基于 Group Lasso 的 Logistic 回归模型构建绝经后骨质疏松性骨折初发风险评估工具.

To establish an early risk prediction tool for osteoporotic fractures that combines demographic risk factors and TCM symptoms in females aged between 40 and 65 years in Beijing and Shanghai． Methods In this study，risk factors and TCM symptoms of 1129 women aged 40 to 65 years at high risk of osteoporosis were collected in Dongcheng District of Beijing and Xuhui District of Shanghai from March to August 2009 using a registered study method ． Observational registration continued for three consecutive years． The SMOTE oversampling algorithm was used to balance the data． Group Lasso's logistic regression model was used to screen for risk factors associated with osteoporosis and TCM symptoms，and a risk assessment tool for osteoporotic fractures was established． Results Based on the grplasso package of R 3. 3. 3 software，we studied risk factors of postmenopausal osteoporotic fractures and TCM syndrome factors at different λ levels． Finally，combining mathematics and medical science，we believe that the variables selected are the best when λ = 0. 0235． The specific group variables include: bone mineral density，age， food type，height，menstruation，number of births，and liver and kidney yin deficiency． Further，based on the logistic regression model，osteoporotic fracture prediction tools were derived: P = - 1. 88 + 0. 437* BMD + 0. 289* age + 0. 023* rice noodles - 0. 007* dairy products - 0. 096* soy products - 0. 128* meat - 0. 084* fish - 0. 007* fresh vegetables - 0. 018* eggs + 0. 047 * seaweeds + 0. 048* height - 0. 035 * whether became shorter - 0. 081 * menarche age + 0. 171 * whether menopause + 0. 121* menopause years + 0. 039* number of pregnancy + 0. 192* number of birth - 0. 056* whether the uterus and ovary were resected + 0. 05* fever of hands and feet - 0. 094* night sweat + 0. 008* soft legs + 0. 15* dizziness - 0. 048* blurred vision - 0. 045* dry eyes - 0. 089 * bad heat + 0. 08 * hair loss + 0. 034 * loose teeth - 0. 101 * bitter mouth + 0. 004 * irritable + 0. 054* afternoon hot flash - 0. 056* insomnia + 0. 019* dreaminess and easily frightened - 0. 02* chest thrush + 0. 137* lower limb spasm． The receiver operating characteristic curve was plotted against the predictive probability of the predictive model． The result showed that the area under the curve was 0. 8775 ( 95% CI = 0. 8412 - 0. 9138) ． Conclusion A preliminary risk prediction tool for osteoporotic fractures in 40 to 65-year-old females based on the demographic characteristics of Beijing and Shanghai was established． [ABSTRACT FROM AUTHOR]