Prediction of Osteoporotic Fractures in Elderly Individuals: A Derivation and Internal Validation Study Using Healthcare Administrative Data.
FRACTURE RISK ASSESSMENT
GENERAL POPULATION STUDIES
OSTEOPOROSIS
Journal
Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
ISSN: 1523-4681
Titre abrégé: J Bone Miner Res
Pays: United States
ID NLM: 8610640
Informations de publication
Date de publication:
12 2021
12 2021
Historique:
revised:
11
07
2021
received:
29
03
2021
accepted:
04
09
2021
pubmed:
8
9
2021
medline:
24
12
2021
entrez:
7
9
2021
Statut:
ppublish
Résumé
In Canada and other countries, osteoporosis is monitored as part of chronic disease population surveillance programs. Although fractures are the principal manifestation of osteoporosis, very few algorithms are available to identify individuals at high risk of osteoporotic fractures in current surveillance systems. The objective of this study was to derive and validate predictive models to accurately identify individuals at high risk of osteoporotic fracture using information available in healthcare administrative data. More than 270,000 men and women aged ≥66 years were randomly selected from the Quebec Integrated Chronic Disease Surveillance System. Selected individuals were followed between fiscal years 2006-2007 and 2015-2016. Models were constructed for prediction of hip/femur and major osteoporotic fractures for follow-up periods of 5 and 10 years. A total of 62 potential predictors measurable in healthcare administrative databases were identified. Predictor selection was performed using a manual backward algorithm. The predictive performance of the final models was assessed using measures of discrimination, calibration, and overall performance. Between 20 and 25 predictors were retained in the final prediction models (eg, age, sex, social deprivation index, most of the major and minor risk factors for osteoporosis, diabetes, Parkinson's disease, cognitive impairment, anemia, anxio-depressive disorders). Discrimination of the final models was higher for the prediction of hip/femur fracture than major osteoporotic fracture and higher for prediction for a 5-year than a 10-year period (hip/femur fracture for 5 years: c-index = 0.77; major osteoporotic fracture for 5 years: c-index = 0.71; hip/femur fracture for 10 years: c-index = 0.73; major osteoporotic fracture for 10 years: c-index = 0.68). The predicted probabilities globally agreed with the observed probabilities. In conclusion, the derived models had adequate predictive performance in internal validation. As a final step, these models should be validated in an external cohort and used to develop indicators for surveillance of osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2329-2342Informations de copyright
© 2021 American Society for Bone and Mineral Research (ASBMR).
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