Evidence map›Paper›PMID 26227148›Full record

ArticleBMC medical research methodology2015

Ranking treatments in frequentist network meta-analysis works without resampling methods.

Gerta Rücker, Guido Schwarzer

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 801 papers, 115 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
801citing papers in PubMed, 115 pooled it
23.6field-weighted citation impact, top 1% of its field
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

801 citing papers in PubMed, 115 syntheses or guidelines pooled it, 1,647 citations in OpenAlex.

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741 more citing papers are in PubMed but not listed here.

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

2 authors at 1 institution in 1 country.

Gerta RückerInstitute for Medical Biometry and Statistics, Medical Center - University of Freiburg, Stefan-Meier-Strasse 26, Freiburg, 79104, Germany. ruecker@imbi.uni-freiburg.de.
Guido SchwarzerInstitute for Medical Biometry and Statistics, Medical Center - University of Freiburg, Stefan-Meier-Strasse 26, Freiburg, 79104, Germany. sc@imbi.uni-freiburg.de.
University of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNetwork meta-analysis is used to compare three or more treatments for the same condition. Within a Bayesian framework, for each treatment the probability of being best, or, more general, the probability that it has a certain rank can be derived from the posterior distributions of all treatments. The treatments can then be ranked by the surface under the cumulative ranking curve (SUCRA). For comparing treatments in a network meta-analysis, we propose a frequentist analogue to SUCRA which we call P-score that works without resampling.

methodsP-scores are based solely on the point estimates and standard errors of the frequentist network meta-analysis estimates under normality assumption and can easily be calculated as means of one-sided p-values. They measure the mean extent of certainty that a treatment is better than the competing treatments.

resultsUsing case studies of network meta-analysis in diabetes and depression, we demonstrate that the numerical values of SUCRA and P-Score are nearly identical.

conclusionsRanking treatments in frequentist network meta-analysis works without resampling. Like the SUCRA values, P-scores induce a ranking of all treatments that mostly follows that of the point estimates, but takes precision into account. However, neither SUCRA nor P-score offer a major advantage compared to looking at credible or confidence intervals.

Indexed as

Bayes TheoremMeta-Analysis as TopicReview Literature as TopicAlgorithmsBiomedical ResearchBiometryData Interpretation, StatisticalHumansReproducibility of Results

Identifiers

PMID26227148
PMCPMC4521472
OpenAlexW2111999709

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.