ArticleTranslational lung cancer research2024
Development of a predictive model to predict postoperative bone metastasis in pathological I-II non-small cell lung cancer.
Article in Translational lung cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Risk factors and clinical risk stratification of distant metastasis in early-stage lung cancer in never smokers.World journal of surgical oncology · 2025Article
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5 authors.
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Abstract
Background: Bone is a common metastatic site in postoperative metastasis, but related risk factors for early-stage non-small cell lung cancer (NSCLC) remain insufficiently investigated. Thus, the study aimed to identify risk factors for postoperative bone metastasis in early-stage NSCLC and construct a nomogram to identify high-risk individuals. Methods: Between January 2015 and January 2021, we included patients with resected stage I-II NSCLC at the Department of Thoracic Surgery, West China Hospital. Univariable and multivariable Cox regression analyses were used to identify related risk factors. Additionally, we developed a visual nomogram to forecast the likelihood of bone metastasis. Evaluation of the model involved metrics such as the area under the curve (AUC), C-index, and calibration curves. To ensure reliability, internal validation was performed through bootstrap resampling. Results: Our analyses included 2,106 eligible patients, with 54 (2.56%) developing bone metastasis. Multivariable Cox analyses showed that tumor nodules with solid component, higher pT stage, higher pN stage, and histologic subtypes especially solid/micropapillary predominant types were considered as independent risk factors of bone metastasis. In the training set, the developed model demonstrated AUCs of 0.807, 0.769, and 0.761 for 1-, 3-, and 5-year follow-ups, respectively. The C-index, derived from 1,000 bootstrap resampling, showed values of 0.820, 0.793, and 0.777 for 1-, 3-, and 5-year follow-ups. The calibration curve showed that the model was well calibrated. Conclusions: The predictive model is proven to be valuable in estimating the probability of bone metastasis in early-stage NSCLC following surgery. Leveraging four easy-to-acquire clinical parameters, this model effectively identifies high-risk patients and enables individualized surveillance strategies for better patient care.
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