A novel clinical prediction model for hip fractures: a development and validation study in the total population of Sweden.

Bone specific treatment Guidelines Hip fractures Prediction model

Journal

EClinicalMedicine
ISSN: 2589-5370
Titre abrégé: EClinicalMedicine
Pays: England
ID NLM: 101733727

Informations de publication

Date de publication:
Nov 2024
Historique:
received: 17 06 2024
revised: 19 09 2024
accepted: 23 09 2024
medline: 21 10 2024
pubmed: 21 10 2024
entrez: 21 10 2024
Statut: epublish

Résumé

Low bone density and osteoporosis are indications for bone-specific treatment. However, given the limited availability of bone density data in clinical practice and the fact that most patients with hip fracture do not have osteoporosis, accurate prediction of hip fracture risk in the absence of bone density data would be crucial. This development and validation study included the entire Swedish population aged 50 years or older in 2005 (N = 3,340,977) and was conducted by cross-linking data from nationwide registers. Potential predictive variables included diagnoses, prescription medications, familial factors, frailty-related factors, and socioeconomic factors. The primary endpoint was the 5-year risk of hip fracture. Fracture prediction algorithms were developed and validated using multivariable models. Model performance and validation was also examined in a sub cohort restricted to 504,431 individuals with non-Swedish background. During a total follow-up of 15.2 million person-years, 87,089 individuals suffered a hip fracture within 5 years. In the final prediction model, 19 variables were associated with a population attributable fraction of 93.9% (95% CI, 93.7-94.1) in women and 92.7% (95% CI, 92.2-93.0) in men. The strongest predictor, besides old age, was the use of homemaker service, with a 5-year risk of hip fracture of 7.8% in women and 4.7% in men. The diagnoses most strongly predicting the 5-year risk of hip fracture was Parkinson's disease (6.8% in women, 4.6% in men) and dementia (6.1% in women, 3.6% in men). Validation of the prediction model suggested that the optimal threshold for treatment with bone-specific agents was an estimated 5-year hip fracture risk of 3%. Assuming a threshold of 3% and a 30% relative risk reduction from bone-specific treatment, the number needed to treat to prevent one hip fracture was estimated to 36 in women and 52 in men. Similar results were obtained in the sub cohort with non-Swedish background. A clinical prediction model developed and validated in the total Swedish population could predict the risk of hip fractures with high precision even in absence of data on bone density. The model was associated with a population attributable fraction for hip fracture of more than 90%, and the strongest predictor besides old age was the use of homemaker service, which likely reflect frailty. Based on the model, individuals with an estimated 5-year risk of hip fracture of at least 3% could be considered for bone-specific treatment. None.

Sections du résumé

Background UNASSIGNED
Low bone density and osteoporosis are indications for bone-specific treatment. However, given the limited availability of bone density data in clinical practice and the fact that most patients with hip fracture do not have osteoporosis, accurate prediction of hip fracture risk in the absence of bone density data would be crucial.
Methods UNASSIGNED
This development and validation study included the entire Swedish population aged 50 years or older in 2005 (N = 3,340,977) and was conducted by cross-linking data from nationwide registers. Potential predictive variables included diagnoses, prescription medications, familial factors, frailty-related factors, and socioeconomic factors. The primary endpoint was the 5-year risk of hip fracture. Fracture prediction algorithms were developed and validated using multivariable models. Model performance and validation was also examined in a sub cohort restricted to 504,431 individuals with non-Swedish background.
Findings UNASSIGNED
During a total follow-up of 15.2 million person-years, 87,089 individuals suffered a hip fracture within 5 years. In the final prediction model, 19 variables were associated with a population attributable fraction of 93.9% (95% CI, 93.7-94.1) in women and 92.7% (95% CI, 92.2-93.0) in men. The strongest predictor, besides old age, was the use of homemaker service, with a 5-year risk of hip fracture of 7.8% in women and 4.7% in men. The diagnoses most strongly predicting the 5-year risk of hip fracture was Parkinson's disease (6.8% in women, 4.6% in men) and dementia (6.1% in women, 3.6% in men). Validation of the prediction model suggested that the optimal threshold for treatment with bone-specific agents was an estimated 5-year hip fracture risk of 3%. Assuming a threshold of 3% and a 30% relative risk reduction from bone-specific treatment, the number needed to treat to prevent one hip fracture was estimated to 36 in women and 52 in men. Similar results were obtained in the sub cohort with non-Swedish background.
Interpretation UNASSIGNED
A clinical prediction model developed and validated in the total Swedish population could predict the risk of hip fractures with high precision even in absence of data on bone density. The model was associated with a population attributable fraction for hip fracture of more than 90%, and the strongest predictor besides old age was the use of homemaker service, which likely reflect frailty. Based on the model, individuals with an estimated 5-year risk of hip fracture of at least 3% could be considered for bone-specific treatment.
Funding UNASSIGNED
None.

Identifiants

pubmed: 39430614
doi: 10.1016/j.eclinm.2024.102877
pii: S2589-5370(24)00456-5
pmc: PMC11490797
doi:

Types de publication

Journal Article

Langues

eng

Pagination

102877

Informations de copyright

© 2024 The Author(s).

Déclaration de conflit d'intérêts

We declare no competing interests.

Auteurs

Peter Nordström (P)

Department of Public Health and Caring Sciences, Clinical Geriatrics, Uppsala University, Uppsala, Sweden.

Viktor H Ahlqvist (VH)

Department of Public Health and Caring Sciences, Clinical Geriatrics, Uppsala University, Uppsala, Sweden.
Department of Biomedicine, Aarhus University, Aarhus, Denmark.
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Marcel Ballin (M)

Department of Public Health and Caring Sciences, Clinical Geriatrics, Uppsala University, Uppsala, Sweden.
Centre for Epidemiology and Community Medicine, Region Stockholm, Stockholm, Sweden.

Anna Nordström (A)

Department of Medical Sciences, Rehabilitation Medicine, Uppsala University, Uppsala, Sweden.
School of Sport Sciences, UiT, The Arctic University of Norway, Tromsø, Norway.

Classifications MeSH