Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers
Background Osteoporosis, a prevalent orthopedic issue, significantly influences patients’ quality of life and results in considerable financial burden. The objective of this study was to develop and validate a clinical prediction model for osteoporosis risk, utilizing computer algorithms and demogra...
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PeerJ Inc.
2023-09-01
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| author | Dan Han Zhongcheng Fan Yi-sheng Chen Zichao Xue Zhenwei Yang Danping Liu Rong Zhou Hong Yuan |
| author_facet | Dan Han Zhongcheng Fan Yi-sheng Chen Zichao Xue Zhenwei Yang Danping Liu Rong Zhou Hong Yuan |
| author_sort | Dan Han |
| collection | DOAJ |
| description | Background Osteoporosis, a prevalent orthopedic issue, significantly influences patients’ quality of life and results in considerable financial burden. The objective of this study was to develop and validate a clinical prediction model for osteoporosis risk, utilizing computer algorithms and demographic data. Method In this research, a total of 4,552 residents from Shanghai were retrospectively included. LASSO regression analysis was executed on the sample’s basic characteristics, and logistic regression was employed for analyzing clinical characteristics and building a predictive model. The model’s diagnostic capacity for predicting osteoporosis risk was assessed using R software and computer algorithms. Results The predictive nomogram model for bone loss risk, derived from the LASSO analysis, comprised factors including BMI, TC, TG, HDL, Gender, Age, Education, Income, Sleep, Alcohol Consumption, and Diabetes. The nomogram prediction model demonstrated impressive discriminative capability, with a C-index of 0.908 (training set), 0.908 (validation set), and 0.910 (entire cohort). The area under the ROC curve (AUC) of the model was 0.909 (training set), 0.903 (validation set), and applicable to the entire cohort. The decision curve analysis further corroborated that the model could efficiently predict the risk of bone loss in patients. Conclusion The nomogram, based on essential demographic and health factors (Body Mass Index, Total Cholesterol, Triglycerides, High-Density Lipoprotein, Gender, Age, Education, Income, Sleep, Alcohol Consumption, and Diabetes), offered accurate predictions for the risk of bone loss within the studied population. |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-09T07:54:32Z |
| publishDate | 2023-09-01 |
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| spelling | doaj.art-56578af8c5bf4a0c93f2371cc3d6015d2023-12-03T01:16:13ZengPeerJ Inc.PeerJ2167-83592023-09-0111e1601710.7717/peerj.16017Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellersDan Han0Zhongcheng Fan1Yi-sheng Chen2Zichao Xue3Zhenwei Yang4Danping Liu5Rong Zhou6Hong Yuan7Department of Emergency Medicine and Intensive Care, Songjiang Hospital Affiliated to Shanghai Jiaotong University School of Medicine (Preparatory Stage), Shanghai, Shanghai, ChinaDepartment of Orthopaedics, Hainan Province Clinical Medical Center, Haikou Orthopedic and Diabetes Hospital of Shanghai Sixth People’s Hospital, Haikou, ChinaDepartment of Sports medicine, Huashan Hospital, Fudan University, Shanghai, ChinaDepartment of Orthopaedics, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, ChinaDepartment of Orthopaedics, First Affiliated Hospital of Jinzhou Medical University, Jinzhou, ChinaDepartment of Orthopaedics, First Affiliated Hospital of Jinzhou Medical University, Jinzhou, ChinaDepartment Two of Medical Administration, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment Two of Medical Administration, Zhongshan Hospital, Fudan University, Shanghai, ChinaBackground Osteoporosis, a prevalent orthopedic issue, significantly influences patients’ quality of life and results in considerable financial burden. The objective of this study was to develop and validate a clinical prediction model for osteoporosis risk, utilizing computer algorithms and demographic data. Method In this research, a total of 4,552 residents from Shanghai were retrospectively included. LASSO regression analysis was executed on the sample’s basic characteristics, and logistic regression was employed for analyzing clinical characteristics and building a predictive model. The model’s diagnostic capacity for predicting osteoporosis risk was assessed using R software and computer algorithms. Results The predictive nomogram model for bone loss risk, derived from the LASSO analysis, comprised factors including BMI, TC, TG, HDL, Gender, Age, Education, Income, Sleep, Alcohol Consumption, and Diabetes. The nomogram prediction model demonstrated impressive discriminative capability, with a C-index of 0.908 (training set), 0.908 (validation set), and 0.910 (entire cohort). The area under the ROC curve (AUC) of the model was 0.909 (training set), 0.903 (validation set), and applicable to the entire cohort. The decision curve analysis further corroborated that the model could efficiently predict the risk of bone loss in patients. Conclusion The nomogram, based on essential demographic and health factors (Body Mass Index, Total Cholesterol, Triglycerides, High-Density Lipoprotein, Gender, Age, Education, Income, Sleep, Alcohol Consumption, and Diabetes), offered accurate predictions for the risk of bone loss within the studied population.https://peerj.com/articles/16017.pdfOsteoporosisBone lossClinical prediction modelRetrospective study |
| spellingShingle | Dan Han Zhongcheng Fan Yi-sheng Chen Zichao Xue Zhenwei Yang Danping Liu Rong Zhou Hong Yuan Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers PeerJ Osteoporosis Bone loss Clinical prediction model Retrospective study |
| title | Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers |
| title_full | Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers |
| title_fullStr | Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers |
| title_full_unstemmed | Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers |
| title_short | Retrospective study: risk assessment model for osteoporosis—a detailed exploration involving 4,552 Shanghai dwellers |
| title_sort | retrospective study risk assessment model for osteoporosis a detailed exploration involving 4 552 shanghai dwellers |
| topic | Osteoporosis Bone loss Clinical prediction model Retrospective study |
| url | https://peerj.com/articles/16017.pdf |
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