Evidence map›Paper›PMID 42008168›Full record

ArticleOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2026

Development and external validation of prediction models for major osteoporotic fracture and hip fracture in people with intellectual disability.

Margaret Smith, Jan Roast, Gary S Collins, Tim A Holt, Valeria Frighi

Abstract readValidation Study
In one paragraph

Article in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Margaret SmithNuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, Oxford, UK.
Jan RoastDimensions UK, RG7 4SA, Reading, UK.
Gary S CollinsDepartment of Applied Health Sciences, School of Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.
Tim A HoltNuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, Oxford, UK. timholt@nhs.net.
Valeria FrighiDepartment of Psychiatry, University of Oxford, OX3 7JX, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People with intellectual disability (ID) have a relatively high incidence of fractures, so current risk prediction models are not appropriate. A new prediction model for people with ID showed good calibration and discrimination in external validation. This is the first such prediction model developed for people with ID. PURPOSE: Compared with the general population, people with intellectual disabilities (ID) have higher incidences of major osteoporotic fracture (MOF) and hip fracture (HF), and they develop osteoporosis at a younger age. The rate of HF in those aged 50 years and over is two times higher than that in women without ID and four times higher than that in men without ID. It is essential to identify people with ID who are at risk of such fractures so that a targeted fracture prevention strategy can be designed. However, current fracture prediction models are derived from the general population and may underestimate risk in the ID population.

methodsPrediction models (IDFracture) for the 10-year risk of HF and MOF were developed and validated in populations of people with ID aged 30-79 years. Models were developed in the CPRD GOLD database and temporally validated in the Aurum database. The predictors included those in current fracture prediction models and ID-specific predictors such as Down syndrome. All the predictors were included in the Cox regression models. Bootstrapping was used to adjust for overfitting.

resultsThe development cohort included 38,665 people with IDs, 1045 with MOFs and 360 with HFs within 10 years. The external validation cohort included 76,385 people, 2420 MOFs and 1001 HFs. Discrimination, as judged by the C statistic, was good: MOF 0.775 and HF 0.839. The calibration was also good but tended to overpredict at the highest predicted risks.

conclusionIDFracture has potential as a screening tool in clinical practice to identify people with ID who are at increased risk of MOF and HF.

Indexed as

Hip FracturesIntellectual DisabilityOsteoporotic FracturesAdultAgedDatabases, FactualFemaleHumansMaleMiddle AgedPrediction AlgorithmsReproducibility of ResultsRisk AssessmentRisk Factorsclinical prediction rulecohort studieship fracturesintellectual disabilityosteoporotic fracturesrisk factors

Identifiers

PMID42008168
PMCPMC13190501

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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.