Evidence map›Paper›PMID 35523482›Full record

ArticleBMJ open2022

Study designs for clinical trials applied to personalised medicine: a scoping review.

Cecilia Superchi, Florie Brion Bouvier, Chiara Gerardi, Montserrat Carmona, Lorena San Miguel, Luis María Sánchez-Gómez, Iñaki Imaz-Iglesia, Paula Garcia, Jacques Demotes, Rita Banzi and 2 more

Abstract readScoping Review
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Guideline
  4. Review
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  6. Review
  7. Article
  8. Article
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  11. Toward Sex-Specific Biomaterials Innovation: A Perspective.ACS biomaterials science & engineering · 2025
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  13. Review
  14. Genomic medicine and personalized treatment: a narrative review.Annals of medicine and surgery (2012) · 2025
    Review
  15. Article
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  18. In Silico Clinical Trials: Is It Possible?Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Cecilia SuperchiCentre of Research in Epidemiology and Statistics, Université de Paris, Paris, Île-de-France, France cecilia.superchi@gmail.com.ORCID 0000-0002-5375-6018
Florie Brion BouvierCentre of Research in Epidemiology and Statistics, Université de Paris, Paris, Île-de-France, France.ORCID 0000-0001-6364-6106
Chiara GerardiCenter for Health Regulatory Policies, Istituto di Ricerche Farmacologiche Mario Negri, Milano, Lombardia, Italy.ORCID 0000-0002-2459-4769
Montserrat CarmonaAgencia de Evaluación de Tecnologias Sanitarias, Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0002-4680-7745
Lorena San MiguelBelgian Health Care Knowledge Centre (KCE), Brussels, Belgium.ORCID 0000-0002-7155-7303
Luis María Sánchez-GómezAgencia de Evaluación de Tecnologias Sanitarias, Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0003-4358-6032
Iñaki Imaz-IglesiaAgencia de Evaluación de Tecnologias Sanitarias, Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0002-7864-4194
Paula GarciaEuropean Clinical Research Infrastructure Network (ECRIN), Paris, France.
Jacques DemotesEuropean Clinical Research Infrastructure Network (ECRIN), Paris, France.ORCID 0000-0002-0807-0746
Rita BanziCenter for Health Regulatory Policies, Istituto di Ricerche Farmacologiche Mario Negri, Milano, Lombardia, Italy.ORCID 0000-0002-2211-3300
Raphaël PorcherCentre of Research in Epidemiology and Statistics, Université de Paris, Paris, Île-de-France, France.ORCID 0000-0002-5277-4679
PERMIT Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Precision MedicineResearch DesignBiomarkersHumansMedical OncologyRecordsBiomarkersClinical trialPrecision medicineScoping reviewStudy design

Identifiers

PMID35523482
PMCPMC9083424

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.