Evidence map›Paper›PMID 37986108›Full record

ArticleArthritis research & therapy2023

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

Takuya Kotani, Shogo Matsuda, Ayana Okazaki, Daisuke Nishioka, Ryu Watanabe, Takaho Gon, Atsushi Manabe, Mikihito Shoji, Keiichiro Kadoba, Ryosuke Hiwa and 3 more

Abstract readMulticenter Study
In one paragraph

Article in Arthritis research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. [Therapeutic antibodies in rheumatology].Zeitschrift fur Rheumatologie · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Takuya Kotani *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 *Department of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan.
Ayana OkazakiDepartment of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan.
Daisuke NishiokaDepartment of Medical Statistics, Research & Development Center, Osaka Medical and Pharmaceutical University, Osaka, Japan.
Ryu WatanabeDepartment of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan.
Takaho GonDepartment of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan.
Atsushi ManabeDepartment of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Mikihito ShojiDepartment of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Keiichiro KadobaDepartment of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Ryosuke HiwaDepartment of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Wataru YamamotoDepartment of Health Information Management, Kurashiki Sweet Hospital, Kurashiki, Japan.
Motomu HashimotoDepartment of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan.
Tohru TakeuchiDepartment of Internal Medicine (IV), Division of Rheumatology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki, Osaka, 569-8686, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo establish refined risk prediction models for mortality in patients with microscopic polyangiitis (MPA) by using comprehensive clinical characteristics.

methodsData 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.

resultsOver 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.

conclusionsThe 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.

Indexed as

Anti-Neutrophil Cytoplasmic Antibody-Associated VasculitisGranulomatosis with PolyangiitisMicroscopic PolyangiitisAgedCohort StudiesHumansRetrospective StudiesRisk AssessmentRisk FactorsSurvival RateMicroscopic polyangiitisMulticentre cohort studyPrognosisRisk prediction model

Identifiers

PMID37986108
PMCPMC10658814

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.