ArticleClinical and translational science2013
Statistical evaluation of the use of concurrent controls in treatment screening studies.
Article in Clinical and translational science, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed, 0 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A well-designed pilot study can advance science by providing essential preliminary data to support or motivate further research, refine study logistics, and demonstrate proof of concept. Often, the outcomes of such studies can be quantified by a success/failure dichotomy. For example, a novel compound may show activation of a neural pathway, or it may not. When an intervention's efficacy is quantified using a dichotomous outcome, probability mass functions can be enumerated to determine the probability that the observed result from a pilot study supports further evaluation of the intervention since there is only a finite, and often small, number of sample configurations possible. The purpose of this research was to determine the probability of an "efficacy signal" for pilot studies using one- and two-sample pilot study designs. Efficacy signal was defined as the probability of observing a more favorable response proportion relative to a historical control (one-sample setting) or to a concurrent control (two-sample setting). An enumeration study (exact simulation) was conducted to calculate the efficacy signal probability. One-sample study designs yielded higher probability of determining an efficacy signal than the two-sample setting; however, sampling variation must be accounted for. A 68% score confidence interval is recommended for this purpose.
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What OpenQuestion holds
Registered trials
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.