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The Use Of Real World Evidence (Rwe) To Investigate The Overall Treatment Effects Of Different Lines Of Therapy In Rheumatoid Arthritis

      Objectives

      Due to high costs, randomised clinical trials (RCTs) typically do not include a wide variety of doses and treatments within a single trial. Real-world evidence (RWE) can be used to fill the gaps left by treatment arms or doses not studied in first or second line RCTs. This is illustrated in rheumatoid arthritis (RA). The combined evidence can allow for investigating the area of dosing that can only be studied when all evidence is included. This may impact future dosing strategies that could result in approval of treatment (combinations) that may not have been studied otherwise but could substantially benefit patients with RA.

      Methods

      RCT and RWE data was combined in a network meta-analysis (NMA) to investigate treatment effects in patients with RA. Response surface methods were used to investigate the three dimensional surface of the observed effects as a function of doses for each pair of treatments. Optimization methods were used to establish the optimal treatment/dose region in patients with RA.

      Results

      Results showed that including RWE has increased the totality of evidence with reduced uncertainty in first and second line treatment effects in patients with RA. The greatest evidence of effect was observed in a treatment/dose combination region not yet studied in RCTs

      Conclusions

      The optimal treatment regimen for patients with RA can be investigated by pooling RCT and RWE data in a response surface analysis. The maximum effect may be established in a region of treatment/dose combination not yet studied in a randomised setting. This methodology can also be used to determine which combination of patient’s characteristics will result in the most optimal effect for each (line) of therapy and as a result, provide targeted treatment for (groups of) patients based on their baseline characteristics. Further work could involve optimizing the response in higher dimensions.