Abstract: BACKGROUND: A nomogram prediction model can be plotted based on independent influencing factors derived from multiple regression analyses. The probability of bone mass loss in patients can be intuitively calculated based on the total score obtained from various influencing factors.
OBJECTIVE: To establish a nomogram prediction model based on the independent factors of bone mass loss in middle-aged men. 
METHODS: The clinical data of 279 middle-aged men who underwent physical examinations in the Physical Examination Center of the First Affiliated Hospital of Jinzhou Medical University from June 15 to July 15, 2021 and from October 15 to November 15, 2021 were collected and divided into training set (214 cases) and verification set (65 cases) according to different time periods of data collection. The self-made “Middle-aged Male Bone Mass Survey Questionnaire” was used in all subjects and the DiscoveryW dual-energy X-ray bone densitometer was used to measure the bone mineral density of the left hip. Based on the single-factor analysis and multivariate Logistics regression analysis of training set, the independent influencing factors of bone mass loss were screened, and the nomogram model for predicting bone mass loss was made. C-index verification and calibration curve were used to preliminarily evaluate the differentiation and calibration degree of the model. The internal validation of the model was performed by k-fold cross validation, and the external validation of the model was performed by the validation set. The performance of the nomogram model was further evaluated by C index, Hosmer-Lemeshow test, and calibration curve.
RESULTS AND CONCLUSION: Results from the single-factor analysis showed that there were statistical differences in smoking, dairy products, exercise, and breakfast in the training set. Multivariate Logistics regression analysis results showed that smoking was an independent risk factor for bone mass loss, while dairy products and exercise were protective factors. According to the independent factors and existing theories, the nomogram model for predicting bone mass loss was established with a C-index of 0.671 (95% confidence interval: 0.600-0.750), indicating that the calibration curve fitted well. K-fold cross verification showed that the mean value of C-index was 0.708. The C-index of external validation was 0.689 (95% confidence interval: 0.600-0.742), P=0.09 > 0.05 in the Hosmer-Lemeshow test, and the calibration curve was fitted well. To conclude, this nomogram model for predicting bone mass loss has well inspection efficiency and can help screen middle-aged male patients with boss mass loss.

Key words: bone mass loss, nomogram, prediction model, middle-aged man