ArticleInternational journal of general medicine2022
Development of a Nomogram for Predicting Very Low Bone Mineral Density (T-Scores <-3) in the Chinese Population.
Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?BMC medical informatics and decision making · 2025Article
- Age trend and risk factors of height loss in Chinese over 40 years old.Frontiers in endocrinology · 2025Article
- Spine, hip, and femoral neck bone mineral density in relation to vegetarian type and status among Taiwanese adults.Archives of osteoporosis · 2023Article
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9 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
purposeFragility fractures, the most serious complication of osteoporosis, affect life quality and increase medical expenses and economic burden. Strategies to identify populations with very low bone mineral density (T-scores <-3), indicating very high fracture risk according to the American Association of Clinical Endocrinologists/American College of Endocrinology (AACE/ACE), are necessary to achieve acceptable fracture risk levels. In this study, the characteristics of persons with T-scores <-3 were analyzed in the Chinese population to identify risk factors and develop a nomogram for very low bone mineral density (T-scores <-3) identification. MATERIALS AND
methodsWe conducted a cross-sectional study using the datasets of the Health Improvement Program of Bone (HOPE), with 602 men aged ≥50 years and 482 postmenopausal women. Bone mineral density (BMD) was measured using dual energy X-ray absorptiometry (DXA). Data on clinical risk factors, including age, sex, weight, height, previous fracture, parental hip fracture history, smoking, alcohol intake >3 units/day, glucocorticoid use, rheumatoid arthritis, and secondary osteoporosis were collected. A multivariate logistic regression to evaluate the relationship between the clinical risk factors and very low BMD (T-scores <-3) was conducted. Parameter estimates of the final model were then used to construct a nomogram.
resultsSixty-three of 1084 participants (5.8%) had BMD T-score <-3. In multivariable regression analysis, age (odds ratio [OR] = 1.068, 95% confidence interval [CI]: 1.037-1.099) and weight (OR = 0.863, 95% CI: 0.830-0.897) were significant factors that were associated with very low BMD (T-scores <-3). These variables were the factors considered in developing the nomogram. The area under the receiver operating characteristic (ROC) curve for the model was 0.861. The cut-off value of the ROC curve was 0.080.
conclusionThe nomogram can effectively assist clinicians to identify persons with very low BMD (T-scores <-3) and very high fracture risk in the Chinese population.
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