
The enrollment date for cases and controls was defined as the date of the first diagnosis code of any kind. For cases, the reference date was defined as the date of the first encounter associated with a diagnosis code for SSc. For the controls, the reference date was calculated as the enrollment date plus the comorbidity accumulation time of the matched case, defined as the interval between enrollment date and reference date. The censoring date was the date of first CVA/TIA diagnosis, date of death, or date of most recent diagnosis of any kind, whichever came first. CVA: cerebrovascular accident; SSc: systemic sclerosis; TIA: transient ischemic attack.
To reduce bias from potentially matching patients receiving care at vastly different timepoints, we divided the 15-year study period into 5-year periods, and controls were required to have at least 1 encounter during the 5-year period of the reference date of their respective cases. This approach was adapted from a previously published matched cohort study16.
Both cases and controls for any matched set in which any control had an invalid reference date (prior stroke diagnosis or before enrollment date) were excluded after matching (153 cases), owing to the calculation of control reference date after matching. Two cycles of matching were performed to reduce the number of controls with invalid reference dates. The subject selection process is shown in Figure 2.
Study subject selection process. CVA: cerebrovascular accident; SSc: systemic sclerosis; TIA: transient ischemic attack.
Definition of ischemic stroke
We identified the first encounter for each patient associated with an ICD-9 code that corresponded to cerebrovascular ischemia (433.x1, 434.x1, 435.x, 436, 437.1), including codes for TIA. Identifying strokes using algorithms involving ICD-9 codes has been previously performed using VA data17. Positive predictive values for the selected stroke ICD-9 codes were generally found to be > 75% in a metaanalysis18. Patients were followed from date of SSc diagnosis (cases) or matched reference date (controls) until the first diagnosis of ischemic stroke, death, or last encounter, whichever came first.
Assessment of covariates
Baseline traditional cardiovascular (CV) risk factors [atrial fibrillation, hypertension (HTN), diabetes mellitus, noncerebrovascular atherosclerotic disease, hyperlipidemia) were assessed during the period between the first encounter and the reference date based on the presence of relevant diagnostic codes. Any previous statin use was also incorporated into the definition of hyperlipidemia. Smoking status at baseline (yes, no, unknown) was assessed using health factors data collected by providers in the VA electronic medical record using automated clinical reminders, a method that has been validated in comparison to patient questionnaires19. Baseline medication use [aspirin, oral nonsteroidal antiinflammatory drugs (NSAID)] was defined as a filled prescription and/or recorded non-VA medication in the 12 months prior to the start of followup.
To account for potential differences between cases and controls due to differential patterns of healthcare use, we also measured Medicare enrollment as a proxy for non-VA care. More than half of all veterans report enrollment in Medicare, and these patients likely receive care through both VA and non-VA sources20. Yearly Medicare enrollment records were extracted from Centers for Medicare and Medicaid Services data provided to the VA, and patients were considered enrolled in Medicare if they were enrolled for at least 1 year during their followup. Patients with unavailable Medicare enrollment data were considered to have not been enrolled (n = 6).
Statistical analyses
We compared cases and controls on the basis of nonmatched characteristics, using chi-square tests for categorical variables and t tests for continuous variables. The number of cases and controls with ischemic stroke during followup and total person-years (PY) of followup were used to estimate incidence rates. To generate HR, we used a Cox proportional hazard regression model stratified by matched sets of patients. Tests of collinearity and evaluation of the proportional hazards assumption were performed. Multivariable analyses were adjusted for baseline traditional CV risk factors (atrial fibrillation, HTN, diabetes mellitus, non-cerebrovascular atherosclerotic disease, hyperlipidemia), baseline medication use (aspirin, NSAID, statins), and Medicare enrollment during followup. Extraction of data was performed using Microsoft SQL Server 2014 (Microsoft Corp.). Statistical analysis was performed with STATA/MP 15.1 (StataCorp).
Sensitivity analyses
We performed 5 sensitivity analyses. First, a separate analysis was performed using only cases who were given an SSc diagnosis code during an outpatient rheumatology encounter. We hypothesized that these cases would be more likely to have accurate diagnoses of SSc, based on a chart review of all SSc cases diagnosed at the San Francisco VA that showed this criterion to be the most accurate in distinguishing true diagnoses of SSc. Second, we restricted the SSc cohort to those with at least 2 SSc diagnosis codes separated by at least 30 days. Third, we excluded patients from both cohorts with any diagnoses of rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE), as both diseases increase risk of stroke21 and may be misdiagnosed as SSc. Finally, the last 2 sensitivity analyses were performed using Medicare enrollment data to ensure that missing diagnoses from non-VA care were not significantly affecting our results. We analyzed a subset of patients first with additional censoring at the time of the first year of Medicare enrollment, and separately by excluding all patients enrolled in Medicare during followup. These 2 analyses were necessarily unstratified owing to the removal of patients who became censored or excluded before their reference date.
RESULTS
We included 4545 cases and 9090 matched controls in our primary analysis. Baseline patient characteristics are shown in Table 1. Both cases and controls were predominantly male (83%) and white (60%), with an average age of 61 years at reference date. Patients with SSc generally had higher baseline rates of CV risk factors, higher rates of baseline aspirin and NSAID use, and were more likely to be enrolled in Medicare during followup (p < 0.001). The mean reference date was in calendar year 2006, and the mean interval between first VA encounter and reference date was 3.7 years for both groups.
Baseline characteristics of systemic sclerosis (SSc) and matched controls (non-SSc).
The mean followup duration was 5.1 years for patients with SSc and 5.2 years for controls. New diagnoses of ischemic stroke or TIA occurred in 353 patients with SSc over 23,078 PY of followup (15.3/1000 PY), and 574 controls over 47,175 PY of followup (12.2/1000 PY; Table 2). There was a significantly higher incidence of ischemic events among patients with SSc (p = 0.0004), diverging early in the followup period (Figure 3).
Cumulative incidence of ischemic stroke or transient ischemic attack in 4545 individuals with systemic sclerosis (SSc) as compared with 9090 non-SSc individuals matched for age, sex, race, VA facility, and smoking status.
HR of incident stroke or TIA according to systemic sclerosis (SSc) status.
The unadjusted HR for cerebrovascular ischemic events in patients with SSc was 1.28 (95% CI 1.11–1.47; Table 2). After adjusting for baseline CV risk factors, medication use, and Medicare enrollment during followup, the HR was 1.21 (95% CI 1.05–1.40). HR remained consistent for all sensitivity analyses. Limiting cases to the 1538 patients with SSc diagnosed during an outpatient rheumatology encounter resulted in an unadjusted HR of 1.49 (95% CI 1.14–1.95) and adjusted HR of 1.48 (95% CI 1.10–1.99). Requiring 2 SSc diagnosis codes resulted in an unadjusted HR of 1.33 (95% CI 1.09–1.62) and adjusted HR of 1.33 (95% CI 1.07–1.64) among 2201 cases and 4402 controls. After excluding patients with diagnoses of RA or SLE, there were 3471 cases and 6942 controls, with an unadjusted HR of 1.18 (95% CI 1.00–1.39) and adjusted HR of 1.14 (95% CI 0.96–1.36). Censoring at time of Medicare enrollment resulted in an unadjusted HR of 1.51 (95% CI 1.22–1.87) and adjusted HR of 1.31 (95% CI 1.05–1.62) among 2020 cases and 4601 controls. Excluding all patients enrolled in Medicare during followup resulted in an unadjusted HR of 1.64 (95% CI 1.26–2.11) and adjusted HR of 1.37 (95% CI 1.05–1.78) among 1142 cases and 2942 controls.
DISCUSSION
In this cohort of US veterans, the risk of incident stroke or TIA was 20–30% higher in individuals with SSc compared to matched controls. While this effect was somewhat attenuated after adjustment for known stroke risk factors and baseline medication use, it remained statistically significant. As the first study of SSc in a predominantly male US veteran population, to our knowledge, this provides evidence that SSc is associated with additional risk of developing ischemic stroke in US veterans, a population with a significant burden of traditional stroke risk factors. The current study contains the largest cohort of patients with SSc to date in which macrovascular disease has been assessed. Our cohort size is within an order of magnitude of the estimated prevalence of SSc in the VA healthcare system (1400–2900), based on previously published estimates of SSc prevalence in the United States22,23 and the number of veterans receiving VA care24. However, it must be noted that the veteran population differs in many ways from the general population, including with various occupational and military exposures during military service that may increase the risk of autoimmune conditions25.
There are several possible mechanisms for macrovascular disease in SSc. Endothelial dysfunction is a hallmark of SSc and leads to a characteristic vasculopathy consisting of both proliferative obliterative and destructive features26. Production of reactive oxygen species can be caused by endothelial dysfunction and vascular inflammation, which leads to oxidation of low-density lipoprotein and eventually formation of atherosclerotic plaques27. Cerebral vasospasm as evidenced by angiography is another posited mechanism of cerebrovascular disease in SSc28.
Prior studies have found an increased prevalence of subclinical cerebrovascular atherosclerotic disease in SSc through measures such as carotid IMT on ultrasound, intracerebral calcifications on computed tomography, and white-matter hyperintensities on magnetic resonance imaging5. Previous cohort studies have found increased risk of clinical coronary artery disease7,9,10 and stroke7,8 in patients with SSc compared to controls, in agreement with our findings. Chiang, et al reported a roughly 40% increased risk of ischemic stroke or TIA in a Taiwanese SSc cohort8, and both Man, et al and Aviña-Zubieta, et al found a 2- to 3-fold increased risk of ischemic stroke (not including TIA) in British and Canadian SSc cohorts, respectively7,11. Compared to these previous studies, our study population was older, predominantly male, and had higher rates of CV risk factors such as HTN, diabetes, and atrial fibrillation, as would be expected in a veteran population, making comparisons to other cohort studies difficult. As the first study to investigate the risk of stroke in SSc in both a US population and a predominantly male cohort, we found lower HR compared to previous cohort studies, but this may be explained by the higher burden of atherosclerotic risk factors in our cohort that may blunt the additive risk of SSc.
The prevalence of traditional CV risk factors in our study was significantly higher in the cases than controls, in contrast to data from a matched retrospective cohort study that showed similar baseline rates of HTN, diabetes, hyperlipidemia, and atrial fibrillation between patients with SSc and controls7. This finding may suggest that SSc in males and/or veterans is more closely associated with CV risk factors than in the general SSc population, or it may reflect a higher degree of diagnostic delay of SSc, because several of these CV comorbidities are potential complications of SSc or its treatment. Men in a European SSc cohort were found to have higher rates of pulmonary hypertension, heart failure, and all-cause mortality compared to women29, although macrovascular disease was not specifically studied. This might also be an artifact arising from our use of administrative data, because patients diagnosed with a serious and complex condition such as SSc may be more likely to receive comorbid diagnoses around the time of diagnosis as a result of increased contacts with the healthcare system22. We attempted to account for this using an algorithm that matched on comorbidity accumulation time, although it is possible that some residual confounding remained.
The strengths of our study include the use of a nationwide administrative database to follow a large number of patients with a rare disease over a sufficiently long time to detect cerebrovascular events. As the first study of SSc in US veterans, to our knowledge, we have demonstrated the value of studying a female-predominant disease in a male-predominant veteran population. We have also described a novel matching process to generate reference dates in controls while also matching for comorbidity accumulation time.
Limitations of our study include uncertainty about diagnostic accuracy, as with all studies using administrative data. Classification of ischemic stroke as well as atrial fibrillation, diabetes, and HTN by ICD-9 codes were shown to have an 85–90% positive predictive value when compared to chart review30. To minimize the effect of potential misclassification of SSc, we excluded all patients who had a diagnosis of one or more SSc mimics, in addition to performing a sensitivity analysis using only patients with SSc diagnosed during a rheumatology outpatient encounter. Based on our chart review, this more specific definition of SSc is more likely to record correct diagnoses of SSc, at the expense of excluding patients with poor access to specialty care. Our sensitivity analysis excluding patients with RA and SLE diagnoses resulted in a nonsignificant HR after adjustment, but this analysis likely excluded valid SSc cases who received an alternate diagnosis of RA or SLE near the time of their initial SSc diagnosis during a period of diagnostic uncertainty, or truly had an overlap syndrome.
With many patients in our cohort being enrolled in Medicare and thus likely receiving non-VA care, there is also the risk of missing stroke diagnoses that occurred outside of the VA. However, the overall effect of this missing data should generally bias our results toward the null, as more cases than controls were enrolled in Medicare. We did not have access to data such as SSc subtype, organ involvement, or disease severity, nor stroke severity. We attempted to analyze 30-day mortality after stroke events but were limited by small sample sizes. Medication data for aspirin and NSAID use may be underascertained because of frequent over-the-counter purchase of these medications31, which is not always recorded by provider-entered non-VA medication fields32; however, we would not expect this underascertainment to be differential among cases and controls. Although we collected data on baseline oral glucocorticoid use, we did not incorporate this variable into our model owing to concern that baseline glucocorticoid use reflected a subset of SSc patients with manifestations such as arthritis that preceded a formal diagnosis of SSc.
Our study provides evidence that SSc is associated with an increased risk of cerebrovascular disease in the US veteran population, independent of traditional CV risk factors. Future work should focus on identifying mechanisms and risk factors for cerebrovascular disease in SSc, such as disease subtype or disease manifestations such as vasculopathy, hypercoagulability, and vasospasm. Further, our findings suggest that patients with SSc in the US veteran population may benefit from targeted stroke screening or prevention strategies.
Acknowledgment
We thank Stephen Shiboski for assistance with statistical analysis. We are also grateful to Andrew Quartin, Giancarlo Diaz-Zamora, and Kristin Haffizulla for their contributions to this project.
Footnotes
This study was funded by the US Department of Veterans Affairs Merit Review grant (EG), the National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIH/NIAMS) K23 AR063770 (GS), and NIH/NIAMS P30 AR070155 (JY). This project was also supported by the National Center for Advancing Translational Sciences, NIH, through the University of California, San Francisco Clinical and Translational Science Institute (UCSF-CTSI grant number UL1 TR001872), and the Rosalind Russell/Ephraim Engleman Rheumatology Research Center. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the NIH, the Department of Veterans Affairs, or the US government.
- Accepted for publication February 27, 2019.
REFERENCES
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