Evidence map›Paper›PMID 22786670›Full record

ArticleStatistics in medicine2013

Planning future studies based on the conditional power of a meta-analysis.

Verena Roloff, Julian P T Higgins, Alex J Sutton

Registry-linked trialAbstract read
In one paragraph

Article in Statistics in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04383925 (Randomized Trial Evaluating the Non-specific Effects of Different BCG Strains in Guinea-Bissau), which is not on this map. Cited by 29 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 5 pooled it
–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.

NCT04383925 phase4completednot on this mapstarted 2020, after this paper: background citation

Randomized Trial Evaluating the Non-specific Effects of Different BCG Strains in Guinea-Bissau: Effects on Early-life Mortality and Morbidity

TypeinterventionalSponsorBandim Health ProjectRan2020 to 2022Enrolled16,390ConditionsDeath, Infant, Morbidity, InfantArmsBCG-Japan, BCG-Russia
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  16. When Is Enough, Enough? When Are More Observational Epidemiologic Studies Needed to Resolve a Research Question: Illustrations Using Biomarker-Cancer Associations.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Verena RoloffMRC Biostatistics Unit, Cambridge, U.K.
Julian P T Higgins
Alex J Sutton

Funding

Medical Research Council MC_U105285807Medical Research Council U105285807
6 · The paper itself

Abstract

Systematic reviews often provide recommendations for further research. When meta-analyses are inconclusive, such recommendations typically argue for further studies to be conducted. However, the nature and amount of future research should depend on the nature and amount of the existing research. We propose a method based on conditional power to make these recommendations more specific. Assuming a random-effects meta-analysis model, we evaluate the influence of the number of additional studies, of their information sizes and of the heterogeneity anticipated among them on the ability of an updated meta-analysis to detect a prespecified effect size. The conditional powers of possible design alternatives can be summarized in a simple graph which can also be the basis for decision making. We use three examples from the Cochrane Database of Systematic Reviews to demonstrate our strategy. We demonstrate that if heterogeneity is anticipated, it might not be possible for a single study to reach the desirable power no matter how large it is.

Indexed as

Meta-Analysis as TopicModels, StatisticalResearch DesignAntibiotic ProphylaxisDrug TherapyEarEsophageal NeoplasmsHumansImmunotherapyRhinitis, AllergicRhinitis, Allergic, Perennial

Identifiers

PMID22786670
PMCPMC3562483

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.