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To what extent do autoantibodies help to identify high-risk patients in systemic sclerosis?


1, 2, 3, 4, 5, 6, 7, 8, 9

 

  1. Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands. m.boonstra@lumc.nl
  2. Department of Medical Statistics and Bioinformatics, Leiden University Medical Centre, Leiden, The Netherlands.
  3. Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands.
  4. Department of Pulmonology, Leiden University Medical Centre, Leiden, The Netherlands.
  5. Department of Cardiology, Leiden University Medical Centre, Leiden, The Netherlands.
  6. Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands.
  7. Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands.
  8. Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands.
  9. Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands.

CER10950
2018 Vol.36, N°4 ,Suppl.113
PI 0109, PF 0117
Diagnosis

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PMID: 30148428 [PubMed]

Received: 07/11/2017
Accepted : 26/03/2018
In Press: 18/07/2018
Published: 29/09/2018

Abstract

OBJECTIVES:
To evaluate the additive value of autoantibodies in identifying systemic sclerosis (SSc) patients with high complication risk.
METHODS:
Patients entering the Combined Care In SSc cohort, Leiden University Medical Centre between April 2009 and May 2016 were included. Subgroups of patients were determined using hierarchical clustering, performed on Principal Component Analysis scores, 1) using baseline data of demographic and clinical variables only and 2) with additional use of antibody status. Disease-risk within subgroups was assessed by evaluating 5-year mortality rates. Clinical and autoantibody characteristics of obtained subgroups were compared.
RESULTS:
In total 407 SSc patients were included, of which 91% (n=371) fulfilled ACR/EULAR 2013 criteria for SSc. Prevalences of autoantibodies were: anti-centromere 37%, anti-topoisomerase (ATA) 24%, anti-RNA polymerase III 5%, anti-fibrillarin 4% and anti-Pm/Scl 5%. Clinical cluster analysis identified 4 subgroups, with two subgroups showing higher than average mortality (resp. 17% and 7% vs. total group mortality of 4%). ATA-positivity ranged from 10 to 21% in low-risk groups and from 30 to 49% among high-risk groups. Adding autoantibody status to the cluster process resulted in 5 subgroups with 3 showing higher than average mortality. Still, 22% of ATA- positive patients were clustered into a low-risk subgroup, while the total number of patients stratified to a high-risk subgroup increased.
CONCLUSIONS:
Autoantibodies only partially contribute to risk-stratification and clinical subsetting in SSc. The current findings confirm that not all ATA-positive patients have worse prognosis and as such, additional biomarkers are needed to guide clinical follow-up in SSc.

Rheumatology Article