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Meijs J, Schouffoer AA, Ajmone Marsan N, et al. A prediction model for progressive disease in systemic sclerosis. RMD Open. 2015;1(1):e000113doi: 10.1136/rmdopen-2015-000113.
Meijs, J., Schouffoer, A. A., Ajmone Marsan, N., Stijnen, T., Putter, H., Ninaber, M. K., Huizinga, T. W., & de Vries-Bouwstra, J. K. (2015). A prediction model for progressive disease in systemic sclerosis. RMD open, 1(1), e000113. https://doi.org/10.1136/rmdopen-2015-000113
Meijs, Jessica, et al. "A prediction model for progressive disease in systemic sclerosis." RMD open vol. 1,1 (2015): e000113. doi: https://doi.org/10.1136/rmdopen-2015-000113
Meijs J, Schouffoer AA, Ajmone Marsan N, Stijnen T, Putter H, Ninaber MK, Huizinga TW, de Vries-Bouwstra JK. A prediction model for progressive disease in systemic sclerosis. RMD Open. 2015 Dec 01;1(1):e000113. doi: 10.1136/rmdopen-2015-000113. eCollection 2015. PMID: 26688749; PMCID: PMC4680735.
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RMD Open. 2015 Dec 01;1(1):e000113. doi: 10.1136/rmdopen-2015-000113. eCollection 2015.

A prediction model for progressive disease in systemic sclerosis.

RMD open

Jessica Meijs, Anne A Schouffoer, Nina Ajmone Marsan, Theo Stijnen, Hein Putter, Maarten K Ninaber, Tom W J Huizinga, Jeska K de Vries-Bouwstra

Affiliations

  1. Department of Rheumatology , Leiden University Medical Center , Leiden , The Netherlands.
  2. Department of Rheumatology , Leiden University Medical Center , Leiden , The Netherlands ; Haga Hospital , The Hague , The Netherlands.
  3. Department of Cardiology , Leiden University Medical Center , Leiden , The Netherlands.
  4. Department of Medical Statistics , Leiden University Medical Center , Leiden , The Netherlands.
  5. Department of Pulmonology , Leiden University Medical Center , Leiden , The Netherlands.

PMID: 26688749 PMCID: PMC4680735 DOI: 10.1136/rmdopen-2015-000113

Abstract

OBJECTIVE: To develop a model that assesses the risk for progressive disease in patients with systemic sclerosis (SSc) over the short term, in order to guide clinical management.

METHODS: Baseline characteristics and 1 year follow-up results of 163 patients with SSc referred to a multidisciplinary healthcare programme were evaluated. Progressive disease was defined as: death, ≥10% decrease in forced vital capacity, ≥15% decrease in diffusing capacity for carbon monoxide, ≥10% decrease in body weight, ≥30% decrease in estimated-glomerular filtration rate, ≥30% increase in modified Rodnan Skin Score (with Δ≥5) or ≥0.25 increase in Scleroderma Health Assessment Questionnaire. The number of patients with progressive disease was determined. Univariable and multivariable logistic regression analyses were used to assess the probability of progressive disease for each individual patient. Performance of the prediction model was evaluated using a calibration plot and area under the receiver operating characteristic curve.

RESULTS: 63 patients had progressive disease, including 8 patients who died ≤18 months after first evaluation. Multivariable analysis showed that friction rubs, proximal muscular weakness and decreased maximum oxygen uptake as % predicted, adjusted for age, gender and use of immunosuppressive therapy at baseline, were significantly associated with progressive disease. Using the prediction model, the predicted chance for progressive disease increased from a pretest chance of 37% to 67-89%.

CONCLUSIONS: Using the prediction model, the chance for progressive disease for individual patients could be doubled. Friction rubs, proximal muscular weakness and maximum oxygen uptake as % predicted were identified as relevant parameters.

Keywords: Epidemiology; Systemic Sclerosis; Treatment

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