Optimizing clinical scientific research: the cohort intervention random sampling study with historical controls
Randomized controlled trials (RCTs) are regarded as the highest level of evidence in medical research, but RCTs also have their drawbacks. Over the years, several alternative study designs have been introduced to address these problems. However, many of the alternative designs are often regarded as inferior to RCTs or currently not suitable for widespread implementation due to, for example, ethical or statistical problems. Thus, there is a need for study designs that have the same level of validity as RCTs, but are also suitable for large-scale implementation. The cohort intervention random sampling study (CIRSS) with historical controls meets these requirements, by combining the strengths of abovementioned designs. The CIRSS with historical controls has the potential to optimize implementation of promising new treatments as fluidly and rapidly as possible, representing real-world clinical population. Further research is required to address the range of analyses, implementation, issues, barriers and facilitators and ethical questions related to CIRSS.
Authors
- Edwin R. van den Heuvel (ORCID: https://orcid.org/0000-0001-9157-7224)
- S. Guid Oei (ORCID: https://orcid.org/0000-0002-0157-3332)
- Myrthe van der Ven (ORCID: https://orcid.org/0000-0002-2414-5824)
- M. Beatrijs van der Hout‐van der Jagt (ORCID: https://orcid.org/0000-0002-5805-5333)
- Judith O. E. H. van Laar (ORCID: https://orcid.org/0000-0001-5350-3267)
- Annemarie Fransen (ORCID: https://orcid.org/0000-0001-9391-5397)
- Nadine D de Klerk (ORCID: https://orcid.org/0009-0001-3861-9330)
- Phebe B. Q. Berben (ORCID: https://orcid.org/0009-0004-7909-3795)
Institutions
- Radboud University Nijmegen (NL)
- Máxima Medisch Centrum (NL)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- Journal of Comparative Effectiveness Research
- Published
- 2025-09-16
- DOI
- https://doi.org/10.57264/cer-2024-0168
- Citations
- 2
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 5.26