scholarly journals Multiomics and Machine Learning Accurately Predict Clinical Response to Adalimumab and Etanercept Therapy in Patients With Rheumatoid Arthritis

2020 ◽  
Author(s):  
Weiyang Tao ◽  
Arno N. Concepcion ◽  
Marieke Vianen ◽  
Anne C. A. Marijnissen ◽  
Floris P. G. J. Lafeber ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Machine Learning ◽  
Clinical Response ◽  
Etanercept Therapy

FRI0175 The influence of smoking on clinical response to etanercept therapy in patients with rheumatoid arthritis

2013 ◽  
Vol 71 (Suppl 3) ◽  
pp. 371.2-371 ◽  
Author(s):  
S. Zivojinovic ◽  
N. Pilipovic ◽  
M. Sefik Bukilica ◽  
L. Kovacevic ◽  
N. Roganovic ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Clinical Response ◽  
Etanercept Therapy

scholarly journals AB0199 GENES PREDICTIVE ON THE EFFICACY OF INFLIXIMAB IN THE TREATMENT OF RHEUMATOID ARTHRITIS: A PROSPECTIVE, MULTI-CENTRE, CLINICAL PERFORMANCE EVALUATION STUDY FOR AN IN-VITRO DIAGNOSTICS MEDICAL DEVICE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1400.2-1400
Author(s):  
E. Kiss ◽  
G. Poór ◽  
G. Zahuczky ◽  
K. Tauberné Jakab ◽  
M. Sebeszta ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Machine Learning ◽  
Clinical Response ◽  
Medical Device ◽  
Expression Profiling ◽  
Biological Therapy ◽  
Infliximab Treatment ◽  
In Vitro Diagnostic

Background:Approximately 30% of rheumatoid arthritis (RA) patients fail to respond to first biological therapy, thus treatment selection of biologic therapy for patients with RA is of high importance. The lack of biomarkers to predict specific biological treatment response, in the case of non-responder (NR) patients leads to unnecessary exposure, delay of adequate therapy, progression of the disease and therapy cost increase. Predicting the patient’s responsiveness to the first biological therapy is still an unmet need in the clinical setting. Predictive in vitro testing would have a significant effect on the administration of biological therapy, on the real life implementation of cost effective personalized therapy.Objectives:The purpose of this in vitro diagnostic medical device study was to demonstrate that particular gene expression profiles as genomic biomarkers (i.e. the IVD medical device) predict therapeutic response to infliximab, discriminate between responders and non-responders to infliximab treatment. Responders were defined if they reached DAS target value DAS28≤3.2 at 6 month (M6).Methods:110 bionaive patients were enrolled with moderate-high activity RA (DAS28-CRP >3.2), who have responded inadequately to DMARDs (including methotrexate), after they have been assigned to infliximab treatment. All patients received commercially available infliximab, procured according to SmPC, local guidelines and regulations in this non-interventional clinical study. The clinical response was evaluated according to the change from baseline in disease activity at M6. Clinical characteristics (RA duration, smoke, steroid treatment, etc.) and serological parameters (RF, ACPA, aCVM) were collected. A 3rdvisit scheduled around week 22 (M6) and change of DAS28-CRP value from the baseline has been evaluated. Gene expression profiling was performed from blood samples taken at month 0 (M0); - just before the first infliximab infusion. Global gene expression profiling was performed to identify differentially expressing genes using RNA sequencing. The set of differentially expressing genes were further reduced with a combination of machine learning modelling and various feature elimination methods. The expression of the reduced gene set was confirmed and further analysed using reverse-transcription and quantitative real-time PCR.Results:A total of 250 genes were identified by a combination of differential gene expression analyses, feature elimination techniques and various machine learning modelling methods of which 44 genes showed significant differences between NR and good responder groups. Preliminary interim analysis identified associations between gene expression and clinical response/ non-response to infliximab therapy.Table.Three models containing gene expression + clinical data sets illustrates some statistical characteristicsModell building_IDAccuracySensitivitySpecificityModell VerificationAccuracySensitivitySpecificity00232100.00100.00100.00002328888.8987.5000249 98.82 96.55100.00002498477.7887.5000270 98.82 96.55100.00002708877.7893.75Conclusion:Our preliminary analysis shows that this set of genes and selected clinical parameters are predictive markers for infliximab specific response in RA patients. Ongoing work involves the clinical validation of these results in an independent patient cohort (n=60). This approach provides the opportunity to develop an in vitro diagnostic test method for the prediction of infliximab treatment responsiveness in bionaive rheumatod arthritis patients, hence to personalize infliximab therapy for these patients.Disclosure of Interests:Emese Kiss Consultant of: EK has received consultancy fees from Egis., Gyula Poór Consultant of: GyP has received consultancy fees from Egis and he was the coordinating investigator in this study, Gábor Zahuczky Grant/research support from: Egis, Katalin Tauberné Jakab Employee of: Egis., Miklós Sebeszta Employee of: Egis., Tamás Ponyi Employee of: Egis., Zsolt Holló Employee of: Egis.

scholarly journals Improvements in clinical response between 12 and 24 weeks in patients with rheumatoid arthritis on etanercept therapy with or without methotrexate

2008 ◽  
Vol 67 (10) ◽  
pp. 1444-1447 ◽  
Author(s):  
A Kavanaugh ◽  
L Klareskog ◽  
D van der Heijde ◽  
J Li ◽  
B Freundlich ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Clinical Response ◽  
Etanercept Therapy

scholarly journals AB0135 A VERY EARLY CLINICAL RESPONSE TO TOFACITINIB IS ASSOCIATED WITH LOW RHEUMATOID ARTHRITIS ACTIVITY AFTER 3 AND 6 MONTHS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1095.3-1096
Author(s):  
A. Karateev ◽  
A. Lila ◽  
E. Nasonov ◽  
V. Mazurov ◽  
D. Chakieva ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Clinical Response ◽  
Central Sensitization ◽  
Intracellular Signaling ◽  
Pain Reduction ◽  
Pain Severity ◽  
Jak Inhibitors ◽  
Significant Pain ◽  
Number Of Patients ◽  
Days Of Therapy

Background:JAK inhibitors block intracellular signaling pathways responsible for the synthesis of cytokines and mediators involved in the development of chronic pain and central sensitization (CS). This determines a very rapid clinical response to JAK inhibitors. However, it is not clear how the significant pain reduction in the first weeks of therapy is associated with the achievement of low rheumatoid arthritis (RA) activity.Objectives:to assess the relationship between the early clinical response to tofacitinib and the decrease in RA activity after 3 and 6 months.Methods:Study group included 88 patients with RA, their age was 53±11,5, 79.3% of women, 89.8% of RF “+”, DAS28 5.2±1.2, receiving DMARDs (methotrexate 59.5% and leflunomide 19.8%), who were administered with tofacitinib 5 mg 2 times a day due to inefficacy or intolerance of biological DMARDs. There were assessed the pain severity using Brief pain inventory (BPI) questionnaire, the presence of neuropathic pain component (NPC) using PainDETECT questionnaire and signs of CS using Central Sensitisation Inventory (CSI) questionnaire at early time after tofacitinib administration, RA activity using DAS28 after 3 and 6 months.Results:The mean pain severity at baseline was 5.3±2.0 according to the visual analogue scale (VAS 0-10), 51.1% of patients had signs of central sensitization (CSI ≥ 40), 15.9% had NPC (PainDETECT ≥18). 7 days after tofacitinib intake there was statistically reliable reduction of pain severity – up to 4.1±1.8 (р<0.05) and CS – CSI from 40.4±13.5 to 36.5±12.5 (р=0.01). After 28 days, the effect was higher: the pain level (VAS) was 2.8±1.6 (p=0.000), PainDETECT decreased from 11.8±5.6 to 6.8±3.1 (p=0.000), CSI – to 31.6±13.9 (p=0.000). DAS28 after 3 and 6 months was 3.7±1.3 and 3.6±1.2. The number of patients with pain decrease of ≥50% after 28 days of therapy was 59.9%. Low RA activity after 3 months. (DAS28 ≤3.2) was achieved in 64.4% of patients. There was a clear correlation between the number of patients with significant pain reduction at 28 days and the number of patients with low RA activity after 3 and 6 months (rS=0.548, p=0.000; rS=0.790, p=0.000). Six patients withdrew from the study due to inefficacy or social reasons. There were no serious adverse reactions.Conclusion:The application of JAK inhibitor tofacitinib allows to reach a fast analgesic effect and reduce CS signs. An early clinical response to tofacitinib (pain relief) predicts a decrease in RA activity after 3 and 6 months of the therapy.Limitation: Open-label observatory study.Disclosure of Interests:None declared

scholarly journals FRI0046 PHARMACOGENOMICS-DRIVEN INDIVIDUALIZED PREDICTION OF TREATMENT RESPONSE TO METHOTREXATE IN PATIENTS WITH RHEUMATOID ARTHRITIS: A MACHINE LEARNING APPROACH

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 598.2-598
Author(s):  
E. Myasoedova ◽  
A. Athreya ◽  
C. S. Crowson ◽  
R. Weinshilboum ◽  
L. Wang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Machine Learning ◽  
Supervised Machine Learning ◽  
Research Support ◽  
Eular Response ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Early Ra ◽  
Genome Wide

Background:Methotrexate (MTX) is the most common anchor drug for rheumatoid arthritis (RA), but the risk of missing the opportunity for early effective treatment with alternative medications is substantial given the delayed onset of MTX action and 30-40% inadequate response rate. There is a compelling need to accurately predicting MTX response prior to treatment initiation, which allows for effectively identifying patients at RA onset who are likely to respond to MTX.Objectives:To test the ability of machine learning approaches with clinical and genomic biomarkers to predict MTX response with replications in independent samples.Methods:Age, sex, clinical, serological and genome-wide association study (GWAS) data on patients with early RA of European ancestry from 647 patients (336 recruited in United Kingdom [UK]; 307 recruited across Europe; 70% female; 72% rheumatoid factor [RF] positive; mean age 54 years; mean baseline Disease Activity Score with 28-joint count [DAS28] 5.65) of the PhArmacogenetics of Methotrexate in RA (PAMERA) consortium was used in this study. The genomics data comprised 160 genome-wide significant single nucleotide polymorphisms (SNPs) with p<1×10-5 associated with risk of RA and MTX metabolism. DAS28 score was available at baseline and 3-month follow-up visit. Response to MTX monotherapy at the dose of ≥15 mg/week was defined as good or moderate by the EULAR response criteria at 3 months’ follow up visit. Supervised machine-learning methods were trained with 5-repeats and 10-fold cross-validation using data from PAMERA’s 336 UK patients. Class imbalance (higher % of MTX responders) in training was accounted by using simulated minority oversampling technique. Prediction performance was validated in PAMERA’s 307 European patients (not used in training).Results:Age, sex, RF positivity and baseline DAS28 data predicted MTX response with 58% accuracy of UK and European patients (p = 0.7). However, supervised machine-learning methods that combined demographics, RF positivity, baseline DAS28 and genomic SNPs predicted EULAR response at 3 months with area under the receiver operating curve (AUC) of 0.83 (p = 0.051) in UK patients, and achieved prediction accuracies (fraction of correctly predicted outcomes) of 76.2% (p = 0.054) in the European patients, with sensitivity of 72% and specificity of 77%. The addition of genomic data improved the predictive accuracies of MTX response by 19% and achieved cross-site replication. Baseline DAS28 scores and following SNPs rs12446816, rs13385025, rs113798271, and rs2372536 were among the top predictors of MTX response.Conclusion:Pharmacogenomic biomarkers combined with DAS28 scores predicted MTX response in patients with early RA more reliably than using demographics and DAS28 scores alone. Using pharmacogenomics biomarkers for identification of MTX responders at early stages of RA may help to guide effective RA treatment choices, including timely escalation of RA therapies. Further studies on personalized prediction of response to MTX and other anti-rheumatic treatments are warranted to optimize control of RA disease and improve outcomes in patients with RA.Disclosure of Interests:Elena Myasoedova: None declared, Arjun Athreya: None declared, Cynthia S. Crowson Grant/research support from: Pfizer research grant, Richard Weinshilboum Shareholder of: co-founder and stockholder in OneOme, Liewei Wang: None declared, Eric Matteson Grant/research support from: Pfizer, Consultant of: Boehringer Ingelheim, Gilead, TympoBio, Arena Pharmaceuticals, Speakers bureau: Simply Speaking

scholarly journals AB0304 IMMUNOGENICITY OF BIOLOGIC DRUGS IN THE CLINICAL PRACTICE IN THE BULGARIAN POPULATION OF PATIENTS SUFFERING FROM RHEUMATOID ARTHRITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1451.3-1451
Author(s):  
K. Kraev ◽  
M. Geneva-Popova ◽  
S. Popova
Keyword(s):  
Rheumatoid Arthritis ◽  
Clinical Practice ◽  
Disease Activity ◽  
Clinical Response ◽  
Neutralizing Antibodies ◽  
Tnf Alpha ◽  
Drug Bioavailability ◽  
Drug Induced ◽  
Etanercept Treatment ◽  
Markers Of Inflammation

Background:Biological drugs are protein derivatives that, as such, are highly immunogenic. In recent years there have been many conflicting opinions about the role of drug immunogenicity in clinical practice.Objectives:To evaluate the drug immunogenicity of TNF-alpha blocking drugs (etanercept and adalimumab) used to treat patients with rheumatoid arthritis. To determine whether their presence can alter the effect of treatment and to evaluate their role in the clinical practice of rheumatologists.Methods:121 patients with rheumatoid arthritis, as well as 31 healthy controls, similar in sex and age, were examined. They were all monitored at 0, 6, 12 and 24 months from the start of TNF-alpha blocker treatment. Demographics, vital signs, markers of inflammation such as C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and disease activity indices were examined at each visit, respectively. Drug-induced neutralizing antibodies, as well as drug bioavailability in patients treated with adalimumab, were examined by ELISA.Results:Drug-induced neutralizing antibodies to adalimumab were detected in 11.57% of patients at 6 month, in 17.64% of patients at 12 month, and 24.8% at 24 month. Drug-induced neutralizing antibodies to etanercept were not detected at 6 months, at 7.77% at 12 months, at 9.63% of patients at 24 months. Of the adalimumab patients who were having drug-induced antibodies, 92.59% had low drug bioavailability, while the remaining 7.41% of patients showed normal drug bioavailability despite the presence of drug-induced neutralizing antibodies. In terms of worsening of the disease activity, a positive correlation was found with the presence of drug antibodies - Pearson Correlation = 0.701, p = 0.001. Patients with poor clinical response and available drug antibodies receiving adalimumab were slightly more than those treated with etanercept at 12 and 24 months but the difference is non-significant-U = 0.527, p> 0.05 and U = 0.623, p> 0.05, respectively.Conclusion:Presence of drug-induced neutralizing antibodies in patients treated with adalimumab and etanercept has been associated with poor clinical response and worsening of the patient’s condition. Testing of drug-induced neutralizing antibodies as well as the drug bioavailability of the drug used can be used as reliable biomarkers in clinical rheumatology.References:[1]Benucci M., F.Li Gobbi, M. Meacii et al., “Antidrug antibodies against TNF-blocking agents: correlations between disese activity, hypersensitivity reactions, and different classes of immunoglobulins”, Biologics and Targets and Therapy, 2015: 9 7 -2.[2]Chen D., Y. Chen, W. Tsai et al., “ Significant associations of antidrug antibody levels with serum drug trough levels and therapeutic response of adalimumab and etanercept treatment in rheumatoid arthritis”, Ann Rheum Dis. 2015 Mar; 74 (3).[3]Kalden J. and H. Schulze-Koops, “ Immunogenicity and loss of response to TNF inhibitors: implications for rheumatoid arthritis treatment ”, Nature Reviews Rheumatology, 2017 volume 13, 707–718.[4]Wolf-Henning Boehnck, N. Brembilla, “ Immunogenicity of biological therapies: causes and consequences, ” Expert Review of Clinical Immunology, Vol 14, 2018, Issue 6, 513-523Disclosure of Interests:None declared

scholarly journals SAT0006 SIMULTANEOUS ANALYSIS OF ANTI-CCP, RHEUMATOID FACTOR, ANTI-PAD4 AND ANTI-CARBAMYLATED PROTEIN ANTIBODIES REVEALS INTERACTION EFFECTS WITH RESPONSE TO ANTI-TNF THERAPY IN RHEUMATOID ARTHRITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 933.2-934
Author(s):  
A. Julià ◽  
M. Lopez Lasanta ◽  
F. Blanco ◽  
A. Gómez ◽  
I. Haro ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Rheumatoid Factor ◽  
Clinical Response ◽  
Therapeutic Approach ◽  
Drug Response ◽  
Single Marker Analysis ◽  
Das28 Score ◽  
Positive Interaction ◽  
Single Marker ◽  
Necrosis Factor

Background:Blocking of the Tumor Necrosis Factor (TNF) activity is a successful therapeutic approach for 2 out of 3 Rheumatoid Arthritis patients. Identifying the patients that will not respond to this therapeutic approach is a major translational goal in RA. Association of seropositivity to rheumatoid factor (RF) or anti-cyclic-citrullinated antibodies (anti-CCP) with anti-TNF response has proven inconclusive, suggesting that other yet unexplored biomarkers could be more informative for this goal.Objectives:We tested the association of two recently introduced biomarkers in RA: anti-carbamylated protein antibodies (anti-CarP) and anti-peptidylarginine deiminase type 4 (anti-PAD4).Methods:A prospective cohort of n=80 RA patients starting anti-TNF therapy was recruited and levels for all four autoantibodies -RF, anti-CCP, anti-CarP and anti-PAD4- were measured at baseline. The change in DAS28 score between baseline and week 12 of therapy was used as the clinical endpoint.Results:Single marker-analysis showed no significant association with drug response. However, when testing for interactions between autoantibodies, we found highly significant associations with drug response. Anti-CCP and RF showed a positive interaction with the response to anti-TNF therapy (P=0.00068), and anti-PAD4 and antiCarP titers showed a negative interaction with the clinical response at week 12 (P=0.0062). Using an independent retrospective sample (n=199 patients), we validated the interaction between anti-CCP and RF with the clinical response to anti-TNF agents. (P=0.044).Conclusion:The results of this study show that interactions between antibodies are important in the response to anti-TNF therapy and suggest potential pathogenic relationships.Acknowledgments :We would like to thank the clinical researchers and patients participating in the IMID Consortium for their collaborationDisclosure of Interests:Antonio Julià: None declared, Maria Lopez Lasanta: None declared, Francisco Blanco: None declared, Antonio Gómez: None declared, Isabel Haro: None declared, Antonio Juan Mas: None declared, Alba Erra: None declared, Mª Luz García Vivar: None declared, Jordi Monfort: None declared, Simon Sánchez Fernandez: None declared, Isidoro González-Álvaro Grant/research support from: Roche Laboratories, Consultant of: Lilly, Sanofi, Paid instructor for: Lilly, Speakers bureau: Abbvie, MSD, Roche, Lilly, Mercedes Alperi-López: None declared, Raúl Castellanos: None declared, Antonio Fernandez-Nebro: None declared, Cesar Diaz Torne: None declared, Núria Palau: None declared, Raquel M Lastra: None declared, Jordi Lladós: None declared, Raimon Sanmarti: None declared, Sara Marsal: None declared

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