OP0216 DEVELOPMENT AND VALIDATION OF PATIENT-LEVEL PREDICTION MODELS FOR ADVERSE HEALTH OUTCOMES AMONGST ADULT RA PATIENTS INITIATING FIRST-LINE TREATMENT OF METHOTREXATE MONOTHERAPY: A MULTINATIONAL REAL-WORLD COHORT ANALYSIS INCLUDING 164,735 SUBJECTS
Authors: C. Yang, R. Williams, J. Swerdel, M. Jani, T. Duarte-Salles, K. Chatzidionysiou, D. Prieto-Alhambra, P. Ryan, P. Rijnbeek
Journal: Annals of the Rheumatic Diseases (2020)

Background: EULAR guidelines recommend the early initiation of methotrexate (MTX) monotherapy as soon as possible after the diagnosis of rheumatoid arthritis (RA). Evaluating patient-level risks for adverse outcomes after MTX initiation would allow clinicians to provide more personalised care. Objectives: To develop and validate patient-level prediction models for adverse health outcomes including leukopenia, pancytopenia, infection (serious, opportunistic, all), cardiovascular disease (CVD) (myocardial infarction (MI), stroke), and cancer (breast, colorectal, uterus) in adult RA patients initiating first-line treatment of MTX monotherapy Methods: Health data from claims and electronic health records were used including patients from 7 European countries (Spain, Estonia, Netherlands, Belgium, Germany, France, and the UK), the United States of America, Australia, and Japan. All RA patients initiating first-line treatment of MTX monotherapy with at least one year of prior observation were included. Prediction models for the outcomes were developed for a time at risk of 3 months (infections, leukopenia, pancytopenia), 2 years (MI and stroke), and 5 years (cancers) on the Optum© De-Identified Clinformatics® Data Mart Database. Models were developed using LASSO logistic regression and were evaluated using the area under the receiver operator characteristic curve (AUROC) for discrimination and graphically assessed for calibration. The models were externally validated on all other databases. Results: A total of 21,307 subjects were used for training and validated against 143,427 patients from 14 sites. MI (AUROC internal 0.77, AUROC external ranging from 0.49 to 0.78), stroke (AUROC internal 0.78, AUROC external ranging from 0.68 to 0.79) and serious infection (AUROC internal 0.75, AUROC external ranging from 0.63 to 0.79) had good predictive validity [Table 1]. Discrimination for all other outcomes was lower, with all AUC&lt;0.7 in internal validation. For detailed results see: https://data.ohdsi.org/ehdenRaPrediction/ Table 1. Internal (Optum) and external validation results: AUC ROC for discrimination Database Acute MI within 2y Stroke within 2y Serious Infection within 3m Optum (internal) 0.77 0.78 0.75 PanTher 0.76 0.78 0.74 IQVIA_AMBEMR 0.76 0.72 CCAE 0.73 0.73 0.66 IQVIA_GERMANY 0.64 0.70 IQVIA_THIN 0.62 0.65 MDCR 0.68 0.68 0.67 IQVIA_HOSPITAL 0.67 0.63 0.61 MDCD 0.72 0.79 0.63 JMDC 0.49 0.75 0.71 IQVIA_LPDFRANCE 0.69 Estonia 0.67 0.77 0.82 IQVIA_AUS 0.58 IPCI 0.68 SIDIAP 0.65 0.75 Conclusion: Clinical tools were developed that successfully identify subjects at risk of MI, stroke and serious infection at the initiation of first-line MTX therapy. The developed algorithms had good transportability and generally, the models with high AUROC had adequate internal calibration although some external validations show they could benefit from recalibration. For short-term opportunistic and all infections, as well as 5-year cancer models, we were unable to achieve a high enough AUROC to warrant validating externally. Disclosure of Interests: Cynthia Yang: None declared, Ross Williams: None declared, Joel Swerdel Shareholder of: J&amp;J shares, Grant/research support from: Full-time employment salary from Janssen, Consultant of: Janssen employee, Employee of: Janssen, Paid instructor for: Janssen employee, have instructed at conferences, Speakers bureau: Janssen employee, have spoken at conferences, Meghna Jani Speakers bureau: Grifols, Talita Duarte-Salles: None declared, Katerina Chatzidionysiou Consultant of: AbbVie, Pfizer, Lilly., Daniel Prieto-Alhambra Grant/research support from: Professor Prieto-Alhambra has received research Grants from AMGEN, UCB Biopharma and Les Laboratoires Servier, Consultant of: DPA’s department has received fees for consultancy services from UCB Biopharma, Speakers bureau: DPA’s department has received fees for speaker and advisory board membership services from Amgen, Patrick Ryan: None declared, Peter Rijnbeek: None declared