Evidence map›Paper›PMID 38708024›Full record

ArticleRheumatology advances in practice2024

Clinical phenotyping in patients with anti-synthetase antibodies using cluster analysis.

Shintaro Yamamoto, Akira Yoshida, Yuka Okazaki, Takahisa Gono, Masataka Kuwana

Abstract read
In one paragraph

Article in Rheumatology advances in practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

5 authors.

Shintaro YamamotoDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-6172-9116
Akira YoshidaDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0003-3590-1637
Yuka OkazakiDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan.
Takahisa GonoDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-2593-1771
Masataka KuwanaDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0001-8352-6136

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To characterize clinically distinct subgroups among unselected patients with anti-synthetase antibodies using cluster analysis. Methods: This study evaluated patients with anti-synthetase antibodies registered to two independent cohorts; 106 consecutive patients from a prospective, single-centre cohort of the Scleroderma/Myositis Centre of Excellence (SMCE) were used as a derivation cohort and 125 patients from the Multicentre Retrospective Cohort of Japanese Patients with Myositis-Associated Interstitial Lung Disease (JAMI) were used as a validation cohort. Anti-synthetase antibodies were identified by RNA immunoprecipitation. A multiple correspondence analysis followed by hierarchical clustering was performed to aggregate the patients into homogeneous subgroups. Subsequently, a simple-to-use classification tree was generated using classification and regression tree analysis. Results: Three clusters were identified in the SMCE cohort: cluster 1 ( Conclusion: Patients with anti-synthetase antibodies were classified into three distinct phenotypes, indicating substantial heterogeneity within this patient group.

Indexed as

anti-synthetase syndromecluster analysisinterstitial lung diseasemyositisscleroderma

Identifiers

PMID38708024
PMCPMC11069276

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.