scholarly journals A Bayesian Model for Prediction of Rheumatoid Arthritis from Risk Factors

2020 ◽  
Author(s):  
Leon Lufkin ◽  
Marko Budišić ◽  
Sumona Mondal ◽  
Shantanu Sur
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Predictive Model ◽  
Characteristic Curve ◽  
Strong Association ◽  
Autoimmune Disorder ◽  
Mixed Data ◽  
Validation Dataset ◽  
Third Order ◽  
Organ Systems

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that typically manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to influence the incidence and progress of the disease. In this work, we aimed to predict RA from a set of 11 well-known risk factors and their interactions using Bayesian logistic regression. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The predictive model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA). We use data from the National Health and Nutrition Examination Survey (NHANES). Our optimal predictive model has a smoothed AUC of 0.826 (95% CI: 0.801 −0.850) on a validation dataset and 0.805 (95% CI: 0.781 −0.829) on a holdout test dataset. Our model identified multiple second- and third-order interactions that demonstrate a strong association with RA, implying the potential role of risk factor interactions in the disease mechanism. Interestingly, we find that the inclusion of higher-order interactions in the model only marginally improves overall predictive ability. Our findings on the contribution of RA risk factors and their interaction on disease prediction could be useful in developing strategies for early diagnosis of RA, thus opening potential avenues for improved patient outcomes and reduced healthcare burden to society.

scholarly journals A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions

2021 ◽  
Vol 9 ◽  
Author(s):  
Leon Lufkin ◽  
Marko Budišić ◽  
Sumona Mondal ◽  
Shantanu Sur
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Characteristic Curve ◽  
Strong Association ◽  
Mixed Data ◽  
Validation Dataset ◽  
Individual Risk ◽  
Third Order ◽  
Cross Sectional ◽  
Organ Systems

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that commonly manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to associate with RA and influence the progress of the disease. In this work, we used a Bayesian logistic regression model to quantitatively assess how these factors influence the risk of RA, individually and through their interactions. Using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES), a set of 11 well-known RA risk factors such as age, gender, ethnicity, body mass index (BMI), and depression were selected to predict RA. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA) with the optimal predictive model having a smoothed AUC of 0.826 (95% CI: 0.801–0.850) on a validation dataset and 0.805 (95% CI: 0.781–0.829) on a holdout test dataset. Apart from corroborating the influence of individual risk factors on RA, our model identified a strong association of RA with multiple second- and third-order interactions, many of which involve age or BMI as one of the factors. This observation suggests a potential role of risk-factor interactions in RA disease mechanism. Furthermore, our findings on the contribution of RA risk factors and their interactions to disease prediction could be useful in developing strategies for early diagnosis of RA.

scholarly journals Explaining the cardiovascular risk associated with rheumatoid arthritis: traditional risk factors versus markers of rheumatoid arthritis severity

2010 ◽  
Vol 69 (11) ◽  
pp. 1920-1925 ◽  
Author(s):  
Daniel H Solomon ◽  
Joel Kremer ◽  
Jeffrey R Curtis ◽  
Marc C Hochberg ◽  
George Reed ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Incidence Rate ◽  
Characteristic Curve ◽  
C Statistic ◽  
The Usa ◽  
Traditional Risk Factors ◽  
And Gender ◽  
Cv Disease ◽  
Prospective Longitudinal

BackgroundCardiovascular (CV) disease has a major impact on patients with rheumatoid arthritis (RA), however, the relative contributions of traditional CV risk factors and markers of RA severity are unclear. The authors examined the relative importance of traditional CV risk factors and RA markers in predicting CV events.MethodsA prospective longitudinal cohort study was conducted in the setting of the CORRONA registry in the USA. Baseline data from subjects with RA enrolled in the CORRONA registry were examined to determine predictors of CV outcomes, including myocardial infarction, stroke or transient ischemic attack. Possible predictors were of two types: traditional CV risk factors and markers of RA severity. The discriminatory value of these variables was assessed by calculating the area under the receiver operating characteristic curve (c-statistic) in logistic regression. The authors then assessed the incidence rate for CV events among subjects with an increasing number of traditional CV risk factors and/or RA severity markers.ResultsThe cohort consisted of 10 156 patients with RA followed for a median of 22 months. The authors observed 76 primary CV events during follow-up for a composite event rate of 3.98 (95% CI 3.08 to 4.88) per 1000 patient-years. The c-statistic improved from 0.57 for models with only CV risk factors to 0.67 for models with CV risk factors plus age and gender. The c-statistic improved further to 0.71 when markers of RA severity were also added. The incidence rate for CV events was 0 (95% CI 0 to 5.98) for persons without any CV risk factors or markers of RA severity, while in the group with two or more CV risk factors and three or more markers of RA severity the incidence was 7.47 (95% CI 4.21 to 10.73) per 1000 person-years.ConclusionsTraditional CV risk factors and markers of RA severity both contribute to models predicting CV events. Increasing numbers of both types of factors are associated with greater risk.

scholarly journals Bronchopulmonary Dysplasia Predicted by Developing a Machine Learning Model of Genetic and Clinical Information

2021 ◽  
Vol 12 ◽  
Author(s):  
Dan Dai ◽  
Huiyao Chen ◽  
Xinran Dong ◽  
Jinglong Chen ◽  
Mei Mei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Predictive Model ◽  
Risk Prediction ◽  
Bronchopulmonary Dysplasia ◽  
Premature Infants ◽  
Genetic Factors ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Clinical Risk Factors ◽  
Clinical Risk

BackgroundAn early and accurate evaluation of the risk of bronchopulmonary dysplasia (BPD) in premature infants is pivotal in implementing preventive strategies. The risk prediction models nowadays for BPD risk that included only clinical factors but without genetic factors are either too complex without practicability or provide poor-to-moderate discrimination. We aim to identify the role of genetic factors in BPD risk prediction early and accurately.MethodsExome sequencing was performed in a cohort of 245 premature infants (gestational age <32 weeks), with 131 BPD infants and 114 infants without BPD as controls. A gene burden test was performed to find risk genes with loss-of-function mutations or missense mutations over-represented in BPD and severe BPD (sBPD) patients, with risk gene sets (RGS) defined as BPD–RGS and sBPD–RGS, respectively. We then developed two predictive models for the risk of BPD and sBPD by integrating patient clinical and genetic features. The performance of the models was evaluated using the area under the receiver operating characteristic curve (AUROC).ResultsThirty and 21 genes were included in BPD–RGS and sBPD–RGS, respectively. The predictive model for BPD, which combined the BPD–RGS and basic clinical risk factors, showed better discrimination than the model that was only based on basic clinical features (AUROC, 0.915 vs. AUROC, 0.814, P = 0.013, respectively) in the independent testing dataset. The same was observed in the predictive model for sBPD (AUROC, 0.907 vs. AUROC, 0.826; P = 0.016).ConclusionThis study suggests that genetic information contributes to susceptibility to BPD. The predictive model in this study, which combined BPD–RGS with basic clinical risk factors, can thus accurately stratify BPD risk in premature infants.

scholarly journals Infections Caused by Extended-Spectrum β-Lactamase Producing Escherichia Coli in Systemic Lupus Erythematosus Patients: Prevalence, Risk Factors, and Predictive Model

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yuetian Yu ◽  
Hui Shen ◽  
Cheng Zhu ◽  
Ruru Guo ◽  
Yuan Gao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Escherichia Coli ◽  
Systemic Lupus Erythematosus ◽  
Predictive Model ◽  
Lupus Erythematosus ◽  
Characteristic Curve ◽  
Antibiotics Resistance ◽  
Systemic Lupus ◽  
E Coli ◽  
Extended Spectrum

Objective. To investigate the prevalence and risk factors of infections caused by Extended-Spectrum β-Lactamase (ESBL) producing Escherichia coli (E. coli) in systemic lupus erythematosus (SLE) patients and develop a predictive model. Methods. Three hundred and eighty-four consecutive SLE patients with E. coli infection were enrolled in this retrospective case control study from January 2012 to December 2017. Prevalence and antimicrobial susceptibility pattern of ESBL producing E. coli were analyzed. Multivariate analysis was performed to determine the risk factors. Sensitivity and specificity were obtained at various point cutoffs and area under the receiver operator characteristic curve (AuROC) was determined to confirm the prediction power of the model. Results. Of the total 384 E. coli strains tested, 212 (55.2%) produced ESBL. The majority of these isolates were from urine (44.3%). Carbapenems (>80%) and amikacin (89.6%) had good activity against ESBL producing E. coli. Eleven variables were identified as independent risk factors for ESBL producing E. coli infection including Enterobacteriaceae colonization or infection in preceding year (OR=8.15, 95%CI 5.12–21.71), daily prednisone dose > 30mg (OR=5.48, 95%CI 3.12–13.72), low C3 levels (OR=2.17, 95%CI 1.62–6.71), nosocomial acquired infection (OR=4.12, 95%CI 1.98–8.85), etc. The model developed to predict ESBL producing E. coli infection was effective, with the AuROC of 0.840 (95% CI 0.799-0.876). Conclusions. The prevalence of ESBL producing E. coli was increasing with high antibiotics resistance in patients with SLE. The model revealed excellent predictive performance and exhibited a good discrimination.

scholarly journals Knowledge, prevalence and risk factors of rheumatoid arthritis among middle-aged and old aged population

2020 ◽  
Vol 11 (SPL3) ◽  
pp. 522-528
Author(s):  
Sachin Aditya B ◽  
Karthik Ganesh Mohanraj ◽  
Vishnu Priya V
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Joint Destruction ◽  
Premature Death ◽  
Autoimmune Disorder ◽  
Economic Loss ◽  
Chronic Disorder ◽  
Fluctuating Course ◽  
Patients Experience ◽  
Structured Questionnaire

Rheumatoid Arthritis is a chronic disorder and affects the lining of joints and functioning of various other vital organs like the heart, kidneys and lungs. It is an autoimmune disorder where the body's immune system attacks its tissues. Most patients experience a chronic fluctuating course of a disease that, despite therapy, may result in progressive joint destruction, deformity, disability, and even premature death. Joints most commonly affected are those with the highest ratio of synovium to articular cartilage. It is more common in women than in men. Its symptoms include tender and warm joints which may lead to joint deformities in extreme cases. This study involved 100 participants of age ranging from 16-55 years. A well-structured questionnaire based on personal, socioeconomic information along with symptoms and treatment of RA was prepared and circulated online through Google forms among the participants. The results showed that most of the participants were aware of the common symptoms of RA and their risk factors and more than 60% of participants were students, over 90% of respondents said it is genetic. Smoking can increase the chance of attaining it. Disability from RA causes major economic loss and can have a profound impact on families. However, it can be managed treated and even remitted in some cases if proper habits like exercise are followed. It should be diagnosed as early as possible for better chances of remission.

Cardiovascular Risk in Rheumatoid Arthritis and Mechanistic Links: From Pathophysiology to Treatment

2020 ◽  
Vol 18 (5) ◽  
pp. 431-446 ◽  
Author(s):  
George E. Fragoulis ◽  
Ismini Panayotidis ◽  
Elena Nikiphorou
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Current Evidence ◽  
Pharmacological Intervention ◽  
Cvd Risk ◽  
The Past ◽  
Increased Risk ◽  
Cv Disease ◽  
Obesity Hypertension ◽  
Inflammatory Burden

Rheumatoid arthritis (RA) is an autoimmune inflammatory arthritis. Inflammation, however, can spread beyond the joints to involve other organs. During the past few years, it has been well recognized that RA associates with increased risk for cardiovascular (CV) disease (CVD) compared with the general population. This seems to be due not only to the increased occurrence in RA of classical CVD risk factors and comorbidities like smoking, obesity, hypertension, diabetes, metabolic syndrome, and others but also to the inflammatory burden that RA itself carries. This is not unexpected given the strong links between inflammation and atherosclerosis and CVD. It has been shown that inflammatory cytokines which are present in abundance in RA play a significant role in every step of plaque formation and rupture. Most of the therapeutic regimes used in RA treatment seem to offer significant benefits to that end. However, more studies are needed to clarify the effect of these drugs on various parameters, including the lipid profile. Of note, although pharmacological intervention significantly helps reduce the inflammatory burden and therefore the CVD risk, control of the so-called classical risk factors is equally important. Herein, we review the current evidence for the underlying pathogenic mechanisms linking inflammation with CVD in the context of RA and reflect on the possible impact of treatments used in RA.

Effect of Dietary Education on Cardiovascular risk Factors in Rheumatoid Arthritis Patients

2020 ◽  
Vol 16 ◽  
Author(s):  
Rahil Taheri ◽  
Shahram Molavynejad ◽  
Parvin Abedi ◽  
Elham Rajaei ◽  
Mohammad Hosein Haghighizadeh
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Blood Pressure ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Statistical Tests ◽  
Intervention Group ◽  
Serum Levels ◽  
Control Group ◽  
Dietary Education

Aim: The aim of this study was to investigate the effect of dietary education on cardiovascular risk factors in patients with rheumatoid arthritis. Method: In this randomized clinical trial, 112 patients with rheumatoid arthritis were randomly assigned into two groups, intervention and control. Dietary education was provided for the intervention group in 4 sessions; anthropometric measurements, serum levels of RF, triglycerides, cholesterol, HDL, LDL, and fasting blood sugar were measured before and three months after intervention. Data was analyzed using SPSS software and appropriate statistical tests. Results: The mean of total cholesterol (p <0.001), triglycerides (p = 0.004), LDL (p <0.001), systolic blood pressure (p = 0.001), diastolic blood pressure (p = 0.003), FBS and BMI (p <0.001) were decreased significantly in the intervention group after education compared the control group. Conclusion: Traditional care for rheumatoid arthritis patients is not enough. Patients need more education in order to improve their situation.

scholarly journals SAT0037 INCREASED CARDIOMETABOLIC RISK FACTORS ARE RELATED TO THE ABNORMAL ADIPOCYTOKINE PROFILE AND AUTOIMMUNITY IN RHEUMATOID ARTHRITIS. MODULATION BY TNFALPHA AND IL6R INHIBITORS

2019 ◽  
Author(s):  
Iván Arias de la Rosa ◽  
Maria del Carmen Abalos-Aguilera ◽  
Rafaela Ortega Castro ◽  
Jerusalem Calvo Gutierrez ◽  
Carlos Perez-Sanchez ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors

scholarly journals POS0441 DEVELOPMENT OF RHEUMATOID ARTHRITIS AMONG ANTI-CITRULLINATED PROTEIN ANTIBODIES POSITIVE ASYMPTOMATIC INDIVIDUALS: A PROSPECTIVE OBSERVATIONAL STUDY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 449.1-449
Author(s):  
S. Mizuki ◽  
K. Horie ◽  
K. Imabayashi ◽  
K. Mishima ◽  
K. Oryoji
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Observational Study ◽  
Rheumatoid Factor ◽  
Prospective Observational Study ◽  
Enzyme Linked Immunosorbent Assay ◽  
P Value ◽  
Healthy Population ◽  
Asymptomatic Individuals ◽  
Citrullinated Protein

Background:In the idividuals with genetic and enviromental risk factors, immune events at mucosal surfaces occur and may precede systemic autoimmunity. Anti-citrullinated protein antibodies (ACPA) are present in the serum for an average of 3-5 years prior to the onset of rheumatoid arthritis (RA) during an asymptomatic period. In ACPA-positivite individuals, the additional presence of RA-related risk factors appears to add significant power for the development of RA. To date, there have been few reports in which clinical courses of ACPA-positive asymptomatic individuals were investigated prospectively.Objectives:To observe the clinical time course of ACPA-positive healthy population for the development of RA.Methods:Healthy volunteers without joint pain or stiffness, who attended the comprehensive health screening of our hospital, were enrolled in this prospective observational study. The serum ACPA levels were quantified by Ig-G anti-cyclic citrullinated peptide enzyme-linked immunosorbent assay with levels > 4.4 U/mL considered positive. ACPA-positive subjects were followed by rheumatologists of our department clinically or a questionnaire sent by mail for screening to detect arthritis.Results:5,971 healthy individuals without joint symptons were included. Ninty-two (1.5%) were positive for ACPA. Of these, 19 (20.7%) developed RA and two were suspected as RA by mail questionnaire. Their average age were 58-years, and women were 68%. The average duration between the date of serum sampling and diagnosis was 10.7 months. ACPA-positive individuals who developed to RA had higher serum ACPA and Ig-M rheumatoid factor levels than ACPA-positive individuals who did not (P value by Mann-Whitney U test: 0.002, 0.005, respectively).Conclusion:Among ACPA-positive asymptomatic individuals, 20% developed RA. The higher titer of ACPA and Ig-M rheumatoid factor levels are risk factors for devoloping RA.Disclosure of Interests:None declared

scholarly journals Prevalence and risk factors for bone loss in rheumatoid arthritis patients from South China: modeled by three methods

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhuoran Hu ◽  
Lei Zhang ◽  
Zhiming Lin ◽  
Changlin Zhao ◽  
Shuiming Xu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Lumbar Spine ◽  
Bone Loss ◽  
South China ◽  
Serum Vitamin ◽  
Tumor Necrosis Factor Inhibitor ◽  
Healthy Controls ◽  
Mineral Density ◽  
Serum Vitamin D

Abstract Background To explore the prevalence of bone loss among patients with rheumatoid arthritis (RA) and healthy controls (HC) and further explored the risk factors for osteopenia and osteoporosis of RA patients. Methods A cross-sectional survey was undertaken in four hospitals in different districts in South China to reveal the prevalence of bone loss in patients. Case records, laboratory tests, and bone mineral density (BMD) results of patients were collected. Traditional multivariable logistic regression analysis and two machine learning methods, including least absolute shrinkage selection operator (LASSO) and random forest (RF) were for exploring the risk factors for osteopenia or osteoporosis in RA patients. Results Four hundred five patients with RA and 198 HC were included. RA patients had lower BMD in almost BMD measurement sites than healthy controls; the decline of lumbar spine BMD was earlier than HC. RA patients were more likely to comorbid with osteopenia and osteoporosis (p for trend < 0.001) in the lumbar spine than HC. Higher serum 25-hydroxyvitamin D3 level and using tumor necrosis factor inhibitor in the last year were protective factors; aging, lower body mass index, and increased serum uric acid might be risk factors for bone loss. Conclusions RA patients were more prone and earlier to have bone loss than HC. More attention should be paid to measuring BMD in RA patients aging with lower BMI or hyperuricemia. Besides, serum vitamin D and all three measurement sites are recommended to check routinely. TNFi usage in the last year might benefit bone mass.

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