Comprehensive Score Identifies Patients at High-Risk of Developing Arthritis

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The comprehensive score was able to recognize 119 high-risk participants (false positive rate of 29%) and 336 low-risk patients (false negative rate of 19%).

A comprehensive scoring system successfully predicted patients at a higher risk of developing inflammatory arthritis (IA) who could benefit from preventative measures and risk stratification, according to a study published in Annals of Internal Medicine.1 Additionally, a simple score was able to identify patients at low risk for IA who were less likely to need secondary care.

Inflammatory arthritis, with its most common form being rheumatoid arthritis (RA), is comprised of all immune-related diseases with the presence of clinical synovitis (swollen joints). As several biomarkers are linked to RA and may be present years prior to the development of clinical synovitis onset, it is considered end-stage. RA can be predicted by environmental factors, genetics, rheumatoid factor (RF), subclinical inflammation, altered circulating immune cell frequencies, and serologic tests to detect anticitrullinated protein antibody (anti-CCP). Other factors include the presence of painful joints, patient-reported pain, fatigue, and general health, and early morning stiffness.2

“To date, 3 major risk prediction scores have been published; these differ in terms of population and biomarkers included,” wrote Laurence Duquenne, MD, Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, United Kingdom, and colleagues. “The first 2 scores selected by serologic status; a third score studied clinically suspect arthralgia (CSA) and showed that possessing 3 or more classification criteria for CSA predicted IA with an acceptable performance.”

In the prospective, observational, cohort study, investigators used multidimensional scores for risk stratification, including a simple score developed using logistic regression and a comprehensive score developed using the selection operator Cox proportional hazard regression and least absolute shrinkage. Other objectives included identifying suitable populations for intervention research and monitoring patients with anti-CCP at risk for IA.

Patients were recruited from primary and secondary care clinics in the United Kingdom between June 2008 and November 2021. Eligible participants had new musculoskeletal symptoms, no clinical synovitis, and a positive test result for anticitrullinated protein antibodies. They were followed-up for ≥48 weeks or until IA developed.

A total of 455 patients were eligible for analysis. During the follow-up period, 32.5% (n = 148/455) developed IA, with 15.4% (n = 70/455) developing the condition within 1 year.

The simple score was able to correctly identify 249 participants deemed “low-risk,” with a false negative rate of 5%. However, it identified 206 high-risk patients with a false-positive rate of 72%. The comprehensive score was able to recognize 119 high-risk participants, with a false positive rate of 29%, and 336 low-risk patients with a false negative rate of 19%. Using the comprehensive score, 40% of the high-risk participants developed IA within 1 year and 71% within 5 years.

Investigators noted the inclusion of the large anti-CCP-positive at-risk population, a wide variety of biomarkers, and a long follow-up period strengthened the study. Additionally, although IA was the primary outcome, 91.9% of patients who developed IA also met the diagnostic criteria for RA.

However, recruiting the population over a 13-year period, coupled with slower and lower rates of IA in later recruitment, limited the study. Additionally, the requirement of external validation, the geographic variation in laboratory testing and recruitment availability, and the use of anti-CCP2 test for recruitment and score hindered results. Future research should focus on better understanding how the simple and comprehensive scores could be incorporated into existing clinical pathways and how they would perform in combination.

“Using a wide range of biomarkers, this study developed simple and comprehensive risk scores,” investigators concluded. “These scores should have a positive effect on persons and health care systems.”


  1. Duquenne, L, Hensor, E, & Wilson, M, et al. (2023). Predicting Inflammatory Arthritis in At-Risk Persons: Development of Scores for Risk Stratification. Annals of Internal Medicine.
  2. Di Matteo A, Mankia K, Wakefield RJ, et al. Response to: 'Pisotriquetral arthritis: 'forgotten' joint in ultrasound imaging of the wrist' by Becciolini et al. Ann Rheum Dis. 2022;81:e98. [PMID: 32513649] doi:10.1136/annrheumdis-2020-218036