Evidence map›Paper›PMID 40660461›Full record

ArticleBiometrical journal. Biometrische Zeitschrift2025

Rethinking Probability of Success as Bayes Utility.

Fulvio De Santis, Stefania Gubbiotti, Francesco Mariani

Abstract read
In one paragraph

Article in Biometrical journal. Biometrische Zeitschrift, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Fulvio De SantisDepartment of Statistical Sciences, Sapienza University of Rome, Rome, Italy.ORCID 0000-0003-1729-1759
Stefania GubbiottiDepartment of Statistical Sciences, Sapienza University of Rome, Rome, Italy.ORCID 0000-0002-1108-0953
Francesco MarianiDepartment of Statistical Sciences, Sapienza University of Rome, Rome, Italy.ORCID 0000-0002-0239-1741

Funding

Sapienza Università di Roma
6 · The paper itself

Abstract

In the hybrid frequentist-Bayesian approach, the probability of success (PoS) of a trial is the expected value of the traditional power function of a test with respect to a design prior assigned to the parameter under scrutiny. However, this definition is not univocal and some of the proposals do not lack of potential drawbacks. These problems are related to the fact that such definitions are all based on the probability of rejecting the null hypothesis rather than on the probability of choosing the correct hypothesis, be it the null or the alternative. In this article, we propose a unifying, decision-theoretic approach that yields a new definition of PoS as the expected utility of the trial (u-PoS), that is, as the expected probability of making the correct choice between the two hypotheses. This proposal shows a conceptual advantage over previous definitions of PoS; moreover, it produces smaller optimal sample sizes whenever the design prior assigns positive probability to the null hypothesis.

Indexed as

BiometryBayes TheoremHumansProbabilityassuranceBayesian powerBayes riskclinical trialssample size determination

Identifiers

PMID40660461
PMCPMC12260142

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.