Clinical trials: what a waste
Clinical trials: what a waste is a research paper published in BMJ (2014). On theSindex it has a DataRank of 0.626. It has been cited 64 times.
Abstract
Trials that are unregistered, unfinished, unpublished, unreachable, or simply irrelevant Randomized controlled trials are the gold standard tool for evaluating interventions. Nevertheless, the utility of this excellent tool is contingent on how it is used. Chapman and colleagues (doi:10.1136/bmj.g6870) show this in a sample of 395 trials relevant to surgical practice that were registered in ClincialTrials.gov between 2008 and 2009.1 By the end of 2013, 21% were discontinued, 34% of those that were completed were not published, and for 77% of the trials that had uncertain fate no way existed to reach investigators to find what had happened to them. This work adds to several other empirical evaluations showing that evidence from randomized controlled trials is wasted at multiple stages from conception to publication and beyond.2 3 4 5 6 7 8 9 10 11 12 Many trials are entirely lost, as they are not even registered. Substantial diversity probably exists across specialties, countries, and settings. Overall, in a survey conducted in 2012, only 30% of journal editors requested or encouraged trial registration.2 Among registered trials, a sizeable fraction are never completed. In some cases, discontinuation may be the best …
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FAIR Checklist
Context only (not used in score)- Has DOI
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DataRank Breakdown
Base Score Contribution
0.626
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.