Evidence map›Paper›PMID 23381029›Full record

ReviewNature reviews. Endocrinology2013

Genetic profiling and individualized assessment of fracture risk.

Tuan V Nguyen, John A Eisman

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Endocrinology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Assessing the clinical utility of genetic profiling in fracture risk prediction: a decision curve analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2021
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. RANKL and OPG gene polymorphisms: associations with vertebral fractures and bone mineral density in premenopausal systemic lupus erythematosus.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2015
    Article
  10. Review
  11. Effect of interleukin-6 polymorphism on fracture risk.International journal of clinical and experimental medicine · 2015
    Article
  12. Review
  13. Review
  14. Comparison between various fracture risk assessment tools.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2014
    Review
  15. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Tuan V NguyenOsteoporosis and Bone Biology Program, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Sydney, NSW 2010, Australia. t.nguyen@ garvan.org.au
John A Eisman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoporosis and its consequence of fragility fracture impose a considerable demand on health-care services because fracture is associated with a series of adverse events, including re-fracture and mortality. One of the major priorities in osteoporosis care is the development of predictive models to identify individuals at high risk of fracture for early intervention and management. Existing predictive models include clinical factors and anthropometric characteristics but have not considered genetic variants in the prediction. Genome-wide association studies conducted in the past decade have identified several genetic variants relevant to fracture risk. These genetic variants are common in frequency but have very modest effect sizes. A remaining challenge is to use these genetic data to individualize fracture risk assessment on the basis of an individual's genetic risk profile. Empirical and simulation studies have shown that the usefulness of a single genetic variant for fracture risk assessment is very limited, but a profile of 50 genetic variants, each with odds ratio ranging from 1.02 to 1.15, could improve the accuracy of fracture prediction beyond that obtained by use of existing clinical risk factors. Thus, genetic profiling when integrated with existing risk assessment models could inform a more accurate prediction of fracture risk in an individual.

Indexed as

Bone DensityFemaleFractures, BoneGenetic Predisposition to DiseaseGenetic VariationHumansMaleOdds RatioOsteoporosisPolymorphism, Single NucleotideRisk AssessmentRisk FactorsSensitivity and SpecificityTranscriptome

Identifiers

PMID23381029

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.