In the Pursuit of Methotrexate Treatment Response Biomarker in Juvenile Idiopathic Arthritis—Are We Getting Closer to Personalised Medicine?

Roszkiewicz, Justyna; Smolewska, Elżbieta

doi:10.1007/s11926-017-0646-8

Cited by 12 publications

(8 citation statements)

References 31 publications

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“…However, a GWAS study found no direct correlation between SNPs related to the pathways of MTX and the efficacy in 759 JIA patients (Cobb et al, 2014). This suggests that SNPs may not necessary in revealing the outcome of JIA (Albers et al, 2009; Roszkiewicz and Smolewska, 2017). Moreover, the expression and activity of enzymes in children may be affected by growth, and the genotype may not directly reflect the phenotype (Zhao et al, 2010; Roszkiewicz and Smolewska, 2017).…”

Section: Discussionmentioning

confidence: 99%

Early and Accurate Prediction of Clinical Response to Methotrexate Treatment in Juvenile Idiopathic Arthritis Using Machine Learning

Chen

et al. 2019

Front. Pharmacol.

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Background and Aims: Accurately predicting the response to methotrexate (MTX) in juvenile idiopathic arthritis (JIA) patients before administration is the key point to improve the treatment outcome. However, no simple and reliable prediction model has been identified. Here, we aimed to develop and validate predictive models for the MTX response to JIA using machine learning based on electronic medical record (EMR) before and after administering MTX.Materials and Methods: Data of 362 JIA patients with MTX mono-therapy were retrospectively collected from EMR between January 2008 and October 2018. DAS44/ESR-3 simplified standard was used to evaluate the MTX response. Extreme gradient boosting (XGBoost), support vector machine (SVM), random forest (RF), and logistic regression (LR) algorithms were applied to develop and validate models with 5-fold cross-validation on the randomly split training and test set. Data of 13 patients additionally collected were used for external validation.Results: The XGBoost screened out the optimal 10 pre-administration features and 6 mix-variables. The XGBoost established the best model based on the 10 pre-administration variables. The performances were accuracy 91.78%, sensitivity 90.70%, specificity 93.33%, AUC 97.00%, respectively. Similarly, the XGBoost developed a better model based on the 6 mix-variables, whose performances were accuracy 94.52%, sensitivity 95.35%, specificity 93.33%, AUC 99.00%, respectively.Conclusion: Based on common EMR data, we developed two MTX response predictive models with excellent performance in JIA using machine learning. These models can predict the MTX efficacy early and accurately, which provides powerful decision support for doctors to make or adjust therapeutic scheme before or after treatment.

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Section: Discussionmentioning

confidence: 99%

Early and Accurate Prediction of Clinical Response to Methotrexate Treatment in Juvenile Idiopathic Arthritis Using Machine Learning

Chen

et al. 2019

Front. Pharmacol.

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“…Rheumatoid vasculitis, a relatively rare condition, can affect the aorta. This condition is difficult to discriminate clinically from atherosclerosis 6 . Furthermore, RA is associated with significant inflammation and an elevated cardiovascular risk and mortality comparable to that of diabetes 7 .…”

Section: Discussionmentioning

confidence: 99%

Case report of an unusual and catastrophic presentation of coral reef aorta

Verreault-Julien

Beaudoin

Theriault

et al. 2019

European Heart Journal - Case Reports

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Background Coral reef aorta (CRA) is a rare condition characterized by atherosclerosis and overt calcification of the aorta leading to severe luminal stenosis of the vessel. Most patients present with hypertension and intermittent claudication at the time of diagnosis. Risk factors associated with this condition are essentially the same as those associated with atherosclerosis. However, no unique condition seems to predispose an individual to develop CRA. Case summary We describe the case of a patient known for rheumatoid arthritis (RA) treated with long-term systemic corticosteroids who presented with a shock of unknown aetiology and left ventricular ejection fraction of 10%. Conventional and computed tomography angiography showed a CRA with subtotal lesion of the aortic arch that led to cardiogenic shock. Discussion Even though the exact aetiology of her condition will remain uncertain, RA and extended use of corticosteroids likely played a role in the development of this severe form of CRA.

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“…Therefore, determinants of early MTX response and toxicity that can be applied to individualize JIA treatment strategies are urgently required. There is growing evidence 4 that single nucleotide polymorphisms (SNP) within the genes responsible for MTX cellular influx/efflux, polyglutamination, involved in folate pathway, purine and pyrimidine synthesis (Figure 1) are associated with response to the drug and risk of therapy adverse events (AE), both in patients with rheumatoid arthritis (RA) 5‐7 and JIA 8 . Despite its widespread use, the mechanism of action of low‐dose MTX used weekly in rheumatological indications remains elusive 9 .…”

Section: Introductionmentioning

confidence: 99%

The impact of single nucleotide polymorphisms in ADORA2A and ADORA3 genes on the early response to methotrexate and presence of therapy side effects in children with juvenile idiopathic arthritis: Results of a preliminary study

et al. 2020

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Aim: Methotrexate (MTX) administered at the dose 10-15 mg/m 2 is recommended as the first-line therapy in most juvenile idiopathic arthritis (JIA) subtypes. The diseasemodifying effect of methotrexate is associated with release of adenosine and mediated via binding to adenosine receptor A2A (ADORA2A) and 3 (ADORA3). The aim of our study was to determine the association between single nucleotide polymorphisms in ADORA2A (rs2236624, rs2298383) and ADORA3 (rs3393) receptor genes on the disease activity and presence of MTX therapy side effects in patients with JIA. Methods: One hundred children with JIA of all subtypes treated with MTX were recruited to the study. Demographic and clinical parameters were collected at the baseline of MTX therapy and on a control visit 4-6 months after starting MTX. Single nucleotide polymorphism genotyping was performed using genomic DNA isolated from peripheral blood samples. Results: The polymorphic variant of ADORA2A rs2236624 was associated with ~3.5 times higher odds of gastrointestinal side effects occurrence (odds ratio: 3.59, 95% CI: 1.15-11.22, P = 0.0282). Children with the ADORA3 rs3393 polymorphic variants (CT/CC) after 6 months of MTX treatment had significantly lower number of joints with active arthritis (median: 0.00 vs 1.00, P = 0.0400) and value of C-reactive protein (0.60 vs 2.40, P = 0.0242) in comparison to TT variant. Conclusion: Although future studies are needed to verify our findings, polymorphisms in ADORA2A and ADORA3 genes may become the determinants of MTX treatment efficacy and gastrointestinal toxicity in children with JIA.

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In the Pursuit of Methotrexate Treatment Response Biomarker in Juvenile Idiopathic Arthritis—Are We Getting Closer to Personalised Medicine?

Cited by 12 publications

References 31 publications

Early and Accurate Prediction of Clinical Response to Methotrexate Treatment in Juvenile Idiopathic Arthritis Using Machine Learning

Early and Accurate Prediction of Clinical Response to Methotrexate Treatment in Juvenile Idiopathic Arthritis Using Machine Learning

Case report of an unusual and catastrophic presentation of coral reef aorta

The impact of single nucleotide polymorphisms in ADORA2A and ADORA3 genes on the early response to methotrexate and presence of therapy side effects in children with juvenile idiopathic arthritis: Results of a preliminary study

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