Dataset Information

4?-Hydroxycholesterol Level in Patients With Rheumatoid Arthritis Before vs. After Initiation of bDMARDs and Correlation With Inflammatory State.

ABSTRACT: Systemic inflammation has been linked to suppressed CYP3A(4) activity. We determined 4?-hydroxycholesterol (4?OHC), an endogenous CYP3A4 metabolite, in patients with rheumatoid arthritis (RA) before and after treatment with biological disease-modifying antirheumatic drugs (bDMARDs). The 4?OHC was compared in 41 patients before and 2-5 months after initiating TNF? inhibitors (n = 31), IL-6 inhibitors (n = 5), or B-cell inhibitors (n = 5). Correlations between 4?OHC and inflammatory markers (C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR)) were also tested before and after bDMARDs. 4?OHC did not differ following bDMARD treatment (P = 0.6), nor in patients who started with IL-6 inhibitors (median 51.6 vs. 50.6 nmol/L). The 4?OHC and CRP/ESR did not correlate before treatment (P > 0.5), but correlated significantly after bDMARDs (CRP = Spearman r -0.40; P < 0.01; ESR = r -0.34; P = 0.028) suggesting that mainly non-CYP3A4-suppressive cytokines were reduced during treatment. Thus, this study does not support a generally regained CYP3A4 phenotype in patients with RA following initiation of bDMARDs.

SUBMITTER: Wollmann BM

PROVIDER: S-EPMC5351010 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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4β-Hydroxycholesterol Level in Patients With Rheumatoid Arthritis Before vs. After Initiation of bDMARDs and Correlation With Inflammatory State.

Wollmann B M BM Syversen S W SW Lie E E Gjestad C C Mehus L L LL Olsen I C IC Molden E E

Clinical and translational science 20161105 1

Systemic inflammation has been linked to suppressed CYP3A(4) activity. We determined 4β-hydroxycholesterol (4βOHC), an endogenous CYP3A4 metabolite, in patients with rheumatoid arthritis (RA) before and after treatment with biological disease-modifying antirheumatic drugs (bDMARDs). The 4βOHC was compared in 41 patients before and 2-5 months after initiating TNFα inhibitors (n = 31), IL-6 inhibitors (n = 5), or B-cell inhibitors (n = 5). Correlations between 4βOHC and inflammatory markers (C-rea ...[more]

PMID: 27991741

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Project description:BackgroundFew studies on rheumatoid arthritis (RA) have generated machine learning models to predict biologic disease-modifying antirheumatic drugs (bDMARDs) responses; however, these studies included insufficient analysis on important features. Moreover, machine learning is yet to be used to predict bDMARD responses in ankylosing spondylitis (AS). Thus, in this study, machine learning was used to predict such responses in RA and AS patients.MethodsData were retrieved from the Korean College of Rheumatology Biologics therapy (KOBIO) registry. The number of RA and AS patients in the training dataset were 625 and 611, respectively. We prepared independent test datasets that did not participate in any process of generating machine learning models. Baseline clinical characteristics were used as input features. Responders were defined as those who met the ACR 20% improvement response criteria (ACR20) and ASAS 20% improvement response criteria (ASAS20) in RA and AS, respectively, at the first follow-up. Multiple machine learning methods, including random forest (RF-method), were used to generate models to predict bDMARD responses, and we compared them with the logistic regression model.ResultsThe RF-method model had superior prediction performance to logistic regression model (accuracy: 0.726 [95% confidence interval (CI): 0.725-0.730] vs. 0.689 [0.606-0.717], area under curve (AUC) of the receiver operating characteristic curve (ROC) 0.638 [0.576-0.658] vs. 0.565 [0.493-0.605], F1 score 0.841 [0.837-0.843] vs. 0.803 [0.732-0.828], AUC of the precision-recall curve 0.808 [0.763-0.829] vs. 0.754 [0.714-0.789]) with independent test datasets in patients with RA. However, machine learning and logistic regression exhibited similar prediction performance in AS patients. Furthermore, the patient self-reporting scales, which are patient global assessment of disease activity (PtGA) in RA and Bath Ankylosing Spondylitis Functional Index (BASFI) in AS, were revealed as the most important features in both diseases.ConclusionsRF-method exhibited superior prediction performance for responses of bDMARDs to a conventional statistical method, i.e., logistic regression, in RA patients. In contrast, despite the comparable size of the dataset, machine learning did not outperform in AS patients. The most important features of both diseases, according to feature importance analysis were patient self-reporting scales.

Project description:INTRODUCTION:Understanding the effects of corticosteroid utilization prior to initiation of biologic disease-modifying antirheumatic drugs (DMARDs) can inform decision-makers on the appropriate use of these medications. This study examined treatment patterns and associated burden of corticosteroid utilization before initiation of biologic DMARDs among rheumatoid arthritis (RA) patients. METHODS:A retrospective analysis was conducted of adult RA patients in the US MarketScan Database (2011-2015). The following patterns of corticosteroid utilization were analyzed: whether corticosteroids were used; duration of use (short/long duration defined as < or ? 3 months); and dosage (low as < 2.5, medium as 2.5 to < 7.5 and high as ? 7.5 mg/day). Effects of corticosteroid use on time to biologic DMARD initiation were examined using Cox proportional hazards models. Likelihood and number of adverse events were examined using logistic and negative binomial regression models. Generalized linear models were used to examine healthcare costs. Independent variables in all models included patient demographics and health characteristics. RESULTS:A total of 25,542 patients were included (40.84% used corticosteroids). Lower hazard of biologic DMARD initiation was associated with corticosteroid use (hazard ratio = 0.89, 95% confidence interval = 0.83-0.96), long duration and lower dose. Corticosteroid users compared to non-users had higher incidence rates of various adverse events including cardiovascular events (P < 0.05). Higher likelihood of adverse events was associated with corticosteroid use and long duration of use, as was increased number of adverse events. Corticosteroid users had a greater annualized mean number of physician visits, hospitalizations, and emergency department (ED) visits than non-users in adjusted analysis. Corticosteroid users compared to non-users had higher mean costs for total healthcare, physician visits, hospitalizations, and ED visits. CONCLUSIONS:Among patients with RA, corticosteroid utilization is associated with delayed initiation of biologic DMARDS and higher burden of adverse events and healthcare utilization/costs before the initiation of biologic DMARDs. FUNDING:AbbVie Inc.

Dataset Information

4?-Hydroxycholesterol Level in Patients With Rheumatoid Arthritis Before vs. After Initiation of bDMARDs and Correlation With Inflammatory State.

Publications

4β-Hydroxycholesterol Level in Patients With Rheumatoid Arthritis Before vs. After Initiation of bDMARDs and Correlation With Inflammatory State.

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