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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis
Medical Decision Making, Volume 38, No. 6, Year 2018
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Description
Background. Decision makers often need to assess the real-world effectiveness of new drugs prelaunch, when phase II/III randomized controlled trials (RCTs) but no other data are available. Objective. To develop a method to predict drug effectiveness prelaunch and to apply it in a case study in rheumatoid arthritis (RA). Methods. The approach 1) identifies a market-approved treatment (S) currently used in a target population similar to that of the new drug (N); 2) quantifies the impact of treatment, prognostic factors, and effect modifiers on clinical outcome; 3) determines the characteristics of patients likely to receive N in routine care; and 4) predicts treatment outcome in simulated patients with these characteristics. Sources of evidence include expert opinion, RCTs, and observational studies. The framework relies on generalized linear models. Results. The case study assessed the effectiveness of tocilizumab (TCZ), a biologic disease-modifying antirheumatic drug (DMARD), combined with conventional DMARDs, compared to conventional DMARDs alone. Rituximab (RTX) combined with conventional DMARDs was identified as treatment S. Individual participant data from 2 RCTs and 2 national registries were analyzed. The model predicted the 6-month changes in the Disease Activity Score 28 (DAS28) accurately: the mean change was -2.101 (standard deviation [SD] = 1.494) in the simulated patients receiving TCZ and conventional DMARDs compared to -1.873 (SD = 1.220) in retrospectively assessed observational data. It was -0.792 (SD = 1.499) in registry patients treated with conventional DMARDs. Conclusion. The approach performed well in the RA case study, but further work is required to better define its strengths and limitations. © The Author(s) 2018.
Authors & Co-Authors
Ruffieux, Yann
Switzerland, Bern
University of Bern
Efthimiou, Orestis
Switzerland, Bern
University of Bern
Gsteiger, Sandro
Switzerland, Basel
F. Hoffmann-la Roche ag
Finckh, Axel
Switzerland, Geneva
Hôpitaux Universitaires de Genève
Salanti, Georgia
Switzerland, Bern
University of Bern
Egger, Matthias
Switzerland, Bern
University of Bern
Statistics
Citations: 5
Authors: 6
Affiliations: 4
Identifiers
Doi:
10.1177/0272989X18775975
ISSN:
0272989X
Study Design
Randomised Control Trial
Cross Sectional Study
Case Study
Study Approach
Qualitative