Study designs for clinical trials applied to personalised medicine: a scoping review
| Autor: | Superchi, Cecilia, Brion Bouvier, Florie, Gerardi, Chiara, Carmona, Montserrat, San Miguel, Lorena, Sanchez-Gomez, Luis Maria, Imaz-Iglesia, Iñaki, Garcia, Paula, Demotes, Jacques, Banzi, Rita, Porcher, Raphaël, PERMIT Group |
|---|---|
| Přispěvatelé: | Unión Europea. Comisión Europea. H2020 |
| Jazyk: | angličtina |
| Předmět: | |
| Zdroj: | BMJ Open Repisalud Instituto de Salud Carlos III (ISCIII) |
| ISSN: | 2044-6055 |
| DOI: | 10.1136/bmjopen-2021-052926 |
| Popis: | ObjectivePersonalised medicine (PM) allows treating patients based on their individual demographic, genomic or biological characteristics for tailoring the ‘right treatment for the right person at the right time’. Robust methodology is required for PM clinical trials, to correctly identify groups of participants and treatments. As an initial step for the development of new recommendations on trial designs for PM, we aimed to present an overview of the study designs that have been used in this field.DesignScoping review.MethodsWe searched (April 2020) PubMed, Embase and the Cochrane Library for all reports in English, French, German, Italian and Spanish, describing study designs for clinical trials applied to PM. Study selection and data extraction were performed in duplicate resolving disagreements by consensus or by involving a third expert reviewer. We extracted information on the characteristics of trial designs and examples of current applications of these approaches. The extracted information was used to generate a new classification of trial designs for PM.ResultsWe identified 21 trial designs, 10 subtypes and 30 variations of trial designs applied to PM, which we classified into four core categories (namely, Master protocol, Randomise-all, Biomarker strategy and Enrichment). We found 131 clinical trials using these designs, of which the great majority were master protocols (86/131, 65.6%). Most of the trials were phase II studies (75/131, 57.2%) in the field of oncology (113/131, 86.3%). We identified 34 main features of trial designs regarding different aspects (eg, framework, control group, randomisation). The four core categories and 34 features were merged into a double-entry table to create a new classification of trial designs for PM.ConclusionsA variety of trial designs exists and is applied to PM. A new classification of trial designs is proposed to help readers to navigate the complex field of PM clinical trials. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|