GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world.

Panayidou, Klea; Gsteiger, Sandro; Egger, Matthias; Kilcher, Gablu; Carreras, Máximo; Efthimiou, Orestis; Debray, Thomas P A; Trelle, Sven; Hummel, Noemi (2016). GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world. Research Synthesis Methods, 7(3), pp. 264-277. Wiley 10.1002/jrsm.1202

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The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real-world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi-state models, discrete event simulation models, physiology-based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real-world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

Item Type:

Journal Article (Review Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine
04 Faculty of Medicine > Pre-clinic Human Medicine > CTU Bern

UniBE Contributor:

Gsteiger, Sandro; Egger, Matthias; Kilcher, Gablu; Trelle, Sven and Hummel, Noemi

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

1759-2879

Publisher:

Wiley

Language:

English

Submitter:

Doris Kopp Heim

Date Deposited:

12 Dec 2016 18:27

Last Modified:

26 Sep 2017 18:10

Publisher DOI:

10.1002/jrsm.1202

PubMed ID:

27529762

Uncontrolled Keywords:

comparative effectiveness research efficacy-effectiveness gap health technology assessment mathematical modelling prediction

BORIS DOI:

10.7892/boris.91445

URI:

https://boris.unibe.ch/id/eprint/91445

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