Establishment and validation of risk prediction model for bone metastasis of NSCLC

Chunxiao Hu; Yafeng Liu; Yixin Su; Jianqiang Guo; Wenting Zhang; Xueqin Wang; Jun Xie; Wanfa Hu; Jing Wu; Yingru Xing; Dong Hu; Xuansheng Ding

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Establishment and validation of risk prediction model for bone metastasis of NSCLC

Author: Chunxiao Hu ^{1
,

2
,

3} ; Yafeng Liu ^{1
,

2
,

3} ; Yixin Su ^{1
,

2} ; Jianqiang Guo ^{1
,

2} ; Wenting Zhang ^{1
,

2} ; Xueqin Wang ^{1
,

2
,

3} ; Jun Xie ³ ; Wanfa Hu ³ ; Jing Wu ^{1
,

2
,

4} ; Yingru Xing ^{1
,

2
,

3
,

4} ; Dong Hu ^{1
,

2
,

4} ; Xuansheng Ding ^{1
,

2}
Author Information

1. School of Medicine , Anhui University of Science &
2. Technology (Anhui Province Engineering Laboratory of Occupational Health and Safety) ,Huainan 232000
3. Cancer Hospital Afiliated to Anhui University of Science and Technology (Huainan Oriental Hospital Group Cancer Hospital) , Huainan 232000
4. Key Laboratory of Anhui Industrial Dust Deep Purification and Occupational Health Ministry of Education , Huainan 232000
Publication Type:Journal Article
Keywords: NSCLC; bone metastasis; risk factors; nomogram
From: Acta Universitatis Medicinalis Anhui 2022;57(5):832-836
CountryChina
Language:Chinese
Abstract: Objective:To construct nomogram to predict the risk of bone metastasis in patients with non-small cell lung cancer(NSCLC).
Methods:The clinical data of NSCLC patients diagnosed in the hospital were retrospectively analyzed, including the occurrence of bone metastasis, age, gender, pathological type, smoking status, PS score, TN stage, metastasis of other sites before bone metastasis, carcinoembryonic antigen(CEA) level, alpha fetoprotein(AFP) level, serum calcium(Ca2+), serum phosphorus(P), alkaline phosphatase(ALP) level, which were determined by univariate and multivariate logistic regression analysis. Receiver operating characteristic curve(ROC) and decision curve analysis were used, DCA was used to verify the accuracy and clinical benefit of the model, and nomogram was used to visualize the model.
Results:Area under the ROC curve(AUC) showed that in the modeling group(n=138) and the validation group(n=92), the AUC value predicted by combined indicators(age, gender, pathological type, CEA, ALP)(modeling group=0.792, validation group=0.629) was higher than that predicted by single indicator.
Conclusion:The prediction model constructed in this study has good effect and can provide reference for clinical screening of high-risk patients with bone metastasis of NSCLC.
Full text:2025022016260647841NSCLC骨转移风险预测模型的建立和验证_胡春晓.pdf