Prediction of 3 months MTX non-response (DAS28>3.2) in early rheumatoid arthritis
Validation of prediction model to identify DMARD-naïve rheumatoid arthritis patients with high risk of insufficient response to MTX using clinical variables.
Författare till forskningsprojekt: Gosselt HR, Verhoeven MMA, de Rotte MCFJ, Pluijm SMF, Muller IB, Jansen G, Tekstra J, Bulatović-Ćalasan M, Heil SG, Lafeber FPJG, Hazes JMW, and de Jonge R.
Version: 1.31
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  • Reumatologi
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Probability of MTX non-response after 3 months of treatment: %

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Villkorlig information

How this model should be used: 
This prediction model could assist in identification of insufficient responders at diagnosis. For patients with high probability of insufficient response to MTX, additional biologics or JAK-inhibitors could be prescribed. For those with low probabilities of insufficient response, these expensive treatments could be spared. This distinction at diagnosis could save precious time for insufficient responders, allowing earlier control of disease activity resulting in better long-term outcomes.

Model performance: 
Discriminative power of the model was assessed through evaluating the area under the receiver operating characteristic curve (AUC). The AUC of the model was 0.75 (95% CI: 0.69 – 0.81), indicating that the model correctly classified patients in 75% of the cases.

Goodness-of-fit between the predicted probabilities and observed values was tested using the Hosmer-Lemeshow test. The associated P-value was 0.634, indicating good model fit. 

Decisions on appropriate risk cut-offs:
Taking into consideration the “window of opportunity” for optimal treatment we consider it crucial to adequately treat insufficient MTX responders with additional bDMARDs/tsDMARDs. Therefore, our goal for this prediction model was to identify as many insufficient responders as possible, while at the same time attempting to restrict the use of bDMARDs/tsDMARDs to those patients who really need them, hence to avoid misclassification of sufficient responders. Considering this, a cut-off probability of 70% (of insufficient response) could be chosen.

At this cut-off, 75% of patients classified as insufficient responder match actual insufficient responders (PPV) and could be treated with additional bDMARDs/tsDMARDs. Additionally, at this cut-off 86% of all sufficient responders would be correctly classified as such (specificity) and could be spared additional treatment.

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