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CDAI and SDAI scores improve prediction of osteoporosis in patients with rheumatoid arthritisNew scores help identify osteoporosis risk in rheumatoid arthritis patients

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Key Takeaway
Note that CDAI and SDAI improve osteoporosis prediction in RA, but CBC-derived indices do not add significant value.

This guideline presents a cross-sectional analysis of 226 patients with rheumatoid arthritis to identify predictors of prevalent osteoporosis. The analysis evaluated clinical reference models, disease-activity scores, and CBC-derived indices including NLR, PLR, MLR, SII, SIRI, and AISI.

Key findings indicate that older age, female sex, lower BMI, and higher CDAI were associated with osteoporosis. The clinical reference model had an AUC of 0.833. Adding CDAI increased the AUC to 0.892 (P = 0.005), and adding SDAI increased the AUC to 0.877 (P = 0.018). In contrast, adding CRP to DAS28-ESR resulted in a negligible AUC change (0.863 to 0.869, P = 0.491), and the addition of any CBC-derived index to the extended model resulted in an AUC change of no more than 0.0014 (P $\geq$ 0.467).

The authors conclude that while certain disease-activity scores provide modest incremental discrimination, CBC-derived indices do not provide significant added value once conventional information is included. These findings do not support the use of CBC-derived indices as substitutes for standard risk assessments like FRAX or DXA.

How this fits prior evidence

This guideline addresses the identification of osteoporosis in patients with rheumatoid arthritis. While previous evidence highlighted that autoantibody-stratified DMARD selection does not improve DAS scores in RA, this current evidence focuses on risk stratification for osteoporosis. The findings suggest that while specific disease-activity scores like CDAI and SDAI offer some predictive value, CBC-derived indices do not provide additional utility over standard clinical assessments.

Living with rheumatoid arthritis often means facing a higher risk of osteoporosis, a condition where bones become weak and brittle. Doctors need reliable ways to identify who is at risk so they can take action early. This study looked at how different scoring systems could help predict bone loss in 226 patients with rheumatoid arthritis.

Researchers found that adding certain disease-activity scores, like CDAI or SDAI, improved the accuracy of identifying osteoporosis compared to standard clinical models. However, other markers like those derived from a complete blood count (CBC) did not add much extra information once the standard clinical data were already included.

While these specific scores offer some extra help in identifying risk, the data do not suggest they should replace standard tools like FRAX scores or bone density scans. These findings provide a clearer picture of how current clinical tools work together to monitor bone health in patients with inflammatory conditions.

What this means for you:
Specific disease-activity scores improve the accuracy of identifying osteoporosis in rheumatoid arthritis patients.

Common questions

How does this help patients with rheumatoid arthritis?

The study found that certain disease-activity scores, specifically CDAI and SDAI, improved the accuracy of identifying osteoporosis. This helps doctors better identify which patients are at risk for bone loss, allowing for more focused care.

Are blood tests useful for finding osteoporosis in these patients?

The study looked at indices derived from a complete blood count (CBC). However, these specific blood markers did not provide significant extra information once standard clinical data were already included in the model.

Should these new scores replace current screening methods?

No, the data do not support using these scores as substitutes for current standard tools like FRAX scores or DXA bone density scans. They are meant to complement, not replace, existing clinical risk assessments.

Study Details

Study typeGuideline
EvidenceLevel 5
PublishedAug 2026
View Original Abstract ↓
Osteoporosis (OP) is a frequent comorbidity in rheumatoid arthritis (RA). This study compared the performance of RA disease-activity scores with complete blood count (CBC)-derived indices for identifying prevalent OP. We retrospectively included 226 consecutive patients with RA who underwent dual-energy X-ray absorptiometry (DXA). Predictors comprised age, sex, body mass index (BMI), disease activity (DAS28-ESR, DAS28-CRP, CDAI, and SDAI), ESR, CRP, and six CBC-derived indices (NLR, PLR, MLR, SII, SIRI, and AISI). Logistic and linear regression, receiver-operating-characteristic (ROC) analysis with paired DeLong tests, decision curve analysis (DCA), and four-knot restricted cubic spline (RCS) analyses were performed. Older age, female sex, lower BMI, and higher CDAI were associated with OP. The five-covariate clinical reference model had an AUC of 0.833. Adding CDAI increased the AUC to 0.892 (ΔAUC, 0.059; P = 0.005), and adding SDAI increased it to 0.877 (ΔAUC, 0.044; P = 0.018), although the ROC curves overlapped substantially. In parallel fully adjusted models, none of the six CBC-derived indices was independently associated with OP (all P≥0.142; apparent AUCs, 0.892–0.895). Adding CRP after DAS28-ESR changed the AUC from 0.863 to 0.869 (ΔAUC, 0.006; P = 0.491). In the extended discrimination model, adding any CBC-derived index changed the AUC by no more than 0.0014 (all P≥0.467). DCA showed small, threshold-dependent differences in net benefit rather than consistent separation between models. Four-knot RCS analyses showed evidence of nonlinearity for DAS28-ESR (P for nonlinearity=0.007) and SDAI (P for nonlinearity Disease-activity scores provided modest incremental discrimination beyond established clinical factors, whereas CBC-derived indices added little once conventional inflammatory and disease-activity information was included. These data do not support calculating CBC-derived indices solely to identify prevalent OP or using them as substitutes for guideline-based clinical risk assessment, FRAX, or DXA. The findings do not establish a new screening or treatment threshold.
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