Prediction Models for Adverse Outcomes Associated with MTX Monotherapy

Rheumatoid Arthritis: Prediction Models for Adverse Outcomes Associated with Methotrexate Monotherapy

2 Mins
Rheumatology

PROMPT initiation of methotrexate (MTX) monotherapy following rheumatoid arthritis (RA) diagnosis is recommended by the European Alliance of Associations for Rheumatology (EULAR) and the American College of Rheumatology (ACR). However, MTX monotherapy is associated with several adverse outcomes, including stroke, myocardial infarction (MI), serious infection, leukopenia, pancytopenia, and malignancy. Therefore, identifying patients with RA who are at high risk of developing these adverse events after commencing MTX monotherapy is imperative.

As a result of this, lead researcher Cynthia Yang, Erasmus University Medical Centre, Rotterdam, the Netherlands, and colleagues, developed prediction models with the aim to evaluate whether these models could identify and predict patients at risk of the adverse outcomes listed above.

The team analysed 15 large-scale claims and electronic health record databases across nine countries using the Patient–Level Prediction Framework from the Observational Health Data Sciences and Informatics initiative.

The study enrolled 21,547 patients aged 18 and over, who had received a diagnosis of RA 5 years prior to starting MTX monotherapy, had been observed for at least 1 year before starting MTX monotherapy, had not previously used disease-modifying antirheumatic drugs or started these within 7 days of commencing MTX monotherapy, had no other diagnoses of inflammatory arthritis, and had no previous history of malignancy.

The team evaluated the prediction model at predicting leukopenia, pancytopenia, and infection within the first 90 days of commencing MTX monotherapy, stroke, or MI within two years of MTX monotherapy, and development of cancer within 5 years of treatment commencement. Results showed that “good discrimination” for identifying patients at high risk of MI, stroke, and serious infection were achieved, whereas only “modest discrimination” for predicting patients at high risk of leukopenia, pancytopenia, and malignancy were achieved.

These findings could be applied clinically, so that patients identified as high risk for MI, stroke, and serious infection could receive closer monitoring during treatment, in order to try and reduce these adverse events and improve care. Yang and colleagues commented that these prediction models could provide clinicians with the opportunity to provide improved, personalised care to patients with RA commencing first line MTX monotherapy.

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