Predicting the course of uveitis against the background of juvenile idiophatic arthritis when using topical therapy regimens. The results of mathematical modeling

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BACKGROUND: Juvenile idiopathic arthritis is the most common rheumatic disease in children, and uveitis is its most destructive extra-articular manifestation. Despite the existence of Federal clinical guidelines for the management of these patients, their treatment is largely based on the experience of doctors and varies greatly even within the same country.

AIM: The aim of the study is to find factors for predicting the course of uveitis and optimizing therapy.

MATERIALS AND METHODS: The case histories of 150 children aged 1.5 to 17 years with active uveitis in the structure of juvenile arthritis were analyzed using multifactorial modeling (construction of classification trees).

RESULTS: The fact of a significant influence of the time elapsed from the onset of rheumatic disease and uveitis until the start of therapy by genetically engineered medications (tumor necrosis factor alpha inhibitors) in treatment programs has been established.

CONCLUSIONS: Thus, the inclusion of this factor into the group of controlling ones makes it possible to achieve inactive uveitis status after 1, 3, and 6 months in a higher percentage of cases. However, the obtained data still require additional clinical confirmation.

作者简介

Виктор Анатольевич Chasnyk

Saint Petersburg State Pediatric Medical University

Email: chasnyk@gmail.com
ORCID iD: 0000-0001-5776-1490
SPIN 代码: 8175-0010

MD, Dr. Sci. (Medicine), Professor

俄罗斯联邦, Saint Petersburg

Виктор Анатольевич Кононов

Saint Petersburg State Pediatric Medical University; North-West State Medical University named after I.I. Mechnikov

Email: 7435020@gmail.com
ORCID iD: 0000-0002-4673-5024
俄罗斯联邦, Saint Petersburg; Saint Petersburg

Vladimir Brzheskiy

Saint Petersburg State Pediatric Medical University

Email: vvbrzh@yandex.ru
ORCID iD: 0000-0001-7361-0270
SPIN 代码: 5442-0989

MD, Dr. Sci. (Medicine), Professor

俄罗斯联邦, Saint Petersburg

Ekaterina Gaidar

Saint Petersburg State Pediatric Medical University

Email: gaidare85@gmail.com
ORCID iD: 0000-0002-0971-2018
SPIN 代码: 1625-9960

MD, Cand. Sci. (Medicine)

俄罗斯联邦, Saint Petersburg

Olga Kalashnikova

Saint Petersburg State Pediatric Medical University

Email: koira7@yandex.ru
ORCID iD: 0000-0002-8683-4270
SPIN 代码: 9114-0435

MD, Cand. Sci. (Medicine), Assistant Professor

俄罗斯联邦, Saint Petersburg

Margarita Dubko

Saint Petersburg State Pediatric Medical University

Email: andrq@rambler.ru
ORCID iD: 0000-0002-6834-1413
SPIN 代码: 4152-4976

MD, Cand. Sci. (Medicine), Assistant Professor

俄罗斯联邦, Saint Petersburg

Mikhail Kostik

Saint Petersburg State Pediatric Medical University

Email: kost-mikhail@yandex.ru
ORCID iD: 0000-0002-1180-8086
SPIN 代码: 7257-0795

MD, Dr. Sci. (Medicine), Professor

俄罗斯联邦, Saint Petersburg

Vera Masalova

Saint Petersburg State Pediatric Medical University

Email: masalova.vera@gmail.com
ORCID iD: 0000-0002-3703-4920
SPIN 代码: 2241-3508
俄罗斯联邦, Saint Petersburg

Ludmila Snegireva

Saint Petersburg State Pediatric Medical University

Email: l.s.snegireva@mail.ru
ORCID iD: 0000-0001-6778-4127
俄罗斯联邦, Saint Petersburg

Tatiana Nikitina

Saint Petersburg State Pediatric Medical University

Email: nikitina.tat.nik@yandex.ru
ORCID iD: 0000-0001-6758-6999
SPIN 代码: 8496-2970

MD, Cand. Sci. (Medicine)

俄罗斯联邦, Saint Petersburg

Nadezhda Kononova

Saint Petersburg State Pediatric Medical University

编辑信件的主要联系方式.
Email: Nali-6@yandex.ru
ORCID iD: 0000-0002-2145-1762
SPIN 代码: 7217-3582

MD, Cand. Sci. (Medicine)

俄罗斯联邦, Saint Petersburg

参考

  1. Drozdova EA. Medical and social aspects of uveitis in juvenile idiopathic arthritis. In: Materials of the interregional scientific and practical conference “Topical issues of ophthalmology”. Orenburg; 2013. P. 113–119. (In Russ.)
  2. Galstyan LA, Zholobova ES, Chebysheva SN, et al. Uveitis associated with juvenile eidiopathic arthritis. Russian Bulletin of Perinatology and Pediatrics. 2019;64(2):30–37. EDN: SHIHNR doi: 10.21508/1027-4065-2019-64-2-30-37
  3. Salugina SO, Katargina LA, Starikova AV. Rheumatological diseases and eyes lesions in children. Scientific and Practical Rheumatology. 2004;42(1):78–81. EDN: QCWZFJ
  4. Drozdova EA. The classification and epidemiology of uveitis. RMJ. Clinical Ophthalmology. 2016;16(3):155–159. EDN: ZNOGAL doi: 10.21689/2311-7729-2016-16-3-155-159
  5. Katargina LA, Brzheskij VV, Guseva MR, et al. The federal clinical guidelines on “The diagnostics and treatment of uveitis associated with juvenile idiopathic arthritis”. Russian Pediatric Ophthalmology. 2016;11(2): 102–111. EDN: VXEJMP doi: 10.18821/1993-1859-2016-11-2-102-111
  6. Zierhut M, Heiligenhaus A, deBoer J, et al. Controversies in juvenile idiopathic. Arthritis-associated uveitis. Ocul Immunol Inflamm. 2013;21(3):167–179. doi: 10.3109/09273948.2013.800561
  7. habr.com [Internet]. What is a decision tree and where is it used? Mosсow; 2020 [cited: 23.11.2023]. Availible from: https://habr.com/ru/companies/productstar/articles/523044/

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2. Fig. 1. The informative value of the features used in the classification. gender — the sex of the child; arthr_type — variant of arthritis; uv_type — primary localization of uveitis; num_eyes — the number of affected eyes at the onset of uveitis; arthr_before — the presence of arthritis before uveitis; CS_bef_uv — treatment with cytostatics before uveitis; nstainf_bef_uv — treatment with systemic nonsteroidal anti-inflammatory drugs before uveitis; gc_sys_bef_uv — treatment with systemic glucocorticoids before the occurrence of uveitis; biol_bef_biol — treatment with genetically engineered biological drugs before the occurrence of uveitis; MTX_bef_biol — treatment of uveitis with methotrexate before the prescription of biological drugs; more_cs_before_uv — treatment with more than one cytostatic agent before the occurrence of uveitis; ageyrs_dis_onset — age (years) at the onset of rheumatic disease; uv_delay_mnths — time from the onset of rheumatic disease to the detection of uveitis in months; numb_eyes — the maximum number of affected eyes

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3. Fig. 2. The informative value of the features used in the classification. See Fig. 1 for the designations

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4. Fig. 3. The informative value of the features used in the classification. biol_delay_from_arthtr_mnths — time from the onset of rheumatic disease to the appointment of a genetically engineered biological drug (in months); biol_delay_from_uv_mnths — time from the occurrence of uveitis to the prescription of a genetically engineered biological drug (in months), other designations see Fig. 1

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5. Fig. 4. The informative value of the features used in the classification for the control point “3 months of follow-up”. biol_delay_from_arthtr_mnths — time from the onset of rheumatic disease to the prescription of a genetically engineered biological drug (in months); biol_delay_from_uv_mnths — time from the occurrence of uveitis to the prescription of a genetically engineered biological drug (in months), other designations see Fig. 1

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6. Fig. 5. The informative value of the features used in the classification for the control point “6 months of follow-up”. biol_delay_from_arthtr_mnths — time from the onset of rheumatic disease to the prescription of a genetically engineered biological drug (in months); biol_delay_from_uv_mnths — time from the occurrence of uveitis to the prescription of a genetically engineered biological drug (in months), other designations see Fig. 1

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