Literature DB >> 35136981

Predictors of Rituximab Effect on Modified Rodnan Skin Score in Systemic Sclerosis: a machine learning analysis of the DESIRES trial.

Satoshi Ebata1, Koji Oba2, Kosuke Kashiwabara3, Keiko Ueda3, Yukari Uemura3,4, Takeyuki Watadani5, Takemichi Fukasawa1, Shunsuke Miura1, Asako Yoshizaki-Ogawa1, Asano Yoshihide1, Ayumi Yoshizaki1, Shinichi Sato1.   

Abstract

OBJECTIVES: The DESIRES trial showed that rituximab is effective in treating skin sclerosis in systemic sclerosis. However, which patient groups are likely to benefit from rituximab is unknown.
METHODS: We performed post-hoc analysis on prospective data from 54 patients who received rituximab or placebo in the DESIRES trial. Twenty-seven baseline factors were used to investigate subpopulations with different magnitudes of rituximab effect on modified Rodnan Skin Score (mRSS) change at 24 weeks. Based on a machine-learning algorithm called the causal tree, we explored the combination of predictors needed to identify subpopulations that would respond to rituximab and have good treatment outcomes.
RESULTS: Three factors were identified as branches of the decision tree: "peripheral blood CD19-positive cell counts", "mRSS", and "serum surfactant protein D (SP-D) levels". Only in the subpopulation of patients with CD19-positive cell counts < 57/μl, rituximab did not show a significant improvement in mRSS vs placebo. In the subpopulation of patients with CD19-positive cell counts ≥ 57/μl and mRSS ≥ 17, mRSS was most improved with rituximab (difference -17.06 [95%CI -24.22 to -9.89]). The second greatest improvement in mRSS with rituximab was in the subpopulation with CD19-positive cell counts ≥ 57/μl, mRSS < 17, and serum SP-D levels ≥ 151 ng/ml (difference -10.35 [95% CI -14.77 to -5.93]).
CONCLUSION: Systemic sclerosis patients who have high CD19-positive cell counts and high mRSS expected greater improvement in mRSS with rituximab. When the patients with high CD19-positive cell counts showed low mRSS, serum SP-D levels may modify the treatment effect. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT04274257 and UMIN-CTR, https://center6.umin.ac.jp, UMIN000030139.
© The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Machine Learning; Modified Rodnan Skin Score; Rituximab; Systemic Sclerosis

Year:  2022        PMID: 35136981     DOI: 10.1093/rheumatology/keac023

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.580


  5 in total

Review 1.  Pathogenetic Aspects of Systemic Sclerosis: A View Through the Prism of B Cells.

Authors:  Konstantinos Melissaropoulos; George Iliopoulos; Lazaros I Sakkas; Dimitrios Daoussis
Journal:  Front Immunol       Date:  2022-06-23       Impact factor: 8.786

Review 2.  Current advances in the treatment of systemic sclerosis.

Authors:  Heather Bukiri; Elizabeth R Volkmann
Journal:  Curr Opin Pharmacol       Date:  2022-04-18       Impact factor: 4.768

Review 3.  New Era in Systemic Sclerosis Treatment: Recently Approved Therapeutics.

Authors:  Satoshi Ebata; Asako Yoshizaki-Ogawa; Shinichi Sato; Ayumi Yoshizaki
Journal:  J Clin Med       Date:  2022-08-08       Impact factor: 4.964

Review 4.  Involvement of B cells in the development of systemic sclerosis.

Authors:  Ayumi Yoshizaki; Takemichi Fukasawa; Satoshi Ebata; Asako Yoshizaki-Ogawa; Shinichi Sato
Journal:  Front Immunol       Date:  2022-07-28       Impact factor: 8.786

Review 5.  The Use and Utility of Machine Learning in Achieving Precision Medicine in Systemic Sclerosis: A Narrative Review.

Authors:  Francesco Bonomi; Silvia Peretti; Gemma Lepri; Vincenzo Venerito; Edda Russo; Cosimo Bruni; Florenzo Iannone; Sabina Tangaro; Amedeo Amedei; Serena Guiducci; Marco Matucci Cerinic; Silvia Bellando Randone
Journal:  J Pers Med       Date:  2022-07-23
  5 in total

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