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Med Decis Making. 2018 Aug;38(6):719-729. doi: 10.1177/0272989X18775975.

Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis.

Author information

1
Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
2
University of Ioannina, School of Medicine, Ioannina, Ioannina, Greece.
3
Department of Rheumatology, Immunology and Allergology, University Hospital and University of Bern, Switzerland.
4
F. Hoffmann-La Roche Ltd., MORSE-Health Technology Assessment Group, Basel, Switzerland.
5
University Hospital of Geneva (HUG), Geneva, Switzerland.
6
Amgen Ltd, Cambridge, Great Britain, Cambridge, Cambridgeshire, UK.

Abstract

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.

KEYWORDS:

effect modifier; efficacy-effectiveness gap; prediction model; prognostic factor; rheumatoid arthritis; treatment predictor

PMID:
30074882
DOI:
10.1177/0272989X18775975

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