Lung cancer is currently the leading cause of cancer-related deaths worldwide, with 30%-36% of patients developing spinal metastases. However, the predictive accuracy of commonly used spinal metastasis scoring systems, such as the revised Tokuhashi score and Tomita score, has decreased. This study aims to optimize the revised Tokuhashi and Tomita scores by incorporating new indicators to assist clinicians in making informed treatment decisions. A retrospective analysis was conducted on 147 patients with lung cancer spinal metastases. Prognostic factors were identified using Cox regression analysis. The predictive performance of different models at the 3-month, 6-month, and 1-year time points was evaluated using receiver operating characteristic (ROC) curves and the DeLong test. By incorporating the Prognostic Nutritional Index (PNI) and the presence of non-small cell lung cancer, the optimized P-Tokuhashi and P-Tomita scores were developed. The predictive abilities of P-Tokuhashi at 3 months (AUC = 0.77), 6 months (AUC = 0.71), and 1 year (AUC = 0.74), as well as P-Tomita at 3 months (AUC = 0.74), 6 months (AUC = 0.62), and 1 year (AUC = 0.70), were all superior to the pre-optimization scores. The DeLong test confirmed that the predictive accuracy of the modified scores at 6 months and 1 year was significantly better than that of the original scores (p < 0.05). The new prognostic scoring system for spinal metastasis, which incorporates the PNI and the status of non-small cell lung cancer (NSCLC), provides better prediction of survival in patients with lung cancer spinal metastases, enabling clinicians to select more personalized treatment strategies.
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Tiantian Wei
Guoqing Zhong
Jia‐Yi Wang
BMC Cancer
Guangzhou Medical University
Guangdong Academy of Medical Sciences
First Affiliated Hospital of Guangzhou Medical University
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Wei et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69d8930e6c1944d70ce042ff — DOI: https://doi.org/10.1186/s12885-026-15952-0
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