Evidence map›Paper›PMID 25711876›Full record

ReviewClinical rheumatology2015

Early systemic sclerosis-opportunities for treatment.

Lazaros I Sakkas, Theodora Simopoulou, Christina Katsiari, Dimitrios Bogdanos, Ian C Chikanza

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical rheumatology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Review
  5. Review
  6. Review
  7. CAR-T cells in systemic sclerosis.Clinical rheumatology · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Immunotherapy of systemic sclerosis.Human vaccines & immunotherapeutics · 2018
    Article
  16. Adenosine AThe American journal of pathology · 2017
    Article
  17. 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.

Lazaros I SakkasDepartment of Rheumatology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, 41 110, Larissa, Greece, lsakkas@med.uth.gr.
Theodora Simopoulou
Christina Katsiari
Dimitrios Bogdanos
Ian C Chikanza

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic sclerosis (SSc) is characterized by microvasculopathy (Raynaud's phenomenon and fibrointimal proliferation), presence of autoantibodies and collagen deposition in skin (scleroderma) and internal organs. Microvasculopathy, detected by nailfold capillaroscopy, and disease-specific autoantibodies (anti-topoisomerase I, anti-centromere, anti-RNA polymerase III antibodies) usually appear earlier, even years before scleroderma. At that stage of the disease, immune activation with T cells and B cells promote fibrosis. Diagnosis of SSc has been relied on scleroderma, and by this time, internal organs may have developed fibrosis, a lethal feature with no available treatment. The new EULAR/ACR 2013 criteria for the classification of SSc will help identify SSc patients before fibrosis of internal organs. The early diagnosis of SSc, before the development of fibrosis in internal organs, will allow the introduction of immunosuppressive medications in these patients in a controlled setting (randomized trials). It is anticipated that this approach will change the hitherto grim prognosis of SSc for the better.

Indexed as

AutoantibodiesEarly DiagnosisHumansImmunosuppressive AgentsMicroscopic AngioscopyPrognosisRaynaud DiseaseScleroderma, SystemicAutoantibodiesImmunosuppressive Agents

Identifiers

What OpenQuestion holds

Textmetadata
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.