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Predicting functional disability in patients with spondyloarthritis using a CRP-based algorithm: A 3-year prospective

Liliana Catan1, Marius Boariu2, Elena Amaricai1

  • 1Department of Balneology, Medical Rehabilitation and Rheumatology, 'Victor Babes' University of Medicine and Pharmacy, 300041 Timisoara, Romania.

Experimental and Therapeutic Medicine
|December 28, 2020
PubMed
Summary

This study developed a new algorithm using C-reactive protein (CRP) levels to predict functional disability in patients with spondyloarthritis (SpA). The CRP-mHAQ-S algorithm offers a potential tool for monitoring disease progression and guiding treatment strategies.

Keywords:
C-reactive proteinHAQ-Sdisease activityfunctional disabilityquality of lifespondyloarthritis

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Area of Science:

  • Rheumatology and Immunology
  • Clinical Prediction Modeling
  • Inflammatory Disease Biomarkers

Background:

  • Spondyloarthritis (SpA) encompasses several inflammatory conditions, including ankylosing spondylitis and psoriatic arthritis, often leading to significant functional disability.
  • Accurate prediction of functional disability is crucial for effective management and personalized treatment of SpA patients.
  • C-reactive protein (CRP) is a key inflammatory marker, but its direct predictive value for long-term functional outcomes in SpA requires further elucidation.

Purpose of the Study:

  • To explore the relationship between C-reactive protein (CRP) levels and functional disability in patients diagnosed with SpA.
  • To derive a predictive algorithm for functional disability based on objective CRP measurements over time.
  • To assess the potential of this algorithm in predicting the evolution of functional disability in SpA.

Main Methods:

  • A prospective study followed 144 SpA patients for 3 years, categorized into five treatment groups.
  • Data collected included C-reactive protein (CRP), modified Health Assessment Questionnaire (mHAQ-S), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and T-scores.
  • Correlation and multivariate regression analyses were employed to develop the CRP-mHAQ-S predictive algorithm.

Main Results:

  • A predictive model was successfully derived: mHAQ-S36=17.14+0.12xCRP0-0.24xCRP12-0.15xCRP36, demonstrating statistical significance (P<0.001).
  • This algorithm utilizes baseline, 12-month, and 36-month CRP levels to predict the 36-month functional disability score (mHAQ-S).
  • The study confirmed a significant correlation between CRP values and functional disability measures in SpA patients.

Conclusions:

  • The developed CRP-mHAQ-S algorithm provides a novel, objective method for predicting functional disability in SpA patients.
  • This tool may aid clinicians in anticipating disease trajectory and optimizing therapeutic interventions.
  • Further validation of this algorithm in diverse SpA populations is warranted to enhance its clinical utility.