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Karcher H, Fu S, Meng J, Ankarfeldt MZ, Efthimiou O, Belger M, Haro JM, Abenhaim L, Nordon C. The "RCT augmentation": a novel simulation method to add patient heterogeneity into phase III trials. BMC Med Res Methodol 2018; 18:75. [PMID: 29980181 PMCID: PMC6035409 DOI: 10.1186/s12874-018-0534-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 06/27/2018] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Phase III randomized controlled trials (RCT) typically exclude certain patient subgroups, thereby potentially jeopardizing estimation of a drug's effects when prescribed to wider populations and under routine care ("effectiveness"). Conversely, enrolling heterogeneous populations in RCTs can increase endpoint variability and compromise detection of a drug's effect. We developed the "RCT augmentation" method to quantitatively support RCT design in the identification of exclusion criteria to relax to address both of these considerations. In the present manuscript, we describe the method and a case study in schizophrenia. METHODS We applied typical RCT exclusion criteria in a real-world dataset (cohort) of schizophrenia patients to define the "RCT population" subgroup, and assessed the impact of re-including each of the following patient subgroups: (1) illness duration 1-3 years; (2) suicide attempt; (3) alcohol abuse; (4) substance abuse; and (5) private practice management. Predictive models were built using data from different "augmented RCT populations" (i.e., subgroups where patients with one or two of such characteristics were re-included) to estimate the absolute effectiveness of the two most prevalent antipsychotics against real-world results from the entire cohort. Concurrently, the impact on RCT results of relaxing exclusion criteria was evaluated by calculating the comparative efficacy of those two antipsychotics in virtual RCTs drawing on different "augmented RCT populations". RESULTS Data from the "RCT population", which was defined with typical exclusion criteria, allowed for a prediction of effectiveness with a bias < 2% and mean squared error (MSE) = 5.8-6.8%. Compared to this typical RCT, RCTs using augmented populations provided improved effectiveness predictions (bias < 2%, MSE = 5.3-6.7%), while returning more variable comparative effects. The impact of augmentation depended on the exclusion criterion relaxed. Furthermore, half of the benefit of relaxing each criterion was gained from re-including the first 10-20% of patients with the corresponding real-world characteristic. CONCLUSIONS Simulating the inclusion of real-world subpopulations into an RCT before running it allows for quantification of the impact of each re-inclusion upon effect detection (statistical power) and generalizability of trial results, thereby explicating this trade-off and enabling a controlled increase in population heterogeneity in the RCT design.
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Affiliation(s)
- Helene Karcher
- Analytica Laser, Audrey House, 16-20 Ely Place, London, EC1N 6SN UK
| | - Shuai Fu
- Analytica Laser, Loerrach, Germany
| | - Jie Meng
- Analytica Laser, Loerrach, Germany
| | - Mikkel Zöllner Ankarfeldt
- Novo Nordisk A/S, Soeborg, Denmark
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Optimed, Clinical Research Centre, Copenhagen University Hospital, Hvidovre, Denmark
| | - Orestis Efthimiou
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Mark Belger
- Eli Lilly and Company, Lilly Research Centre, Windlesham, UK
| | - Josep Maria Haro
- Parc Sanitari Sant Joan de Déu, CIBERSAM, Universitat de Barcelona, Sant Boi de Llobregat, Barcelona, Spain
| | - Lucien Abenhaim
- Analytica Laser, Audrey House, 16-20 Ely Place, London, EC1N 6SN UK
| | - Clementine Nordon
- LASER Core, Paris, France
- INSERM U1178 CESP Maison Blanche Public Hospital, Paris, France
| | - on behalf of the GetReal Consortium Work Package 2
- Analytica Laser, Audrey House, 16-20 Ely Place, London, EC1N 6SN UK
- Analytica Laser, Loerrach, Germany
- Novo Nordisk A/S, Soeborg, Denmark
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Optimed, Clinical Research Centre, Copenhagen University Hospital, Hvidovre, Denmark
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Eli Lilly and Company, Lilly Research Centre, Windlesham, UK
- Parc Sanitari Sant Joan de Déu, CIBERSAM, Universitat de Barcelona, Sant Boi de Llobregat, Barcelona, Spain
- LASER Core, Paris, France
- INSERM U1178 CESP Maison Blanche Public Hospital, Paris, France
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