Evidence map›Paper›PMID 9504931›Full record

ArticleGenetics1998

Meta-analysis of linkage data under worst-case conditions: a demonstration using the human OB region.

D B Allison, M Heo

Abstract read
In one paragraph

Article in Genetics, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 4 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.

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

22 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Pooled it
  5. Review
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  14. Searching for osteoporosis genes in the post-genome era: progress and challenges.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2003
    Review
  15. Article
  16. Article
  17. Article
  18. The significance of not finding a gene.American journal of human genetics · 2001
    Article
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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.

D B AllisonObesity Research Center, St. Luke's/Roosevelt Hospital Center, Columbia University College of Physicians & Surgeons, New York, New York 10025, USA. dba8@columbia.edu
M Heo

Funding

RESEARCH TRAININGP30DK026687 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI Anthony W Ferrante, DYMPNA GALLAGHER · 1986 to 2026
$33.0M
QUANTITATIVE SYNTHESIS OF CLINICAL OBESITY RESEARCHR01DK051716 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI ALLISON, DAVID B · 1996 to 1999
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GENETICS OF OBESITY AND RELATED RISKS AMONG BLACK WOMENR29DK047256 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI ALLISON, DAVID B · 1994 to 1998
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NIDDK NIH HHS P30DK26687NIDDK NIH HHS R01DK51716NIDDK NIH HHS R29DK47256
6 · The paper itself

Abstract

To date, few methods have been developed explicitly for meta-analysis of linkage analyses. Moreover, the methods that have been developed or suggested generally depend on certain ideal situations and have not been widely applied. In this article, we apply standard statistical theory and meta-analytic techniques in novel ways to five published papers discussing the evidence of linkage of body mass index (BMI) to the region of the human genome containing the OB gene. These methods are "inference based," meaning that they allow one to make statements about the statistical significance of the entire body of evidence. As currently developed, they do not allow specific statements to be made about the amount of variance explained by any putative locus or allow precise confidence intervals to be placed around the putative location of a linked locus. By applying these techniques to the literature on linkage in the human OB gene region, we are able to show that the evidence for linkage somewhere in the region is extremely strong (P = 1.5 x 10[-5]).

Indexed as

Meta-Analysis as TopicBody Mass IndexGenetic LinkageGenetic MarkersHumansLeptinModels, GeneticPhenotypeProteinsStatistics as TopicGenetic MarkersLeptinProteins

Identifiers

PMID9504931
PMCPMC1459818

What OpenQuestion holds

Textmetadata
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.