ArticlePediatric rheumatology online journal2025
Identifying the characteristics of and developing a predictive model for differentiating cancer-related musculoskeletal symptoms from juvenile idiopathic arthritis.
Article in Pediatric rheumatology online journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Differentiating Juvenile Idiopathic Arthritis From Acute Lymphoblastic Leukemia in Children: A Multidisciplinary Diagnostic Approach, Systematic Review and Meta-Analysis.Journal of clinical medicine research · 2026Article
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Abstract
backgroundMusculoskeletal (MSK) symptoms are a frequent presentation in pediatric patients and may arise from a range of conditions, including juvenile idiopathic arthritis (JIA) and malignancies. Differentiating cancer-related MSK symptoms from JIA at initial presentation remains challenging due to overlapping clinical features. Delays in the diagnosis of malignancy can result in significant morbidity, underscoring the need for reliable diagnostic tools. The ONCOREUM score was developed to distinguish malignancies presenting with arthropathy from JIA and demonstrated high performance in initial validation. However, its utility is limited to patients with arthropathy and does not extend to other forms of MSK involvement. This study aimed to validate the ONCOREUM score in patients with arthropathy and to develop an expanded predictive model to distinguish cancer-related MSK symptoms from JIA.
methodsPatients aged < 16 years diagnosed with cancer or JIA were included. This retrospective study was conducted in two phases: (1) Evaluating the ability of the ONCOREUM score to identify cancer with arthropathy, (2) Developing a model to differentiate cancer-related MSK symptoms from JIA using stepwise logistic regression analysis.
resultsA total of 1,026 patients were reviewed (646 cancer, 380 JIA). In phase 1, 26 cancer patients (4.0%) and 351 JIA patients (92.4%) were included. The ONCOREUM score (cutoff = - 6) had a sensitivity of 88.5% and specificity of 65.0%, with an AUC of 0.77. In phase 2, MSK symptoms were present in 84 (13%) cancer cases (61 hematologic, 23 solid tumors). The best-fitting model was obtained through multivariable analysis: back pain (OR 15.58, 95% CI 2.77-87.64, p < 0.02), nocturnal pain (OR 789.97, 95% CI 51.26-12,175.54, p < 0.0001), limb bone pain (OR 24.11, 95% CI 6.91-84.12, p < 0.0001), pallor (OR 6.30, 95% CI 1.55-25.60, p < 0.01), morning stiffness (OR 0.03, 95% CI 0.002-0.57, p < 0.02), additive arthritis (OR 0.003, 95% CI 0.00-0.04, p < 0.0001), and monoarticular involvement (OR 0.02, 95% CI 0.00-0.23, p < 0.002). This model yielded an AUC of 0.99 (95% CI 0.98-0.99).
conclusionsThe refined predictive model is a promising clinical tool for differentiating cancer-associated MSK symptoms from JIA.
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