With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study ...designs because it captures almost the complete variety of patients, leading to more generalisable results. For rheumatology, these data are particularly interesting as our diseases are uncommon and often take years to develop. In this review, we discuss the following concepts related to the use of EHR for research and considerations for translation into clinical care: EHR data contain a broad collection of healthcare data covering the multitude of real-life patients and the healthcare processes related to their care. Machine learning (ML) is a powerful method that allows us to leverage a large amount of heterogeneous clinical data for clinical algorithms, but requires extensive training, testing, and validation. Patterns discovered in EHR data using ML are applicable to real life settings, however, are also prone to capturing the local EHR structure and limiting generalisability outside the EHR(s) from which they were developed. Population studies on EHR necessitates knowledge on the factors influencing the data available in the EHR to circumvent biases, for example, access to medical care, insurance status. In summary, EHR data represent a rapidly growing and key resource for real-world studies. However, transforming RWD EHR data for research and for real-world evidence using ML requires knowledge of the EHR system and their differences from existing observational data to ensure that studies incorporate rigorous methods that acknowledge or address factors such as access to care, noise in the data, missingness and indication bias.
Abstract The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is 1.5–2-fold higher than age- and sex-matched individuals from the general population. This excess risk ...is attributed to the systemic chronic inflammation which is a hallmark of RA. Challenges to optimizing CV risk management in RA include the need for improved methods to predict CV risk, and defining the target risk factor(s) to reduce CV risk. Lessons learned from RA studies can also inform CV risk prevention in the general population, where inflammation also has an important role in the pathogenesis of atherosclerosis.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Rheumatoid arthritis and cardiovascular disease Crowson, Cynthia S., MS; Liao, Katherine P., MD, MPH; Davis, John M., MD ...
The American heart journal,
10/2013, Volume:
166, Issue:
4
Journal Article
Peer reviewed
Open access
Background Rheumatic disease and heart disease share common underpinnings involving inflammation. The high levels of inflammation that characterize rheumatic diseases provide a “natural experiment” ...to help elucidate the mechanisms by which inflammation accelerates heart disease. Rheumatoid arthritis (RA) is the most common of the rheumatic diseases and has the best studied relationships with heart disease. Methods A review of current literature on heart disease and RA was conducted. Results Patients with RA have an increased risk of developing heart disease that is not fully explained by traditional cardiovascular risk factors. Therapies used to treat RA may also affect the development of heart disease; by suppressing inflammation, they may also reduce the risk of heart disease. However, their other effects, as in the case of steroids, may increase heart disease risk. Conclusions Investigations of the innate and adaptive immune responses occurring in RA may delineate novel mechanisms in the pathogenesis of heart disease and help identify novel therapeutic targets for the prevention and treatment of heart disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Systemic auto-immune inflammatory arthritides are associated with increased cardiovascular (CV) risk compared to those without these conditions, and is a leading cause of morbidity and mortality. ...Newer biologic drug modifying antirheumatoid drugs (bDMARD) and small molecules have transformed treatment paradigms enabling tighter control of disease activity and in some cases, remission. There is evidence to suggest that the majority of bDMARDs may also reduce cardiovascular risk, although prospective interventional data remain sparse. Additionally, recent results raise concern for treatments targeting specific pathways that may negatively affect cardiovascular risk. This review will cover key biologic pathways targeted in rheumatoid arthritis, psoriatic arthritis, and spondyloarthropathies.
Multiple studies demonstrate an increased cardiovascular (CV) risk associated with RA compared with the general population. While part of this risk appears to be mediated by RA-specific factors, such ...as long-term inflammation, traditional CV comorbidities also play an important role. We review evidence from previous studies of the relationship between RA and traditional CV comorbidities such as dyslipidaemia, obesity, insulin resistance and diabetes, hypertension, cigarette smoking and physical inactivity. We examine the prevalence and consider the effect of inflammation and RA treatments on these risk factors. Finally, we discuss three widely used CV risk estimators, the Framingham Risk Score, Reynolds Risk Score and the Systematic Coronary Risk Evaluation, and their performance in patients with RA. The traditional CV risk factors that appear to differ significantly between RA cases and controls include insulin resistance, abnormal fat distribution, cigarette smoking and lack of physical activity. Dyslipidaemia, diabetes and hypertension may also be elevated in RA; however, the evidence is conflicting. Overall, we found that the majority of information regarding CV risk factors in RA stems from data collected as covariates for studies on CV disease. A gap in knowledge exists regarding detailed information on individual risk factors in RA, their prevalence and modifications that occur as a result of inflammation or treatment. More studies are needed to develop methods for accurate CV risk estimation in RA.
The association between chronic inflammation and increased risk of cardiovascular disease in rheumatoid arthritis (RA) is well established. In the general population, inflammation is an established ...independent risk factor for cardiovascular disease, and much interest is placed on controlling inflammation to reduce cardiovascular events. As inflammation encompasses numerous pathways, the development of targeted therapies in RA provides an opportunity to understand the downstream effect of inhibiting specific pathways on cardiovascular risk. Data from these studies can inform cardiovascular risk management in patients with RA, and in the general population. This Review focuses on pro-inflammatory pathways targeted by existing therapies in RA and with mechanistic data from the general population on cardiovascular risk. Specifically, the discussions include the IL-1, IL-6 and TNF pathways, as well as the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signalling pathway, and the role of these pathways in RA pathogenesis in the joint alongside the development of atherosclerotic cardiovascular disease. Overall, some robust data support inhibition of IL-1 and IL-6 in decreasing the risk of cardiovascular disease, with growing data supporting IL-6 inhibition in both patients with RA and the general population to reduce the risk of cardiovascular disease.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Rheumatoid arthritis (RA) affects 24.5 million people worldwide and has been associated with increased cancer risks. However, the extent to which the observed risks are related to the pathophysiology ...of rheumatoid arthritis or its treatments is unknown. Leveraging nationwide health insurance claims data with 85.97 million enrollees across 8 years, we identified 92 864 patients without cancers at the time of rheumatoid arthritis diagnoses. We matched 68 415 of these patients with participants without rheumatoid arthritis by sex, race, age and inferred health and economic status and compared their risks of developing all cancer types. By 12 months after the diagnosis of rheumatoid arthritis, rheumatoid arthritis patients were 1.21 (95% confidence interval CI 1.14, 1.29) times more likely to develop any cancer compared with matched enrollees without rheumatoid arthritis. In particular, the risk of developing lymphoma is 2.08 (95% CI 1.67, 2.58) times higher in the rheumatoid arthritis group, and the risk of developing lung cancer is 1.69 (95% CI 1.32, 2.13) times higher. We further identified the five most commonly used drugs in treating rheumatoid arthritis, and the log‐rank test showed none of them is implicated with a significantly increased cancer risk compared with rheumatoid arthritis patients without that specific drug. Our study suggested that the pathophysiology of rheumatoid arthritis, rather than its treatments, is implicated in the development of subsequent cancers. Our method is extensible to investigating the connections among drugs, diseases and comorbidities at scale.
What's new?
Cancer risk is increased by chronic inflammation, a significant feature of rheumatoid arthritis (RA). While RA patients are at increased risk of cancer, however, the degree to which cancer risk can be attributed to RA pathophysiology or treatment remains uncertain. Here, the authors examined relationships between RA, RA treatments and risk of different cancer types. RA patients were 1.69 to 2.08 times more likely than those without RA to develop lymphoma or lung cancer within 1 year of RA diagnosis. No significant difference in risk was detected for other cancer types. Commonly used RA treatments were also unlikely to increase cancer risk.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective
To evaluate rheumatoid arthritis (RA) and mortality risk among women followed prospectively in the Nurses’ Health Study (NHS).
Methods
We analyzed 119,209 women in the NHS who reported no ...connective tissue disease at enrollment in 1976. Comorbidity and lifestyle data were collected through biennial questionnaires. Incident RA cases were validated by medical records review. Cause of death was determined by death certificate and medical records review. Cox regression models estimated hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all‐cause, cardiovascular disease (CVD), cancer, and respiratory disease mortality for women with RA compared to those without RA.
Results
We validated 964 incident RA cases and identified 28,808 deaths during 36 years of prospective follow‐up. Of 307 deaths among women with RA, 80 (26%) were from cancer, 70 (23%) were from CVD, and 44 (14%) were from respiratory causes. Women with RA had increased total mortality (HR 1.40, 95% CI 1.25–1.57) compared to those without RA, independent of mortality risk factors, including smoking. RA was associated with significantly increased respiratory disease mortality (HR 2.06, 95% CI 1.51–2.80) and cardiovascular disease mortality (HR 1.45, 95% CI 1.14–1.83), but not cancer mortality (HR 0.93, 95% CI 0.74–1.15). For women with seropositive RA, respiratory disease mortality was nearly 3‐fold higher than among non‐RA women (HR 2.67, 95% CI 1.89–3.77).
Conclusion
Women with RA had significantly increased mortality compared to those without RA. Respiratory disease and cardiovascular disease mortality were both significantly elevated for women with RA. The nearly 3‐fold increased relative risk of respiratory disease mortality was observed only for those with seropositive RA.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Electronic medical records are emerging as a major source of data for clinical and translational research studies, although phenotypes of interest need to be accurately defined first. This article ...provides an overview of how to develop a phenotype algorithm from electronic medical records, incorporating modern informatics and biostatistics methods.
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BFBNIB, CMK, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
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