Towards Personalized Medicine in Rheumatoid Arthritis

References

• Symmons D, Turner G, Webb R, et al. The prevalence of rheumatoid arthritis in the United Kingdom: new estimates for a new century. Rheumatology. 2002;41(7):793–800. doi:10.1093/rheumatology/41.7.793
   PubMed Web of Science ®Google Scholar
• Chiu YM, Lu YP, Lan JL, Chen DY, Wang JD. Lifetime risks, life expectancy, and health care expenditures for rheumatoid arthritis: a nationwide cohort followed up from 2003 to 2016. Arthritis Rheumatol. 2021;73(5):750–758. doi:10.1002/art.41597
   PubMed Web of Science ®Google Scholar
• Smolen JS, Landewé R, Breedveld FC, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs. Ann Rheum Dis. 2010;69(6):964–975. doi:10.1136/ard.2009.126532
   PubMed Web of Science ®Google Scholar
• Nam JL, Takase-Minegishi K, Ramiro S, et al. Efficacy of biological disease-modifying antirheumatic drugs: a systematic literature review informing the 2016 update of the EULAR recommendations for the management of rheumatoid arthritis. Ann Rheum Dis. 2017;76(6):1113–1136. doi:10.1136/annrheumdis-2016-210713
   PubMed Web of Science ®Google Scholar
• guideline NG100 N. Rheumatoid Arthritis in Adults: Diagnosis and Management. London, UK: National Institute for Health and Care Excellence; 2018.
   Google Scholar
• England NH. Improving Outcomes through Personalised Medicine; 2016.
   Google Scholar
• Abrahams E. Right drug-right patient-right time: personalized medicine coalition. Clin Transl Sci. 2008;1(1):11–12. doi:10.1111/j.1752-8062.2008.00003.x
   PubMed Web of Science ®Google Scholar
• MacGregor AJ, Snieder H, Rigby AS, et al. Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis Rheum. 2000;43(1):30–37. doi:10.1002/1529-0131(200001)43:1<30::Aid-anr5>3.0.Co;2-b
   PubMed Web of Science ®Google Scholar
• Yarwood A, Huizinga TW, Worthington J. The genetics of rheumatoid arthritis: risk and protection in different stages of the evolution of RA. Rheumatology. 2016;55(2):199–209. doi:10.1093/rheumatology/keu323
   PubMed Web of Science ®Google Scholar
• van der Woude D, Houwing-Duistermaat JJ, Toes RE, et al. Quantitative heritability of anti-citrullinated protein antibody-positive and anti-citrullinated protein antibody-negative rheumatoid arthritis. Arthritis Rheum. 2009;60(4):916–923. doi:10.1002/art.24385
   PubMed Web of Science ®Google Scholar
• Doran MF, Pond GR, Crowson CS, O’Fallon WM, Gabriel SE. Trends in incidence and mortality in rheumatoid arthritis in Rochester, Minnesota, over a forty-year period. Arthritis Rheum. 2002;46(3):625–631. doi:10.1002/art.509
   PubMed Web of Science ®Google Scholar
• Symmons DP, Barrett EM, Bankhead CR, Scott DG, Silman AJ. The incidence of rheumatoid arthritis in the United Kingdom: results from the Norfolk Arthritis Register. Br J Rheumatol. 1994;33(8):735–739. doi:10.1093/rheumatology/33.8.735
   PubMedGoogle Scholar
• Ma MH, Ibrahim F, Walker D, et al. Remission in early rheumatoid arthritis: predicting treatment response. J Rheumatol. 2012;39(3):470–475. doi:10.3899/jrheum.110169
   PubMed Web of Science ®Google Scholar
• Coulthard LR, Taylor JC, Eyre S, et al. Genetic variants within the MAP kinase signalling network and anti-TNF treatment response in rheumatoid arthritis patients. Ann Rheumatic Dis. 2011;70(1):98–103. doi:10.1136/ard.2010.133249
   PubMed Web of Science ®Google Scholar
• Atzeni F, Bongiovanni S, Marchesoni A, et al. Predictors of response to anti-TNF therapy in RA patients with moderate or high DAS28 scores. Joint Bone Spine. 2014;81(1):37–40. doi:10.1016/j.jbspin.2013.04.005
   PubMed Web of Science ®Google Scholar
• Yamanaka H, Harigai M, Ishiguro N, et al. Trend of patient characteristics and its impact on the response to Adalimumab in patients with rheumatoid arthritis: post hoc time-course analysis of an all-case PMS in Japan. Mod Rheumatol. 2015;25(4):495–502. doi:10.3109/14397595.2014.994263
   PubMed Web of Science ®Google Scholar
• Mancarella L, Bobbio-Pallavicini F, Ceccarelli F, et al. Good clinical response, remission, and predictors of remission in rheumatoid arthritis patients treated with tumor necrosis factor-alpha blockers: the GISEA study. J Rheumatol. 2007;34(8):1670–1673.
   PubMed Web of Science ®Google Scholar
• Levitsky A, Brismar K, Hafström I, et al. Obesity is a strong predictor of worse clinical outcomes and treatment responses in early rheumatoid arthritis: results from the SWEFOT trial. RMD Open. 2017;3(2):e000458. doi:10.1136/rmdopen-2017-000458
   PubMedGoogle Scholar
• Hyrich KL, Watson KD, Silman AJ, Symmons DP. Predictors of response to anti-TNF-alpha therapy among patients with rheumatoid arthritis: results from the British society for rheumatology biologics register. Rheumatology. 2006;45(12):1558–1565. doi:10.1093/rheumatology/kel149
   PubMed Web of Science ®Google Scholar
• Fernández-Nebro A, Irigoyen MV, Ureña I, et al. Effectiveness, predictive response factors, and safety of anti-tumor necrosis factor (TNF) therapies in anti-TNF-naive rheumatoid arthritis. J Rheumatol. 2007;34(12):2334–2342.
   PubMed Web of Science ®Google Scholar
• Kleinert S, Tony HP, Krause A, et al. Impact of patient and disease characteristics on therapeutic success during Adalimumab treatment of patients with rheumatoid arthritis: data from a German noninterventional observational study. Rheumatol Int. 2012;32(9):2759–2767. doi:10.1007/s00296-011-2033-5
   PubMed Web of Science ®Google Scholar
• Sugiyama D, Nishimura K, Tamaki K, et al. Impact of smoking as a risk factor for developing rheumatoid arthritis: a meta-analysis of observational studies. Ann Rheum Dis. 2010;69(1):70–81. doi:10.1136/ard.2008.096487
   PubMed Web of Science ®Google Scholar
• Saevarsdottir S, Wedrén S, Seddighzadeh M, et al. Patients with early rheumatoid arthritis who smoke are less likely to respond to treatment with methotrexate and tumor necrosis factor inhibitors: observations from the epidemiological investigation of rheumatoid arthritis and the Swedish rheumatology register cohorts. Arthritis Rheum. 2011;63(1):26–36. doi:10.1002/art.27758
   PubMed Web of Science ®Google Scholar
• Chatzidionysiou K, Lukina G, Gabay C, et al. Smoking and response to rituximab in rheumatoid arthritis: results from an international European collaboration. Scand J Rheumatol. 2019;48(1):17–23. doi:10.1080/03009742.2018.1466363
   PubMed Web of Science ®Google Scholar
• Sokolove J, Wagner CA, Lahey LJ, et al. Increased inflammation and disease activity among current cigarette smokers with rheumatoid arthritis: a cross-sectional analysis of US veterans. Rheumatology. 2016;55(11):1969–1977. doi:10.1093/rheumatology/kew285
   PubMed Web of Science ®Google Scholar
• Adami G, Fassio A, Pistillo F, et al. Factors associated with radiographic progression in rheumatoid arthritis starting biological diseases modifying anti-rheumatic drugs (bDMARDs). Ther Adv Musculoskelet Dis. 2023;15:1759720x231174534. doi:10.1177/1759720x231174534
   Web of Science ®Google Scholar
• Kristensen LE, Bliddal H, Christensen R, et al. Is swollen to tender joint count ratio a new and useful clinical marker for biologic drug response in rheumatoid arthritis? Results from a Swedish cohort. Arthritis Care Res. 2014;66(2):173–179. doi:10.1002/acr.22107
   Web of Science ®Google Scholar
• Maldonado-Montoro M, Cañadas-Garre M, González-Utrilla A, Plaza-Plaza JC, Calleja-Hernández M. Genetic and clinical biomarkers of tocilizumab response in patients with rheumatoid arthritis. Pharmacol Res. 2016;111:264–271. doi:10.1016/j.phrs.2016.06.016
   PubMed Web of Science ®Google Scholar
• Gremese E, Carletto A, Padovan M, et al. Obesity and reduction of the response rate to anti-tumor necrosis factor α in rheumatoid arthritis: an approach to a personalized medicine. Arthritis Care Res. 2013;65(1):94–100. doi:10.1002/acr.21768
   PubMed Web of Science ®Google Scholar
• de Heredia FP, Gómez-Martínez S, Marcos A. Obesity, inflammation and the immune system. Proc Nutr Soc. 2012;71(2):332–338. doi:10.1017/s0029665112000092
   PubMed Web of Science ®Google Scholar
• Jani M, Chinoy H, Warren RB, et al. Clinical utility of random anti-tumor necrosis factor drug-level testing and measurement of antidrug antibodies on the long-term treatment response in rheumatoid arthritis. Arthritis Rheumatol. 2015;67(8):2011–2019. doi:10.1002/art.39169
   PubMed Web of Science ®Google Scholar
• Mould DR. The Pharmacokinetics of Biologics: a Primer. Dig Dis. 2015;33(Suppl 1):61–69. doi:10.1159/000437077
   PubMed Web of Science ®Google Scholar
• Ogata A, Atsumi T, Fukuda T, et al. Sustainable efficacy of switching from intravenous to subcutaneous tocilizumab monotherapy in patients with rheumatoid arthritis. Arthritis Care Res. 2015;67(10):1354–1362. doi:10.1002/acr.22598
   PubMed Web of Science ®Google Scholar
• Hope HF, Bluett J, Barton A, Hyrich KL, Cordingley L, Verstappen SM. Psychological factors predict adherence to methotrexate in rheumatoid arthritis; findings from a systematic review of rates, predictors and associations with patient-reported and clinical outcomes. RMD Open. 2016;2(1):e000171. doi:10.1136/rmdopen-2015-000171
   PubMedGoogle Scholar
• Bluett J, Morgan C, Thurston L, et al. Impact of inadequate adherence on response to subcutaneously administered anti-tumour necrosis factor drugs: results from the Biologics in rheumatoid arthritis genetics and genomics study syndicate cohort. Rheumatology. 2015;54(3):494–499. doi:10.1093/rheumatology/keu358
   PubMed Web of Science ®Google Scholar
• National Institute for Health and Care Excellence. NICE guideline [NG33]: tuberculosis; 2023. Available from: https://www.nice.org.uk/guidance/ng33/chapter/Recommendations. Accessed May 4, 2024.
   Google Scholar
• Drozdzik M, Rudas T, Pawlik A, Gornik W, Kurzawski M, Herczynska M. Reduced folate carrier-1 80G> A polymorphism affects methotrexate treatment outcome in rheumatoid arthritis. Pharmacogeno J. 2007;7(6):404–407. doi:10.1038/sj.tpj.6500438
   PubMed Web of Science ®Google Scholar
• Li X, Hu M, Li W, et al. The association between reduced folate carrier-1 gene 80G/A polymorphism and methotrexate efficacy or methotrexate related-toxicity in rheumatoid arthritis: a meta-analysis. Int Immunopharmacol. 2016;38:8–15. doi:10.1016/j.intimp.2016.05.012
   PubMed Web of Science ®Google Scholar
• Kung TN, Dennis J, Ma Y, et al. RFC1 80G> A is a genetic determinant of methotrexate efficacy in rheumatoid arthritis: a human genome epidemiologic review and meta‐analysis of observational studies. Arthritis Rheumatol. 2014;66(5):1111–1120. doi:10.1002/art.38331
   PubMed Web of Science ®Google Scholar
• Liu C, Batliwalla F, Li W, et al. Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-TNF treatment in rheumatoid arthritis. Mol Med. 2008;14(9–10):575–581. doi:10.2119/2008-00056.Liu
   PubMed Web of Science ®Google Scholar
• Padyukov L, Lampa J, Heimburger M, et al. Genetic markers for the efficacy of tumour necrosis factor blocking therapy in rheumatoid arthritis. Ann Rheumatic Dis. 2003;62(6):526. doi:10.1136/ard.62.6.526
   PubMed Web of Science ®Google Scholar
• Krintel SB, Palermo G, Johansen JS, et al. Investigation of single nucleotide polymorphisms and biological pathways associated with response to TNFα inhibitors in patients with rheumatoid arthritis. Pharmacogenet Genomics. 2012;22(8):577–589. doi:10.1097/FPC.0b013e3283544043
   PubMed Web of Science ®Google Scholar
• Acosta-Colman I, Palau N, Tornero J, et al. GWAS replication study confirms the association of PDE3A–SLCO1C1 with anti-TNF therapy response in rheumatoid arthritis. Pharmacogenomics. 2013;14(7):727–734. doi:10.2217/pgs.13.60
   PubMed Web of Science ®Google Scholar
• Plant D, Bowes J, Potter C, et al. Genome-wide association study of genetic predictors of anti-tumor necrosis factor treatment efficacy in rheumatoid arthritis identifies associations with polymorphisms at seven loci. Arthritis Rheum. 2011;63(3):645–653. doi:10.1002/art.30130
   PubMedGoogle Scholar
• Márquez A, Ferreiro-Iglesias A, Dávila-Fajardo CL, et al. Lack of validation of genetic variants associated with anti–tumor necrosis factor therapy response in rheumatoid arthritis: a genome-wide association study replication and meta-analysis. Arthritis Res Therapy. 2014;16(2):1–7. doi:10.1186/ar4504
   Web of Science ®Google Scholar
• Cui J, Saevarsdottir S, Thomson B, et al. Rheumatoid arthritis risk allele PTPRC is also associated with response to anti–tumor necrosis factor α therapy. Arthritis Rheum. 2010;62(7):1849–1861. doi:10.1002/art.27457
   PubMed Web of Science ®Google Scholar
• Plant D, Prajapati R, Hyrich KL, et al. Replication of association of the PTPRC gene with response to anti–tumor necrosis factor therapy in a large UK cohort. Arthritis Rheum. 2012;64(3):665–670. doi:10.1002/art.33381
   PubMedGoogle Scholar
• Ferreiro-Iglesias A, Montes A, Perez-Pampin E, et al. Replication of PTPRC as genetic biomarker of response to TNF inhibitors in patients with rheumatoid arthritis. Pharmacogeno J. 2016;16(2):137–140. doi:10.1038/tpj.2015.29
   PubMed Web of Science ®Google Scholar
• Lee YH, Bae SC. Associations between PTPRC rs10919563 A/G and FCGR2A R131H polymorphisms and responsiveness to TNF blockers in rheumatoid arthritis: a meta-analysis. Rheumatol Int. 2016;36(6):837–844. doi:10.1007/s00296-016-3476-5
   PubMed Web of Science ®Google Scholar
• Cui J, Stahl EA, Saevarsdottir S, et al. Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis. PLoS Genet. 2013;9(3):e1003394. doi:10.1371/journal.pgen.1003394
   PubMed Web of Science ®Google Scholar
• Ferreiro-Iglesias A, Montes A, Perez-Pampin E, et al. Evaluation of 12 GWAS-drawn SNPs as biomarkers of rheumatoid arthritis response to TNF inhibitors. A potential SNP association with response to etanercept. PLoS One. 2019;14(2):e0213073. doi:10.1371/journal.pone.0213073
   PubMed Web of Science ®Google Scholar
• Wang J, Bansal A, Martin M, et al. Genome-wide association analysis implicates the involvement of eight loci with response to tocilizumab for the treatment of rheumatoid arthritis. Pharmacogeno J. 2013;13(3):235–241. doi:10.1038/tpj.2012.8
   PubMed Web of Science ®Google Scholar
• International Conference on Harmonisation. Guidance on E15 pharmacogenomics definitions and sample coding; availability. Notice. Fed Regist. 2008;73(68):19074–19076.
   PubMedGoogle Scholar
• Massey J, Plant D, Hyrich K, et al. Genome-wide association study of response to tumour necrosis factor inhibitor therapy in rheumatoid arthritis. Pharmacogeno J. 2018;18(5):657–664. doi:10.1038/s41397-018-0040-6
   PubMed Web of Science ®Google Scholar
• Cordingley L, Prajapati R, Plant D, et al. Impact of psychological factors on subjective disease activity assessments in patients with severe rheumatoid arthritis. Arthritis Care Res. 2014;66(6):861–868. doi:10.1002/acr.22249
   PubMed Web of Science ®Google Scholar
• Hensor EMA, McKeigue P, Ling SF, et al. Validity of a two-component imaging-derived disease activity score for improved assessment of synovitis in early rheumatoid arthritis. Rheumatology. 2019;58(8):1400–1409. doi:10.1093/rheumatology/kez049
   PubMed Web of Science ®Google Scholar
• Gilani SS, Nair N, Plant D, et al. Pharmacogenetics of TNF inhibitor response in rheumatoid arthritis utilizing the two-component disease activity score. Pharmacogenomics. 2020;21(16):1151–1156. doi:10.2217/pgs-2020-0043
   PubMed Web of Science ®Google Scholar
• Lopez-Lasanta M, Julià A, Maymó J, et al. Variation at interleukin-6 receptor gene is associated to joint damage in rheumatoid arthritis. Arthritis Res Therapy. 2015;17(1):242. doi:10.1186/s13075-015-0737-8
   PubMedGoogle Scholar
• Kastbom A, Cöster L, Arlestig L, et al. Influence of FCGR3A genotype on the therapeutic response to rituximab in rheumatoid arthritis: an observational cohort study. BMJ Open. 2012;2(5):e001524. doi:10.1136/bmjopen-2012-001524
   PubMed Web of Science ®Google Scholar
• Hamada M, Tsunakawa Y, Jeon H, Yadav MK, Takahashi S. Role of MafB in macrophages. Exp Anim. 2020;69(1):1–10. doi:10.1538/expanim.19-0076
   PubMed Web of Science ®Google Scholar
• Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments. Genome Med. 2020;12(1):44. doi:10.1186/s13073-020-00742-5
   PubMed Web of Science ®Google Scholar
• Goldberg AD, Allis CD, Bernstein E. Epigenetics: a landscape takes shape. Cell. 2007;128(4):635–638. doi:10.1016/j.cell.2007.02.006
   PubMed Web of Science ®Google Scholar
• Jaenisch R, Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nature Genet. 2003;33(3):245–254. doi:10.1038/ng1089
   PubMedGoogle Scholar
• Nair N, Plant D, Verstappen SM, et al. Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis. Rheumatology. 2020;59(6):1364–1371. doi:10.1093/rheumatology/kez411
   PubMed Web of Science ®Google Scholar
• Gosselt HR, van Zelst BD, de Rotte MC, Hazes JM, de Jonge R, Heil SG. Higher baseline global leukocyte DNA methylation is associated with MTX non-response in early RA patients. Arthritis Res Ther. 2019;21(1):1–8. doi:10.1186/s13075-019-1936-5
   PubMedGoogle Scholar
• Gosselt HR, Vallerga CL, Mandaviya PR, et al. Epigenome wide association study of response to methotrexate in early rheumatoid arthritis patients. PLoS One. 2021;16(3):e0247709. doi:10.1371/journal.pone.0247709
   PubMed Web of Science ®Google Scholar
• Glossop JR, Nixon NB, Emes RD, et al. DNA methylation at diagnosis is associated with response to disease-modifying drugs in early rheumatoid arthritis. Epigenomics. 2017;9(4):419–428. doi:10.2217/epi-2016-0042
   PubMed Web of Science ®Google Scholar
• Plant D, Webster A, Nair N, et al. Differential methylation as a biomarker of response to etanercept in patients with rheumatoid arthritis. Arthritis Rheumatol. 2016;68(6):1353–1360. doi:10.1002/art.39590
   PubMed Web of Science ®Google Scholar
• Sode J, Krintel SB, Carlsen AL, et al. Plasma microRNA profiles in patients with early rheumatoid arthritis responding to Adalimumab plus methotrexate vs methotrexate alone: a placebo-controlled clinical trial. J Rheumatol. 2018;45(1):53–61. doi:10.3899/jrheum.170266
   PubMed Web of Science ®Google Scholar
• Krintel SB, Dehlendorff C, Hetland ML, et al. Prediction of treatment response to Adalimumab: a double-blind placebo-controlled study of circulating microRNA in patients with early rheumatoid arthritis. Pharmacogeno J. 2016;16(2):141–146. doi:10.1038/tpj.2015.30
   PubMed Web of Science ®Google Scholar
• Cheng P, Wang J. The potential of circulating microRNA‐125a and microRNA‐125b as markers for inflammation and clinical response to infliximab in rheumatoid arthritis patients. J Clin Lab Analysis. 2020;34(8):e23329. doi:10.1002/jcla.23329
   PubMed Web of Science ®Google Scholar
• Duroux-Richard I, Pers Y-M, Fabre S, et al. Circulating miRNA-125b is a potential biomarker predicting response to rituximab in rheumatoid arthritis. Med Inflam. 2014;2014:2. doi:10.1155/2014/342524
   Web of Science ®Google Scholar
• Liu Y, Han Y, Qu H, Fang J, Ye M, Yin W. Correlation of microRNA expression profile with clinical response to tumor necrosis factor inhibitor in treating rheumatoid arthritis patients: a prospective cohort study. J Clin Lab Analysis. 2019;33(7):e22953. doi:10.1002/jcla.22953
   PubMed Web of Science ®Google Scholar
• Castro-Villegas C, Pérez-Sánchez C, Escudero A, et al. Circulating miRNAs as potential biomarkers of therapy effectiveness in rheumatoid arthritis patients treated with anti-TNFα. Arthritis Res Ther. 2015;17(1):1–15. doi:10.1186/s13075-015-0555-z
   PubMedGoogle Scholar
• Cavalli G, Heard E. Advances in epigenetics link genetics to the environment and disease. Nature. 2019;571(7766):489–499. doi:10.1038/s41586-019-1411-0
   PubMed Web of Science ®Google Scholar
• Tessarz P, Kouzarides T. Histone core modifications regulating nucleosome structure and dynamics. Nat Rev Mol Cell Biol. 2014;15(11):703–708. doi:10.1038/nrm3890
   PubMed Web of Science ®Google Scholar
• Nair N, Wilson AG. Assessing the potential of epigenetic targets as biomarkers in the diagnosis and treatment of rheumatoid arthritis. Expert Rev Clin Immunol. 2023;19(5):483–488. doi:10.1080/1744666x.2023.2193686
   PubMed Web of Science ®Google Scholar
• Araki Y, Mimura T. The mechanisms underlying chronic inflammation in rheumatoid arthritis from the perspective of the epigenetic landscape. J Immunol Res. 2016;2016:1. doi:10.1155/2016/6290682
   Web of Science ®Google Scholar
• Wada TT, Araki Y, Sato K, et al. Aberrant histone acetylation contributes to elevated interleukin-6 production in rheumatoid arthritis synovial fibroblasts. Biochem Biophys Res Commun. 2014;444(4):682–686. doi:10.1016/j.bbrc.2014.01.195
   PubMed Web of Science ®Google Scholar
• Bogunia-Kubik K, Wysoczańska B, Piątek D, Iwaszko M, Ciechomska M, Świerkot J. Significance of polymorphism and expression of miR-146a and NFkB1 genetic variants in patients with rheumatoid arthritis. Archivum Immunol Et Ther Experiment. 2016;64(S1):131–136. doi:10.1007/s00005-016-0443-5
   PubMedGoogle Scholar
• Evangelatos G, Fragoulis GE, Koulouri V, Lambrou GI. MicroRNAs in rheumatoid arthritis: from pathogenesis to clinical impact. Autoimmunity Rev. 2019;18(11):102391. doi:10.1016/j.autrev.2019.102391
   PubMed Web of Science ®Google Scholar
• Liu T, Zhang L, Joo D, Sun S-C. NF-κB signaling in inflammation. Signal Transd Target Ther. 2017;2(1):1–9. doi:10.1038/sigtrans.2017.23
   Web of Science ®Google Scholar
• Lequerré T, Gauthier-Jauneau A-C, Bansard C, et al. Gene profiling in white blood cells predicts infliximab responsiveness in rheumatoid arthritis. Arthritis Res Ther. 2006;8(4):1–11. doi:10.1186/ar1990
   Web of Science ®Google Scholar
• Tanino M, Matoba R, Nakamura S, et al. Prediction of efficacy of anti-TNF biologic agent, infliximab, for rheumatoid arthritis patients using a comprehensive transcriptome analysis of white blood cells. Biochem Biophys Res Commun. 2009;387(2):261–265. doi:10.1016/j.bbrc.2009.06.149
   PubMed Web of Science ®Google Scholar
• Julià A, Erra A, Palacio C, et al. An eight-gene blood expression profile predicts the response to infliximab in rheumatoid arthritis. PLoS One. 2009;4(10):e7556. doi:10.1371/journal.pone.0007556
   PubMed Web of Science ®Google Scholar
• Stuhlmüller B, Häupl T, Hernandez MM, et al. CD11c as a transcriptional biomarker to predict response to anti-TNF monotherapy with Adalimumab in patients with rheumatoid arthritis. Clin Pharmacol Ther. 2010;87(3):311–321. doi:10.1038/clpt.2009.244
   PubMed Web of Science ®Google Scholar
• van Baarsen LG, Wijbrandts CA, Rustenburg F, et al. Regulation of IFN response gene activity during infliximab treatment in rheumatoid arthritis is associated with clinical response to treatment. Arthritis Res Ther. 2010;12(1):1–10. doi:10.1186/ar2912
   Web of Science ®Google Scholar
• Toonen EJ, Gilissen C, Franke B, et al. Validation study of existing gene expression signatures for anti-TNF treatment in patients with rheumatoid arthritis. PLoS One. 2012;7(3):e33199. doi:10.1371/journal.pone.0033199
   PubMed Web of Science ®Google Scholar
• Dennis G, Holweg CT, Kummerfeld SK, et al. Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics. Arthritis Res Ther. 2014;16(2):1–18. doi:10.1186/ar4555
   Web of Science ®Google Scholar
• Wright HL, Thomas HB, Moots RJ, Edwards SW. Interferon gene expression signature in rheumatoid arthritis neutrophils correlates with a good response to TNFi therapy. Rheumatology. 2015;54(1):188–193. doi:10.1093/rheumatology/keu299
   PubMed Web of Science ®Google Scholar
• Smith SL, Eyre S, Yarwood A, et al. Investigating CD11c expression as a potential genomic biomarker of response to TNF inhibitor biologics in whole blood rheumatoid arthritis samples. Arthritis Res Ther. 2015;17(1):1–7. doi:10.1186/s13075-015-0868-y
   PubMedGoogle Scholar
• Oswald M, Curran ME, Lamberth SL, et al. Modular analysis of peripheral blood gene expression in rheumatoid arthritis captures reproducible gene expression changes in tumor necrosis factor responders. Arthritis Rheumatol. 2015;67(2):344–351. doi:10.1002/art.38947
   PubMed Web of Science ®Google Scholar
• Spiliopoulou A, Colombo M, Plant D, et al. Association of response to TNF inhibitors in rheumatoid arthritis with quantitative trait loci for CD40 and CD39. Ann Rheumatic Dis. 2019;78(8):1055–1061. doi:10.1136/annrheumdis-2018-214877
   PubMed Web of Science ®Google Scholar
• Oliver J, Nair N, Orozco G, et al. Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment. Arthritis Res Therapy. 2021;23(1):80. doi:10.1186/s13075-021-02451-9
   PubMed Web of Science ®Google Scholar
• Cai Y, Xu K, Aihaiti Y, et al. Derlin-1, as a potential early predictive biomarker for nonresponse to infliximab treatment in rheumatoid arthritis, is related to autophagy. Front Immunol. 2022;12:795912. doi:10.3389/fimmu.2021.795912
   PubMed Web of Science ®Google Scholar
• Sanayama Y, Ikeda K, Saito Y, et al. Prediction of therapeutic responses to tocilizumab in patients with rheumatoid arthritis: biomarkers identified by analysis of gene expression in peripheral blood mononuclear cells using genome‐wide DNA microarray. Arthritis Rheumatol. 2014;66(6):1421–1431. doi:10.1002/art.38400
   PubMed Web of Science ®Google Scholar
• Teitsma XM, Jacobs JW, Mokry M, et al. Identification of differential co-expressed gene networks in early rheumatoid arthritis achieving sustained drug-free remission after treatment with a tocilizumab-based or methotrexate-based strategy. Arthritis Res Ther. 2017;19(1):1–10. doi:10.1186/s13075-017-1378-x
   PubMedGoogle Scholar
• Yokoyama-Kokuryo W, Yamazaki H, Takeuchi T, et al. Identification of molecules associated with response to Abatacept in patients with rheumatoid arthritis. Arthritis Res Ther. 2020;22(1):1–8. doi:10.1186/s13075-020-2137-y
   PubMed Web of Science ®Google Scholar
• Thurlings RM, Boumans M, Tekstra J, et al. Relationship between the type I interferon signature and the response to rituximab in rheumatoid arthritis patients. Arthritis Rheum. 2010;62(12):3607–3614. doi:10.1002/art.27702
   PubMedGoogle Scholar
• Raterman HG, Vosslamber S, de Ridder S, et al. The interferon type I signature towards prediction of non-response to rituximab in rheumatoid arthritis patients. Arthritis Res Ther. 2012;14(2):R95. doi:10.1186/ar3819
   PubMed Web of Science ®Google Scholar
• Sellam J, Marion‐Thore S, Dumont F, et al. Use of whole‐blood transcriptomic profiling to highlight several pathophysiologic pathways associated with response to rituximab in patients with rheumatoid arthritis: data from a randomized, controlled, open‐label trial. Arthritis Rheumatol. 2014;66(8):2015–2025. doi:10.1002/art.38671
   PubMed Web of Science ®Google Scholar
• Nakamura S, Suzuki K, Iijima H, et al. Identification of baseline gene expression signatures predicting therapeutic responses to three biologic agents in rheumatoid arthritis: a retrospective observational study. Arthritis Res Ther. 2016;18(1):1–12. doi:10.1186/s13075-016-1052-8
   PubMedGoogle Scholar
• Triaille C, Durez P, Sokolova T, et al. Common transcriptomic effects of Abatacept and other DMARDs on rheumatoid arthritis synovial tissue. Front Immunol. 2021;12:724895. doi:10.3389/fimmu.2021.724895
   PubMed Web of Science ®Google Scholar
• Rivellese F, Nerviani A, Giorli G, et al. Stratification of biological therapies by pathobiology in biologic-naive patients with rheumatoid arthritis (STRAP and STRAP-EU): two parallel, open-label, biopsy-driven, randomised trials. Lancet Rheumatol. 2023;5(11):e648–e659. doi:10.1016/S2665-9913(23)00241-2
   PubMedGoogle Scholar
• Humby F, Durez P, Buch MH, et al. Rituximab versus tocilizumab in anti-TNF inadequate responder patients with rheumatoid arthritis (R4RA): 16-week outcomes of a stratified, biopsy-driven, multicentre, open-label, Phase 4 randomised controlled trial. Lancet. 2021;397(10271):305–317. doi:10.1016/S0140-6736(20)32341-2
   PubMed Web of Science ®Google Scholar
• Sobsey CA, Ibrahim S, Richard VR, et al. Targeted and untargeted proteomics approaches in biomarker development. Proteomics. 2020;20(9):1900029. doi:10.1002/pmic.201900029
   PubMed Web of Science ®Google Scholar
• Lee AN, Beck CE, Hall M. Rheumatoid factor and anti-CCP autoantibodies in rheumatoid arthritis: a review. Clin Lab Sci. 2008;21(1):15.
   PubMedGoogle Scholar
• Julià A, López-Lasanta M, Blanco F, et al. Interactions between rheumatoid arthritis antibodies are associated with the response to anti-tumor necrosis factor therapy. BMC Musculoskel Disorder. 2021;22(1):1–7. doi:10.1186/s12891-021-04248-y
   PubMed Web of Science ®Google Scholar
• Courvoisier DS, Chatzidionysiou K, Mongin D, et al. The impact of seropositivity on the effectiveness of biologic anti-rheumatic agents: results from a collaboration of 16 registries. Rheumatology. 2020;60(2):820–828. doi:10.1093/rheumatology/keaa393
   Web of Science ®Google Scholar
• Bird P, Hall S, Nash P, et al. Treatment outcomes in patients with seropositive versus seronegative rheumatoid arthritis in Phase III randomised clinical trials of tofacitinib. RMD Open. 2019;5(1):e000742. doi:10.1136/rmdopen-2018-000742
   PubMed Web of Science ®Google Scholar
• Genovese MC, Fleischmann R, Kivitz A, et al. Efficacy and safety of sarilumab in combination with csDMARDs or as monotherapy in subpopulations of patients with moderately to severely active rheumatoid arthritis in three phase III randomized, controlled studies. Arthritis Res Ther. 2020;22(1):139. doi:10.1186/s13075-020-02194-z
   PubMed Web of Science ®Google Scholar
• Isaacs JD, Cohen SB, Emery P, et al. Effect of baseline rheumatoid factor and anticitrullinated peptide antibody serotype on rituximab clinical response: a meta-analysis. Ann Rheum Dis. 2013;72(3):329–336. doi:10.1136/annrheumdis-2011-201117
   PubMed Web of Science ®Google Scholar
• Halvorsen EH, Haavardsholm EA, Pollmann S, et al. Serum IgG antibodies to peptidylarginine deiminase 4 predict radiographic progression in patients with rheumatoid arthritis treated with tumour necrosis factor-alpha blocking agents. Ann Rheum Dis. 2009;68(2):249–252. doi:10.1136/ard.2008.094490
   PubMed Web of Science ®Google Scholar
• Ferraccioli G, Tolusso B, Bobbio-Pallavicini F, et al. Biomarkers of good EULAR response to the B cell depletion therapy in all seropositive rheumatoid arthritis patients: clues for the pathogenesis. PLoS One. 2012;7(7):e40362. doi:10.1371/journal.pone.0040362
   PubMed Web of Science ®Google Scholar
• de Moel EC, Derksen VFAM, Stoeken G, et al. Baseline autoantibody profile in rheumatoid arthritis is associated with early treatment response but not long-term outcomes. Arthritis Res Ther. 2018;20(1):33. doi:10.1186/s13075-018-1520-4
   PubMedGoogle Scholar
• Darrah E, Yu F, Cappelli LC, Rosen A, O’Dell JR, Mikuls TR. Association of baseline peptidylarginine deiminase 4 autoantibodies with favorable response to treatment escalation in rheumatoid arthritis. Arthritis Rheumatol. 2019;71(5):696–702. doi:10.1002/art.40791
   PubMed Web of Science ®Google Scholar
• Lourido L, Ruiz-Romero C, Picchi F, et al. Association of Serum Anti-Centromere Protein F Antibodies with Clinical Response to Infliximab in Patients with Rheumatoid Arthritis: A Prospective Study. Elsevier; 2020:1101–1108.
   Google Scholar
• Kumar R, Piantoni S, Boldini M, et al. Anti-carbamylated protein antibodies as a clinical response predictor in rheumatoid arthritis patients treated with Abatacept. Clin Exp Rheumatol. 2021;39(1):91–97. doi:10.55563/clinexprheumatol/g8xqxr
   PubMed Web of Science ®Google Scholar
• Fabre S, Dupuy AM, Dossat N, et al. Protein biochip array technology for cytokine profiling predicts etanercept responsiveness in rheumatoid arthritis. Clin Exp Immunol. 2008;153(2):188–195. doi:10.1111/j.1365-2249.2008.03691.x
   PubMed Web of Science ®Google Scholar
• Trocmé C, Marotte H, Baillet A, et al. Apolipoprotein A-I and platelet factor 4 are biomarkers for infliximab response in rheumatoid arthritis. Ann Rheum Dis. 2009;68(8):1328–1333. doi:10.1136/ard.2008.093153
   PubMed Web of Science ®Google Scholar
• Hueber W, Tomooka BH, Batliwalla F, et al. Blood autoantibody and cytokine profiles predict response to anti-tumor necrosis factor therapy in rheumatoid arthritis. Arthritis Res Ther. 2009;11(3):R76. doi:10.1186/ar2706
   PubMed Web of Science ®Google Scholar
• Fabre S, Guisset C, Tatem L, et al. Protein biochip array technology to monitor rituximab in rheumatoid arthritis. Clin Exp Immunol. 2009;155(3):395–402. doi:10.1111/j.1365-2249.2008.03804.x
   PubMed Web of Science ®Google Scholar
• Hirata S, Marotta A, Gui Y, Hanami K, Tanaka Y. Serum 14-3-3η level is associated with severity and clinical outcomes of rheumatoid arthritis, and its pretreatment level is predictive of DAS28 remission with tocilizumab. Arthritis Res Ther. 2015;17(1):280. doi:10.1186/s13075-015-0799-7
   PubMedGoogle Scholar
• Uno K, Yoshizaki K, Iwahashi M, et al. Pretreatment Prediction of individual rheumatoid arthritis patients’ response to anti-cytokine therapy using serum cytokine/chemokine/soluble receptor biomarkers. PLoS One. 2015;10(7):e0132055. doi:10.1371/journal.pone.0132055
   PubMed Web of Science ®Google Scholar
• Obry A, Hardouin J, Lequerré T, et al. Identification of 7 Proteins in sera of RA patients with potential to predict ETA/MTX treatment response. Theranostics. 2015;5(11):1214–1224. doi:10.7150/thno.12403
   PubMed Web of Science ®Google Scholar
• Han BK, Kuzin I, Gaughan JP, Olsen NJ, Bottaro A. Baseline CXCL10 and CXCL13 levels are predictive biomarkers for tumor necrosis factor inhibitor therapy in patients with moderate to severe rheumatoid arthritis: a pilot, prospective study. Arthritis Res Ther. 2016;18:93. doi:10.1186/s13075-016-0995-0
   PubMed Web of Science ®Google Scholar
• Folkersen L, Brynedal B, Diaz-Gallo LM, et al. Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study. Mol Med. 2016;22(1):322–328. doi:10.2119/molmed.2016.00078
   PubMedGoogle Scholar
• Rinaudo-Gaujous M, Blasco-Baque V, Miossec P, et al. Infliximab induced a dissociated response of severe periodontal biomarkers in rheumatoid arthritis patients. J Clin Med. 2019;8(5):751. doi:10.3390/jcm8050751
   PubMed Web of Science ®Google Scholar
• Chen J, Tang MS, Xu LC, et al. Proteomic analysis of biomarkers predicting the response to triple therapy in patients with rheumatoid arthritis. Biomed Pharmacother. 2019;116:109026. doi:10.1016/j.biopha.2019.109026
   PubMed Web of Science ®Google Scholar
• Ling SF, Nair N, Verstappen SM, et al. Proteomic analysis to define predictors of treatment response to Adalimumab or methotrexate in rheumatoid arthritis patients. Pharmacogeno J. 2020;20(3):516–523. doi:10.1038/s41397-019-0139-4
   PubMed Web of Science ®Google Scholar
• Zhao J, Ye X, Zhang Z. The predictive value of serum soluble ICAM-1 and CXCL13 in the therapeutic response to TNF inhibitor in rheumatoid arthritis patients who are refractory to csDMARDs. Clin Rheumatol. 2020;39(9):2573–2581. doi:10.1007/s10067-020-05043-1
   PubMed Web of Science ®Google Scholar
• Ling SF, Yap CF, Nair N, et al. A proteomics study of rheumatoid arthritis patients on etanercept identifies putative biomarkers associated with clinical outcome measures. Rheumatology. 2023;(Supplement_2). doi:10.1093/rheumatology/kead321
   Google Scholar
• Roessner U, Bowne J. What is metabolomics all about? Biotechniques. 2009;46(5):363–365. doi:10.2144/000113133
   PubMed Web of Science ®Google Scholar
• Gosselt HR, Muller IB, Jansen G, et al. Identification of metabolic biomarkers in relation to methotrexate response in early rheumatoid arthritis. J Pers Med. 2020;10(4):271. doi:10.3390/jpm10040271
   PubMed Web of Science ®Google Scholar
• Medcalf MR, Bantis LE, Shi P, et al. Plasma metabolomic profiling as a tool to identify predictive biomarkers of methotrexate efficacy in rheumatoid arthritis. Semin Arthritis Rheumatism. 2022;56:152056. doi:10.1016/j.semarthrit.2022.152056
   PubMed Web of Science ®Google Scholar
• Kapoor SR, Filer A, Fitzpatrick MA, et al. Metabolic profiling predicts response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis. Arthritis Rheum. 2013;65(6):1448–1456. doi:10.1002/art.37921
   PubMedGoogle Scholar
• Takahashi S, Saegusa J, Onishi A, Morinobu A. Biomarkers identified by serum metabolomic analysis to predict biologic treatment response in rheumatoid arthritis patients. Rheumatology. 2019;58(12):2153–2161. doi:10.1093/rheumatology/kez199
   PubMed Web of Science ®Google Scholar
• Priori R, Casadei L, Valerio M, Scrivo R, Valesini G, Manetti C. ¹H-NMR-Based metabolomic study for identifying serum profiles associated with the response to etanercept in patients with rheumatoid arthritis. PLoS One. 2015;10(11):e0138537. doi:10.1371/journal.pone.0138537
   PubMed Web of Science ®Google Scholar
• Cuppen BV, Fu J, van Wietmarschen HA, et al. Exploring the inflammatory metabolomic profile to predict response to TNF-α inhibitors in rheumatoid arthritis. PLoS One. 2016;11(9):e0163087. doi:10.1371/journal.pone.0163087
   PubMed Web of Science ®Google Scholar
• Murillo-Saich JD, Diaz-Torne C, Ortiz MA, et al. Metabolomics profiling predicts outcome of tocilizumab in rheumatoid arthritis: an exploratory study. Metabolomics. 2021;17(9):74. doi:10.1007/s11306-021-01822-2
   PubMed Web of Science ®Google Scholar
• Teitsma XM, Yang W, Jacobs JW, et al. Baseline metabolic profiles of early rheumatoid arthritis patients achieving sustained drug-free remission after initiating treat-to-target tocilizumab, methotrexate, or the combination: insights from systems biology. Arthritis Res Ther. 2018;20(1):1–11. doi:10.1186/s13075-018-1729-2
   PubMedGoogle Scholar
• Dudka I, Chachaj A, Sebastian A, et al. Metabolomic profiling reveals plasma GlycA and GlycB as a potential biomarkers for treatment efficiency in rheumatoid arthritis. J Pharma Biomed Analysis. 2021;197:113971. doi:10.1016/j.jpba.2021.113971
   PubMed Web of Science ®Google Scholar
• Sweeney SR, Kavanaugh A, Lodi A, et al. Metabolomic profiling predicts outcome of rituximab therapy in rheumatoid arthritis. RMD Open. 2016;2(2):e000289. doi:10.1136/rmdopen-2016-000289
   PubMedGoogle Scholar
• Kang J-S, Lee M-H. Overview of therapeutic drug monitoring. Korean J Int Med. 2009;24(1):1. doi:10.3904/kjim.2009.24.1.1
   PubMedGoogle Scholar
• Rosas J, Llinares-Tello F, de la Torre I, et al. Clinical relevance of monitoring serum levels of Adalimumab in patients with rheumatoid arthritis in daily practice. Clin Exp Rheumatol. 2014;32(6):942–948.
   PubMed Web of Science ®Google Scholar
• van den Bemt BJ, den Broeder AA, Wolbink GJ, et al. The combined use of disease activity and infliximab serum trough concentrations for early prediction of (non-)response to infliximab in rheumatoid arthritis. Br J Clin Pharmacol. 2013;76(6):939–945. doi:10.1111/bcp.12142
   PubMed Web of Science ®Google Scholar
• Jurado T, Plasencia-Rodríguez C, Martínez-Feito A, et al. Predictive value of serum infliximab levels at induction phase in rheumatoid arthritis patients. Open Rheumatol J. 2017;11:75. doi:10.2174/1874312901711010075
   PubMedGoogle Scholar
• Takeuchi T, Miyasaka N, Inoue K, Abe T, Koike T. Impact of trough serum level on radiographic and clinical response to infliximab plus methotrexate in patients with rheumatoid arthritis: results from the RISING study. Mod Rheumatol. 2009;19(5):478–487. doi:10.3109/s10165-009-0195-8
   PubMed Web of Science ®Google Scholar
• Jamnitski A, Krieckaert C, Nurmohamed M, et al. Patients non-responding to etanercept obtain lower etanercept concentrations compared with responding patients. Ann Rheumatic Dis. 2012;71(1):88–91. doi:10.1136/annrheumdis-2011-200184
   PubMed Web of Science ®Google Scholar
• Arad U, Elkayam O. Association of serum tocilizumab trough concentrations with clinical disease activity index scores in adult patients with rheumatoid arthritis. J Rheumatol. 2019;46(12):1577–1581. doi:10.3899/jrheum.181431
   PubMed Web of Science ®Google Scholar
• Kneepkens E, van den Oever I, Plasencia C, et al. Serum tocilizumab trough concentration can be used to monitor systemic IL-6 receptor blockade in patients with rheumatoid arthritis: a prospective observational cohort study. Scand J Rheumatol. 2017;46(2):87–94. doi:10.1080/03009742.2016.1183039
   PubMed Web of Science ®Google Scholar
• Ruscitti P, Sinigaglia L, Cazzato M, et al. Dose adjustments and discontinuation in TNF inhibitors treated patients: when and how. A systematic review of literature. Rheumatology. 2018;57(Supplement_7):vii23–vii31. doi:10.1093/rheumatology/key132
   PubMedGoogle Scholar
• Balsa A, Sanmarti R, Rosas J, et al. Drug immunogenicity in patients with inflammatory arthritis and secondary failure to tumour necrosis factor inhibitor therapies: the REASON study. Rheumatology. 2018;57(4):688–693. doi:10.1093/rheumatology/kex474
   PubMed Web of Science ®Google Scholar
• Strand V, Goncalves J, Isaacs JD. Immunogenicity of biologic agents in rheumatology. Nat Rev Rheumatol. 2021;17(2):81–97. doi:10.1038/s41584-020-00540-8
   PubMed Web of Science ®Google Scholar
• Bartelds GM, Krieckaert CL, Nurmohamed MT, et al. Development of antidrug antibodies against Adalimumab and association with disease activity and treatment failure during long-term follow-up. JAMA. 2011;305(14):1460–1468. doi:10.1001/jama.2011.406
   PubMed Web of Science ®Google Scholar
• Ducourau E, Mulleman D, Paintaud G, et al. Antibodies toward infliximab are associated with low infliximab concentration at treatment initiation and poor infliximab maintenance in rheumatic diseases. Arthritis Res Ther. 2011;13(3):1–7. doi:10.1186/ar3386
   Web of Science ®Google Scholar
• Strand V, Balsa A, Al-Saleh J, et al. Immunogenicity of biologics in chronic inflammatory diseases: a systematic review. BioDrugs. 2017;31(4):299–316. doi:10.1007/s40259-017-0231-8
   PubMed Web of Science ®Google Scholar
• Wells AF, Parrino J, Mangan EK, et al. Immunogenicity of sarilumab monotherapy in patients with rheumatoid arthritis who were inadequate responders or intolerant to disease-modifying antirheumatic drugs. Rheumatol Ther. 2019;6(3):339–352. doi:10.1007/s40744-019-0157-3
   PubMed Web of Science ®Google Scholar
• Xu C, Su Y, Paccaly A, Kanamaluru V. Population pharmacokinetics of sarilumab in patients with rheumatoid arthritis. Clin Pharmacokinet. 2019;58(11):1455–1467. doi:10.1007/s40262-019-00765-1
   PubMed Web of Science ®Google Scholar
• Wincup C, Dunn N, Ruetsch-Chelli C, et al. Anti-rituximab antibodies demonstrate neutralizing capacity, associate with lower circulating drug levels and earlier relapse in lupus. Rheumatology. 2022;62(7):2601–2610. doi:10.1093/rheumatology/keac608
   Web of Science ®Google Scholar
• Moots RJ, Xavier RM, Mok CC, et al. The impact of anti-drug antibodies on drug concentrations and clinical outcomes in rheumatoid arthritis patients treated with Adalimumab, etanercept, or infliximab: results from a multinational, real-world clinical practice, non-interventional study. PLoS One. 2017;12:4.
   Web of Science ®Google Scholar
• Maid PJ, Xavier R, Real RM, et al. Incidence of antidrug antibodies in rheumatoid arthritis patients from Argentina treated with Adalimumab, etanercept, or infliximab in a real-world setting. JCR. 2018;24(4):177–182.
   Google Scholar
• Quistrebert J, Hässler S, Bachelet D, et al. Incidence and risk factors for Adalimumab and infliximab anti-drug antibodies in rheumatoid arthritis: a European retrospective multicohort analysis. Semin Arthritis Rheum. 2019;48(6):967–975. doi:10.1016/j.semarthrit.2018.10.006
   PubMed Web of Science ®Google Scholar
• Burmester GR, Choy E, Kivitz A, et al. Low immunogenicity of tocilizumab in patients with rheumatoid arthritis. Ann Rheum Dis. 2017;76(6):1078–1085. doi:10.1136/annrheumdis-2016-210297
   PubMed Web of Science ®Google Scholar
• Sigaux J, Hamze M, Daien C, et al. Immunogenicity of tocilizumab in patients with rheumatoid arthritis. Joint Bone Spine. 2017;84(1):39–45. doi:10.1016/j.jbspin.2016.04.013
   PubMed Web of Science ®Google Scholar
• Genovese MC, Fleischmann R, Kivitz AJ, et al. Sarilumab plus methotrexate in patients with active rheumatoid arthritis and inadequate response to methotrexate: results of a phase III study. Arthritis Rheumatol. 2015;67(6):1424–1437. doi:10.1002/art.39093
   PubMed Web of Science ®Google Scholar
• Thurlings RM, Teng O, Vos K, et al. Clinical response, pharmacokinetics, development of human anti-chimaeric antibodies, and synovial tissue response to rituximab treatment in patients with rheumatoid arthritis. Ann Rheum Dis. 2010;69(2):409–412. doi:10.1136/ard.2009.109041
   PubMed Web of Science ®Google Scholar
• Bitoun S, Hässler S, Ternant D, et al. Response to biologic drugs in patients with rheumatoid arthritis and antidrug antibodies. JAMA Network Open. 2023;6(7):e2323098–e2323098. doi:10.1001/jamanetworkopen.2023.23098
   PubMed Web of Science ®Google Scholar
• Jamnitski A, Bartelds GM, Nurmohamed MT, et al. The presence or absence of antibodies to infliximab or Adalimumab determines the outcome of switching to etanercept. Ann Rheum Dis. 2011;70(2):284–288. doi:10.1136/ard.2010.135111
   PubMed Web of Science ®Google Scholar
• Ucar E, Gorostiza Í, Gόmez C, et al. SAT0150 Prospective, Intervention, Multicenter Study of Utility of Biologic Drug Monitoring with Respect to the Efficacy and Cost of Adalimumab Tapering in Patients with Rheumatic Diseases: Preliminary Results of INGEBIO Study. BMJ Publishing Group Ltd; 2017.
   Google Scholar
• Syversen SW, Goll GL, Jørgensen KK, et al. Therapeutic drug monitoring of infliximab compared to standard clinical treatment with infliximab: study protocol for a randomised, controlled, open, parallel-group, Phase IV study (the NOR-DRUM study). Trials. 2020;21(1):13. doi:10.1186/s13063-019-3734-4
   PubMed Web of Science ®Google Scholar
• (NICE) NIfHaCE. Therapeutic monitoring of TNF-alpha inhibitors in rheumatoid arthritis. Available from: https://www.nice.org.uk/guidance/dg36. Accessed December 19, 2023.
   Google Scholar
• Krieckaert CL, van Tubergen A, Gehin JE, et al. EULAR points to consider for therapeutic drug monitoring of biopharmaceuticals in inflammatory rheumatic and musculoskeletal diseases. Ann Rheumatic Dis. 2023;82(1):65–73. doi:10.1136/annrheumdis-2022-222155
   PubMed Web of Science ®Google Scholar
• Johnson KB, Wei WQ, Weeraratne D, et al. Precision medicine, AI, and the future of personalized health care. Clin Transl Sci. 2021;14(1):86–93. doi:10.1111/cts.12884
   PubMed Web of Science ®Google Scholar
• Deo RC. Machine learning in medicine. Circulation. 2015;132(20):1920–1930. doi:10.1161/CIRCULATIONAHA.115.001593
   PubMed Web of Science ®Google Scholar
• Mirza B, Wang W, Wang J, Choi H, Chung NC, Ping P. Machine learning and integrative analysis of biomedical big data. Genes. 2019;10(2):87. doi:10.3390/genes10020087
   PubMed Web of Science ®Google Scholar
• Westerlind H, Maciejewski M, Frisell T, Jelinsky SA, Ziemek D, Askling J. What Is the persistence to methotrexate in rheumatoid arthritis, and does machine learning outperform hypothesis-based approaches to its prediction? ACR Open Rheumatol. 2021;3(7):457–463. doi:10.1002/acr2.11266
   PubMedGoogle Scholar
• Miyoshi F, Honne K, Minota S, Okada M, Ogawa N, Mimura T. A novel method predicting clinical response using only background clinical data in RA patients before treatment with infliximab. Mod Rheumatol. 2016;26(6):813–816. doi:10.3109/14397595.2016.1168536
   PubMed Web of Science ®Google Scholar
• Koo BS, Eun S, Shin K, et al. Machine learning model for identifying important clinical features for predicting remission in patients with rheumatoid arthritis treated with biologics. Arthritis Res Ther. 2021;23(1):178. doi:10.1186/s13075-021-02567-y
   PubMed Web of Science ®Google Scholar
• Gosselt HR, Verhoeven MMA, Bulatović-ćalasan M, et al. Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis. J Pers Med. 2021;11(1):44. doi:10.3390/jpm11010044
   PubMed Web of Science ®Google Scholar
• Lim AJ, Lim LJ, Ooi BN, et al. Functional coding haplotypes and machine-learning feature elimination identifies predictors of methotrexate response in rheumatoid arthritis patients. EBioMedicine. 2022;3:75.
   Google Scholar
• Plant D, Maciejewski M, Smith S, et al. Profiling of gene expression biomarkers as a classifier of methotrexate nonresponse in patients with rheumatoid arthritis. Arthritis Rheumatol. 2019;71(5):678–684. doi:10.1002/art.40810
   PubMed Web of Science ®Google Scholar
• Guan Y, Zhang H, Quang D, et al. Machine learning to predict anti-tumor necrosis factor drug responses of rheumatoid arthritis patients by integrating clinical and genetic markers. Arthritis Rheumatol. 2019;71(12):1987–1996. doi:10.1002/art.41056
   PubMed Web of Science ®Google Scholar
• Luque-Tévar M, Perez-Sanchez C, Patiño-Trives AM, et al. Integrative clinical, molecular, and computational analysis identify novel biomarkers and differential profiles of anti-TNF response in rheumatoid arthritis. Front Immunol. 2021;12:631662. doi:10.3389/fimmu.2021.631662
   PubMed Web of Science ®Google Scholar
• Yoosuf N, Maciejewski M, Ziemek D, et al. Early prediction of clinical response to anti-TNF treatment using multi-omics and machine learning in rheumatoid arthritis. Rheumatology. 2022;61(4):1680–1689. doi:10.1093/rheumatology/keab521
   PubMed Web of Science ®Google Scholar
• Tao W, Concepcion AN, Vianen M, et al. Multiomics and machine learning accurately predict clinical response to Adalimumab and etanercept therapy in patients with rheumatoid arthritis. Arthritis Rheumatol. 2021;73(2):212–222. doi:10.1002/art.41516
   PubMed Web of Science ®Google Scholar
• Tasaki S, Suzuki K, Kassai Y, et al. Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission. Nat Commun. 2018;9(1):2755. doi:10.1038/s41467-018-05044-4
   PubMedGoogle Scholar
• Jung SM, Park K-S, Kim K-J. Deep phenotyping of synovial molecular signatures by integrative systems analysis in rheumatoid arthritis. Rheumatology. 2021;60(7):3420–3431. doi:10.1093/rheumatology/keaa751
   PubMed Web of Science ®Google Scholar
• MacEachern SJ, Forkert ND. Machine learning for precision medicine. Genome. 2021;64(4):416–425. doi:10.1139/gen-2020-0131
   PubMed Web of Science ®Google Scholar