title: GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world.
abstract: 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.
authors.affiliation: Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
authors.forename: Klea
authors.initials: K
authors.lastname: Panayidou
authors.affiliation: Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
authors.forename: Sandro
authors.initials: S
authors.lastname: Gsteiger
authors.affiliation: Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland. matthias.egger@ispm.unibe.ch.
authors.forename: Matthias
authors.initials: M
authors.lastname: Egger
authors.affiliation: Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
authors.forename: Gablu
authors.initials: G
authors.lastname: Kilcher
authors.affiliation: F. Hoffmann-La Roche AG, Basel, Switzerland.
authors.forename: Máximo
authors.initials: M
authors.lastname: Carreras
authors.affiliation: Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
authors.forename: Orestis
authors.initials: O
authors.lastname: Efthimiou
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.|Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
authors.forename: Thomas P A
authors.initials: TP
authors.lastname: Debray
authors.affiliation: Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.|Department of Clinical Research, Clinical Trials Unit, Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
authors.forename: Sven
authors.initials: S
authors.lastname: Trelle
authors.affiliation: Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
authors.forename: Noemi
authors.initials: N
authors.lastname: Hummel
mesh_terms: D002318:Cardiovascular Diseases / Q000188:drug therapy; D003198:Computer Simulation; D016206:Databases, Bibliographic; D004341:Drug Evaluation; D004358:Drug Therapy / Q000379:methods*; D006801:Humans; D016014:Linear Models; D008659:Metabolic Diseases / Q000188:drug therapy; D008962:Models, Theoretical; D009422:Nervous System Diseases / Q000188:drug therapy; D004364:Pharmaceutical Preparations; D016032:Randomized Controlled Trials as Topic; D015203:Reproducibility of Results; D012984:Software
chemical_list: D004364:Pharmaceutical Preparations
keywords: comparative effectiveness research; efficacy-effectiveness gap; health technology assessment; mathematical modelling; prediction