Clinical and laboratory markers of methotrexate efficacy in rheumatoid arthritis

Introduction. In recent years an active search is conducted for clinical and laboratory markers (phenotypes of rheumatoid arthritis (RA), capable of predicting its effectiveness at the initiation of methotrexate (MT) therapy, allowing practitioners to determine the tactics of starting drug selection. Objective: to determine clinical and laboratory predictors of different response to methotrexate in patients with rheumatoid arthritis. Materials and methods. The study group consisted of 294 patients with a reliable diagnosis of RA. All patients received MT in the dosage from 10 to 25 mg per week as a first-line baseline drug. After 6 months, according to the dynamics of DAS28 index (Disease Activity Score), the efficacy of treatment was evaluated and "responders" and "non-responders" groups were distinguished. Then the following clinical and laboratory data were processed: gender, body mass index (BMI), smoking status, immunological parameters (RF - rheumatoid factor, ADCP - antibodies to cyclic citrullinated peptide), age of disease onset, activity on the DAS28 index, impaired vital signs on the HAQ (Health Assessment Questionnaire), systemic manifestations and adverse events. The relationship between methotrexate response and clinical and laboratory markers was assessed using two methods of statistical data processing: Nonlinear Principal Component Analysis (NLPCA) and group comparison using Pearson's χ2 criterion. Results. The NLPCA method highlighted the 1st principal component explaining the strong clinical relationship of MT effectiveness from baseline DAS28 and HAQ values (loadings for all three components were greater than 0.7). That is, patients with high DAS and HAQ indices may respond worse to MT monotherapy. The method of group comparison using Pearson's χ2 criterion allowed to confirm the above conclusion: Nonresponders had DAS28 significantly greater than 5.1 and HAQ in the range of 2.1-3.0 (p0.05, 95%CI included 1. Conclusions. The ineffectiveness of MT is significantly associated with the early onset of RA (before 40 years), high inflammatory activity of the disease, significant impairment of vital functions and excess body weight, regardless of gender and immunological markers (RF and ACCP). Smoking and systemic manifestations also have a negative impact on therapy at the probability level. The development of any side effects during treatment is a strong predictor of MT failure. The onset of the disease in middle age (40-60 years), moderate and low activity according to DAS28, minor functional impairments are clinical markers of the effectiveness of MT.

1. Насонов ЕЛ, Каратеев ДЕ, Балабанова РМ. Ревматоидный артрит. В кн.: Насонов ЕЛ, Насонова ВА, редакторы. Ревматология. Национальное руководство. Москва: ГЭОТАР-Медиа . - 2008. - С. 290-331

2. Насонов Е. Л., Олюнин Ю. А., Лила А. М. Ревматоидный артрит: проблемы ремиссии и резистентности к терапии // Научно-практическая ревматология. – 2018. – Т. 56. – №. 3. – С. 263-271.

3. Romão V. C., Canhão H., Fonseca J. E. Old drugs, old problems: where do we stand in prediction of rheumatoid arthritis responsiveness to methotrexate and other synthetic DMARDs? //BMC medicine. – 2013. – Т. 11. – С. 1-24.

4. Kavanaugh A, van Vollenhoven RF, Wolfe BA, Florentinus S, Chen S, Suboticki JL, et al. Predictors of Inadequate Response and Rapid Radiographic Progression in Patients with Early Rheumatoid Arthritis Receiving Methotrexate: a Post Hoc Analysis of 2 Randomized, Controlled Trials of Adalimumab (abstract]. // Arthritis Rheumatol. - 2016/ - T. 68 (suppl 10). – С. 822 - 823

5. Saevarsdottir S, Wallin H, Seddighzadeh M, Ernestam S, Geborek P, Peterson IF, et al. SWEFOT Trial Investigators Group. Predictors of response to methotrexate in early DMARD naive rheumatoid arthritis: results from the initial open-label phase of the SWEFOT trial. //Annals of the rheumatic diseases. – 2011. – Т. 70. – №. 3. – С. 469-475.

6. Benbouazza K, Rkain H, Benchekroun B, Amine B, Bzami F, Benbrahim L, et al. Remission in early rheumatoid arthritis treated with conventional DMARDs. Results of a two-year follow-up study of El Ayachi Moroccan cohort.// Joint Bone Spine. – 2012. – Т. 79. – №. 1. – С. 43-46.

7. Wessels JA, van der Kooi SM, le Cessie S, Kievit W, Barerra P, Allaart CF, et al. Pharmacogenetics Collaborative Research Group. A clinical pharmacogenetic model to predict the efficacy of methotrexate monotherapy in recent-onset rheumatoid arthritis. // Arthritis & Rheumatism. – 2007. – Т. 56. – №. 6. – С. 1765-1775.

8. Floris A, Perra D, Cangemi I, Congia M, Chessa E, Angioni MM, et al. Current smoking predicts inadequate response to methotrexate monotherapy in rheumatoid arthritis patients naïve to DMARDs: Results from a retrospective cohort study. Medicine. – 2021. – Т. 100. – №. 17. – С. e25481.

9. Vittecoq O, Richard L, Banse C, Lequerré T. The impact of smoking on rheumatoid arthritis outcomes. //Joint bone spine. – 2018. – Т. 85. – №. 2. – С. 135-138.

10. Roodenrijs NMT, van der Goes MC, Welsing PMJ, Tekstra J, van Laar JM, Lafeber FPJG, et al. Is prediction of clinical response to methotrexate in individual rheumatoid arthritis patients possible? A systematic literature review. //Joint Bone Spine. – 2020. – Т. 87. – №. 1. – С. 13-23.

11. Aletaha D, Neogi T, Silman AJ. et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/ European League Against Rheumatism collaborative initiative.//Arthritis & rheumatism. – 2010. – Т. 62. – №. 9. – С. 2569-2581.

12. Fransen J, van Riel PL. The Disease Activity Score and the EULAR response criteria. //Clinical and experimental rheumatology. – 2005. – Т. 23. – №. 5. – С. S93.

13. Van der Kooij A.J., Meulman J.J. Categorical Principal Components Analysis. In: Meulman JJ, Heiser WJ, editors. SPPS Categories 10.0. Chicago: SPSS Inc., 1999; С .1–9, 103–126, 221–237

14. Фомина Е.Е. Факторный анализ и категориальный метод главных компонент: сравнительный анализ и практическое применение для обработки результатов анкетирования. //Гуманитарный вестник. – 2017. – №. 10 (60). – С. 3 - 10.

15. Gifi А. Nonlinear Multivariate Analysis. New York: John Wiley & Sons, 1990. – Т8. – 214 с.

16. Michailidis G, de Leeuw J. The Gifi System of Descriptive Multivariate Analysis // Statistical Science. – 1998. – С. 307-336.

17. Manisera M., van der Kooij AJ., Dusseldorp E. Identifying the Component Structure of Satisfaction Scales by Nonlinear Principal Components Analysis. //Quality technology & quantitative management. – 2010. – Т. 7. – №. 2. – С. 97-115.

18. Нохрин Д.Ю. Лабораторный практикум по биостатистике. Челябинск: ЧелГУ. - 2018. – 100 с.

19. Duquesne J. et al. Machine learning identifies a profile of inadequate responder to methotrexate in rheumatoid arthritis // Rheumatology. – 2023. – Т. 62. – №. 7. – С. 2402-2409.

20. Duong SQ, Crowson CS, Athreya A, Atkinson EJ, Davis JM, Warrington KJ, et al. Clinical predictors of response to methotrexate in patients with rheumatoid arthritis: a machine learning approach using clinical trial data. //Arthritis Research & Therapy. – 2022. – Т. 24. – №. 1. – С. 162.

21. Hider SL, Silman AJ, Thomson W, Lunt M, Bunn D, Symmons DP. Can clinical factors at presentation be used to predict outcome of treatment with methotrexate in patients with early inflammatory polyarthritis? //Annals of the rheumatic diseases. – 2009. – Т. 68. – №. 1. – С. 57-62.

22. Teitsma XM, Jacobs JWG, Welsing PMJ, de Jong PHP, Hazes JMW, Weel AEAM, et al. Inadequate response to treat-to-target methotrexate therapy in patients with new-onset rheumatoid arthritis: development and validation of clinical predictors. //Annals of the Rheumatic Diseases. – 2018. – Т. 77. – №. 9. – С. 1261-1267.

23. McCulley CB, Barton JL, Cannon GW, Sauer BC, Teng CC, George MD, et al. Body mass index and persistence of conventional DMARDs and TNF inhibitors in rheumatoid arthritis. //Clinical and experimental rheumatology. – 2019. – Т. 37. – №. 3. – С. 422.

24. Dey M, Zhao SS, Moots RJ, Bergstra SA, Landewe RB, Goodson NJ. The association between increased body mass index and response to conventional synthetic disease-modifying anti-rheumatic drug treatment in rheumatoid arthritis: results from the METEOR database. //Rheumatology. – 2022. – Т. 61. – №. 2. – С. 713-722.

25. Siddiqui A, Totonchian A, Jabar Ali JB, Ahmad I, Kumar J, Shiwlani S, et al. Risk Factors associated with non-respondence to methotrexate in rheumatoid arthritis patients. /Cureus. – 2021. – Т. 13. – №. 9. – С. 18112.

26. Ma MH, Ibrahim F, Walker D, Hassell A, Choy EH, Kiely PD, et al. Remission in early rheumatoid arthritis: predicting treatment response. //The Journal of rheumatology. – 2012. – Т. 39. – №. 3. – С. 470-475.