Evidence map›Paper›PMID 20008691›Full record

ArticleArchives of internal medicine2009

A comparison of prediction models for fractures in older women: is more better?

Kristine E Ensrud, Li-Yung Lui, Brent C Taylor, John T Schousboe, Meghan G Donaldson, Howard A Fink, Jane A Cauley, Teresa A Hillier, Warren S Browner, Steven R Cummings and 1 more

Abstract readComparative Study
In one paragraph

Article in Archives of internal medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 9 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

71 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Performance of predictive tools to identify individuals at risk of non-traumatic fracture: a systematic review, meta-analysis, and meta-regression.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2019
    Pooled it
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  7. Hip protectors for preventing hip fractures in older people.The Cochrane database of systematic reviews · 2014
    Pooled it
  8. Performance of risk assessment instruments for predicting osteoporotic fracture risk: a systematic review.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2014
    Pooled it
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  20. Comparing three machine learning approaches to design a risk assessment tool for future fractures: predicting a subsequent major osteoporotic fracture in fracture patients with osteopenia and osteoporosis.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

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Kristine E EnsrudDepartment of Medicine, Minneapolis Veterans Affairs Medical Center, MN 55417, USA. ensru001@umn.edu
Li-Yung Lui
Brent C Taylor
John T Schousboe
Meghan G Donaldson
Howard A Fink
Jane A Cauley
Teresa A Hillier
Warren S Browner
Steven R Cummings
Study of Osteoporotic Fractures Research Group

Funding

Study of Osteoporotic FracturesR01AG005407 · NIA · UNIVERSITY OF CALIFORNIA SAN FRANCISCO · PI CUMMINGS, STEVEN RON, YAFFE, KRISTINE · 1986 to 2016
$23.2M
Study of Osteoporotic FracturesR01AG005394 · NIA · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ENSRUD, KRISTINE · 1986 to 2015
$6.1M
STUDY OF OSTEOPOROTIC FRACTURES: VERTEBRAL FRACTURESR01AR035583 · NIAMS · KAISER FOUNDATION RESEARCH INSTITUTE · PI HILLIER, TERESA A · 1986 to 2005
$3.2M
Study of Osteoporotic Fractures (SOF)R01AG027574 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI HILLIER, TERESA A · 2006 to 2015
$2.6M
Study of Osteoporotic Fractures (SOF)-Pittsburgh ClinicR01AG027576 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CAULEY, JANE ANN · 2006 to 2015
$2.4M
Study of Osteoporotic FracturesR01AR035582 · NIAMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CAULEY, JANE · 1986 to 2005
$2.4M
Study of Osteoporotic FracturesR01AR035584 · NIAMS · UNIVERSITY OF MARYLAND BALTIMORE · PI HOCHBERG, MARC C. · 1986 to 2005
$2.1M
NIAMS NIH HHS AR35582NIAMS NIH HHS AR35583NIAMS NIH HHS AR35584NIAMS NIH HHS R01 AR035582NIAMS NIH HHS R01 AR035583NIAMS NIH HHS R01 AR035584NIA NIH HHS AG005394NIA NIH HHS AG005407NIA NIH HHS AG027574NIA NIH HHS AG027576NIA NIH HHS AG05394NIA NIH HHS AG05407NIA NIH HHS R01 AG005394NIA NIH HHS R01 AG005407NIA NIH HHS R01 AG027574NIA NIH HHS R01 AG027576
6 · The paper itself

Abstract

backgroundA Web-based risk assessment tool (FRAX) using clinical risk factors with and without femoral neck bone mineral density (BMD) has been incorporated into clinical guidelines regarding treatment to prevent fractures. However, it is uncertain whether prediction with FRAX models is superior to that based on parsimonious models.

methodsWe conducted a prospective cohort study in 6252 women 65 years or older to compare the value of FRAX models that include BMD with that of parsimonious models based on age and BMD alone for prediction of fractures. We also compared FRAX models without BMD with simple models based on age and fracture history alone. Fractures (hip, major osteoporotic [hip, clinical vertebral, wrist, or humerus], and any clinical fracture) were ascertained during 10 years of follow-up. Area under the curve (AUC) statistics from receiver operating characteristic curve analysis were compared between FRAX models and simple models.

resultsThe AUC comparisons showed no differences between FRAX models with BMD and simple models with age and BMD alone in discriminating hip (AUC, 0.75 for the FRAX model and 0.76 for the simple model; P = .26), major osteoporotic (AUC, 0.68 for the FRAX model and 0.69 for the simple model; P = .51), and clinical fracture (AUC, 0.64 for the FRAX model and 0.63 for the simple model; P = .16). Similarly, performance of parsimonious models containing age and fracture history alone was nearly identical to that of FRAX models without BMD. The proportion of women in each quartile of predicted risk who actually experienced a fracture outcome did not differ between FRAX and simple models (P > or = .16).

conclusionSimple models based on age and BMD alone or age and fracture history alone predicted 10-year risk of hip, major osteoporotic, and clinical fracture as well as more complex FRAX models.

Indexed as

AgedAge FactorsArea Under CurveBone DensityFemaleFemur NeckFollow-Up StudiesFractures, BoneHumansModels, BiologicalOsteoporosisProspective StudiesRisk AssessmentRisk FactorsROC CurveSurveys and Questionnaires

Identifiers

PMID20008691
PMCPMC2811407

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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.