Clinical Trial Informativeness

An informative trial is a trial which delivers answers to research questions and helps to advance medical science.
Individuals participating in clinical trials expect that their efforts will help to bring about these advances, but sometimes poor trial design results in preventable uninformativeness.

An informative trial delivers results efficiently and promptly

What happens with a study that ends uninformatively?

01.

It never finishes, often because insufficient participants were recruited, or

02.

It is never published, because it ended underpowered, or

03.

It is never published, due to poor design or an inadequate analysis plan, or

04.

It is published but focuses on a question other than the original research question, or

05.

It is published only after many years’ delay, or

06.

It is published promptly and stakeholders must accept criticism for wasted money and resources.

What are informativeness “best practices”?

The chance that a study ends informatively increases when:

Statistical analysis plans (SAPs) are completed before recruitment begins.
Trial is adequately powered.
Recruitment is designed to ensure trial reaches its target sample size.
Study is registered with appropriate authorities or regulators prior to study initiation

References

Zarin DA, Goodman SN, Kimmelman J. Harms from uninformative clinical trials. Jama. 2019 Sep 3;322(9):813-4.

Hutchinson, Nora, et al. “The proportion of randomized controlled trials that inform clinical practice.” Elife 11 (2022): e79491.

How to cite the Clinical Trial Risk Tool?

If you would like to cite the tool alone, you can cite:

Wood TA and McNair D. Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness. Gates Open Res 2023, 7:56 doi: 10.12688/gatesopenres.14416.1.

A BibTeX entry for LaTeX users is

@article{Wood_2023,
	doi = {10.12688/gatesopenres.14416.1},
	url = {https://doi.org/10.12688%2Fgatesopenres.14416.1},
	year = 2023,
	month = {apr},
	publisher = {F1000 Research Ltd},
	volume = {7},
	pages = {56},
	author = {Thomas A Wood and Douglas McNair},
	title = {Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness},
	journal = {Gates Open Research}
}