Evidence mapPaperPMID 41001363Full record

ArticleFrontiers in medicine2025

Clinical features and recurrence risk prediction model in patients with idiopathic inflammatory myopathies-associated interstitial lung disease: a retrospective study from Ningbo.

Di Wu, Yapeng Hou, Wei Fan, Yingying Du, Qunli Ding

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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Di WuKey Laboratory of Respiratory Disease of Ningbo, Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Yapeng HouKey Laboratory of Respiratory Disease of Ningbo, Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Wei FanKey Laboratory of Respiratory Disease of Ningbo, Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Yingying DuKey Laboratory of Respiratory Disease of Ningbo, Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Qunli DingKey Laboratory of Respiratory Disease of Ningbo, Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Idiopathic inflammatory myopathies (IIMs) are characterized by chronic muscle inflammation and often involve multiple organ systems. Despite treatment, a large number of patients still experience relapse or disease progression. Currently, there is a lack of high-quality studies specifically focusing on recurrence, and early identification of patients at high risk of recurrence remains challenging. Methods: This retrospective study included patients with idiopathic inflammatory myopathy complicated by interstitial lung disease who were hospitalized in the First Affiliated Hospital of Ningbo University from January 2018 to December 2024. All included individuals were followed up for at least 12 months. The diagnosis of idiopathic inflammatory myopathies and interstitial lung disease (ILD) was based on relevant criteria. A wide range of clinical and laboratory data were collected. Significant variables were screened through univariate and multivariate regression analyses, and risk models for predicting recurrence at 1, 2, and 3 years were constructed, with subsequent evaluation of the models' performance. Results: Among the 93 included patients, the recurrence rate was 23.7%, with a median time to recurrence of 38 months. Approximately 26.1% of recurrences were attributed to drug discontinuation or adjustment. Multivariate analysis suggested that positive anti-RO52 antibody, positive anti-PL7 antibody, elevated white blood cell count, elevated ALT, and elevated LDH were positively correlated with the risk of recurrence. The area under the ROC curve (AUC) for recurrence prediction was: 1-year: 1.00 (95% CI: 1.00-1.00), 2-year: 0.91 (95% CI: 0.75-1.08), 3-year: 0.92 (95% CI: 0.78-1.05). Conclusion: Based on baseline clinical and laboratory indicators, this study developed a tool with good predictive ability for IIM-ILD recurrence, which can accurately assess individual recurrence risk and assist in early clinical decision-making. Trial registration number: IRB No:2025092RS.

Indexed as

AUCIIM-ILDNingborecurrencerisk prediction model

Identifiers

PMID41001363
PMCPMC12457148

What Socratic holds

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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 Socratic graph.