| Objective : Bone metastasis is a common distant metastasis of lung cancer,which seriously affects the quality of life of patients.Predicting the risk of bone metastasis in patients with lung cancer is of great significance for clinicians to detect and prevent early,guide treatment and prolong the survival of patients with lung cancer.This study aimed to investigate the risk factors for bone metastasis in patients with lung cancer and to establish a visual risk prediction model for bone metastasis in patients with lung cancer.Methods:This study retrospectively collected the clinical data and laboratory indicators of patients with lung cancer who were first hospitalized in the First Affiliated Hospital of Anhui Medical University and confirmed by pathology from January 1,2020 to September 1,2021.And according to whether the patients with lung cancer had bone metastasis,they were divided into bone metastasis group and without bone metastasis group.Patients with single factor analysis of clinical characteristics（gender,age,pathological type,body mass index,past medical history）and blood index（including absolute eosinophil count,percentage of eosinophils,absolute monocytes count,monocyte percentage,platelet count,D-dimer,lactate dehydrogenase,alkaline phosphatase,HSP90α）,and selected affecting factors of bone metastasis from lung cancer.Multivariate Logistic regression analysis was used to construct a Nomogram,and C index,area under ROC curve,correction diagram and decision curve analysis（DCA）were used to evaluate the accuracy,differential ability and clinical utility of the model.Results:A total of 462 eligible patients were screened in this study.There were 220 patients with bone metastasis of lung cancer,127 males and 93 females.Without bone metastasis occurred in 242 patients with lung cancer,including 163 males and 79 females.Univariate analysis showed age（P<0.001）,gender（P=0.03）,pathological type（P<0.001）,past history（P=0.003）,absolute monocytes count（P=0.02）,percentage of monocytes（P=0.01）,D-dimer level（P<0.001）,lactate dehydrogenase（LDH）（P<0.002）,alkaline phosphatase（ALP）（P<0.003）were correlated with bone metastasis of lung cancer.Multivariate Logistic regression analysis suggested pathological type（OR=11.62,P=0.00）,medical history（OR=9.46,P=0.01）,percentage of monocytes（OR=7.02,P=0.01）,LDH level（OR=4.81,P=0.03）and ALP level（OR=37.72,P<0.001）were independent risk factors for bone metastasis of lung cancer.The Nomogram was constructed which based on these risk factors.The area under ROC curve（AUC）of the prediction model was 0.777,and the C index was 0.777.The calibration curve showed that the predicted curve was basically consistent with the actual observed curve.Based on the Nomogram prediction model,the selected variables were subjected to decision curve analysis for the risk of bone metastasis from lung cancer.The results showed that when the threshold probability of the patient was 0-1.0,the net benefit of using the Nomogram to predict the risk of bone metastasis in lung cancer patients was higher.Conclusions:The risk predicted model constructed in this study has good effect,which can be used in clinical work to screen the high-risk population with bone metastasis for lung cancer patients and provide early intervention measures. |
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