Risk prediction model for mortality in microscopic polyangiitis: multicentre REVEAL cohort study.


Journal

Arthritis research & therapy
ISSN: 1478-6362
Titre abrégé: Arthritis Res Ther
Pays: England
ID NLM: 101154438

Informations de publication

Date de publication:
20 Nov 2023
Historique:
received: 14 09 2023
accepted: 07 11 2023
medline: 22 11 2023
pubmed: 21 11 2023
entrez: 21 11 2023
Statut: epublish

Résumé

To establish refined risk prediction models for mortality in patients with microscopic polyangiitis (MPA) by using comprehensive clinical characteristics. Data from the multicentre Japanese registry of patients with vasculitis (REVEAL cohort) were used in our analysis. In total, 194 patients with newly diagnosed MPA were included, and baseline demographic, clinical, laboratory, and treatment details were collected. Univariate and multivariate analyses were conducted to identify the significant risk factors predictive of mortality. Over a median follow-up of 202.5 (84-352) weeks, 60 (30.9%) of 194 patients died. The causes of death included MPA-related vasculitis (18.3%), infection (50.0%), and others (31.7%). Deceased patients were older (median age 76.2 years) than survivors (72.3 years) (P < 0.0001). The death group had shorter observation periods (median 128.5 [35.3-248] weeks) than the survivor group (229 [112-392] weeks). Compared to survivors, the death group exhibited a higher smoking index, lower serum albumin levels, higher serum C-reactive protein levels, higher Birmingham Vasculitis Activity Score (BVAS), higher Five-Factor Score, and a more severe European Vasculitis Study Group (EUVAS) categorization system. Multivariate analysis revealed that higher BVAS and severe EUVAS independently predicted mortality. Kaplan-Meier survival curves demonstrated lower survival rates for BVAS ≥20 and severe EUVAS, and a risk prediction model (RPM) based on these stratified patients into low, moderate, and high-risk mortality groups. The developed RPM is promising to predict mortality in patients with MPA and provides clinicians with a valuable tool for risk assessment and informed clinical decision-making.

Sections du résumé

BACKGROUND BACKGROUND
To establish refined risk prediction models for mortality in patients with microscopic polyangiitis (MPA) by using comprehensive clinical characteristics.
METHODS METHODS
Data from the multicentre Japanese registry of patients with vasculitis (REVEAL cohort) were used in our analysis. In total, 194 patients with newly diagnosed MPA were included, and baseline demographic, clinical, laboratory, and treatment details were collected. Univariate and multivariate analyses were conducted to identify the significant risk factors predictive of mortality.
RESULTS RESULTS
Over a median follow-up of 202.5 (84-352) weeks, 60 (30.9%) of 194 patients died. The causes of death included MPA-related vasculitis (18.3%), infection (50.0%), and others (31.7%). Deceased patients were older (median age 76.2 years) than survivors (72.3 years) (P < 0.0001). The death group had shorter observation periods (median 128.5 [35.3-248] weeks) than the survivor group (229 [112-392] weeks). Compared to survivors, the death group exhibited a higher smoking index, lower serum albumin levels, higher serum C-reactive protein levels, higher Birmingham Vasculitis Activity Score (BVAS), higher Five-Factor Score, and a more severe European Vasculitis Study Group (EUVAS) categorization system. Multivariate analysis revealed that higher BVAS and severe EUVAS independently predicted mortality. Kaplan-Meier survival curves demonstrated lower survival rates for BVAS ≥20 and severe EUVAS, and a risk prediction model (RPM) based on these stratified patients into low, moderate, and high-risk mortality groups.
CONCLUSIONS CONCLUSIONS
The developed RPM is promising to predict mortality in patients with MPA and provides clinicians with a valuable tool for risk assessment and informed clinical decision-making.

Identifiants

pubmed: 37986108
doi: 10.1186/s13075-023-03210-8
pii: 10.1186/s13075-023-03210-8
pmc: PMC10658814
doi:

Types de publication

Multicenter Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

223

Informations de copyright

© 2023. The Author(s).

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Auteurs

Takuya Kotani (T)

Department of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan. takuya.kotani@ompu.ac.jp.

Shogo Matsuda (S)

Department of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan.

Ayana Okazaki (A)

Department of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan.

Daisuke Nishioka (D)

Department of Medical Statistics, Research & Development Center, Osaka Medical and Pharmaceutical University, Osaka, Japan.

Ryu Watanabe (R)

Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan.

Takaho Gon (T)

Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan.

Atsushi Manabe (A)

Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Mikihito Shoji (M)

Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Keiichiro Kadoba (K)

Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Ryosuke Hiwa (R)

Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Wataru Yamamoto (W)

Department of Health Information Management, Kurashiki Sweet Hospital, Kurashiki, Japan.

Motomu Hashimoto (M)

Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan.

Tohru Takeuchi (T)

Department of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan.

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