Arsalan A Khan, Wara Naeem, Minha Ansari, Oluwamuyiwa W Adebayo, Savan K Shah, Gillian C Alex, Nicole M Geissen, Michael J Liptay, Christopher W Seder
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引用次数: 0
Abstract
Background: Sarcopenia has emerged as a prognostic biomarker in lung cancer, yet the optimal radiological metric for its assessment remains debated. Skeletal Muscle Gauge (SMG), a composite of muscle volume and density, may offer superior prognostic utility compared with individual measures.
Patients and methods: We retrospectively analyzed 343 patients who underwent lung resection for clinical stage I-IIB NSCLC between 2010 and 2021 and had a preoperative positron emission tomography (PET) scan. Volumetric body composition metrics, skeletal muscle index, skeletal muscle area, skeletal muscle density (SMD), and SMG were derived from automated segmentation using PET scans followed by normalization. Associations with overall survival was assessed using Cox proportional hazards analyses. Predictive accuracy was evaluated using the concordance index. Optimal SMG cutoff was determined by maximally selected rank statistics.
Results: SMG and SMD were independently associated with overall survival after adjustment for clinical and tumor characteristics. SMG and SMD demonstrated the highest prognostic accuracy (C-index 0.743 and 0.710, respectively). No linear relationship was observed between skeletal muscle metrics and BMI, underscoring the limitation of BMI in detecting sarcopenia. SMG values < 87,816 AU were associated with significantly worse survival in both sexes (HR 2.34, 95% CI 1.48-3.69; p < 0.001).
Conclusions: SMG outperforms individual skeletal muscle indices in predicting overall survival following lung resection for early-stage NSCLC. These findings support the clinical utility of this composite measure for assessing cancer associated sarcopenia and advocate for the integration of automated body composition analysis into preoperative evaluation.
背景:骨骼肌减少症已成为肺癌的预后生物标志物,但其评估的最佳放射学指标仍存在争议。骨骼肌测量(SMG)是一种肌肉体积和密度的组合,与单独测量相比,可能提供更好的预后效用。患者和方法:我们回顾性分析了2010年至2021年间343例临床I-IIB期NSCLC肺切除术患者,并进行了术前正电子发射断层扫描(PET)扫描。体积体组成指标、骨骼肌指数、骨骼肌面积、骨骼肌密度(SMD)和SMG是通过PET扫描和规范化的自动分割得到的。使用Cox比例风险分析评估与总生存率的关系。使用一致性指数评估预测准确性。最优SMG截止值由最大选择的秩统计量确定。结果:调整临床和肿瘤特征后,SMG和SMD与总生存率独立相关。SMG和SMD的预后准确性最高(c指数分别为0.743和0.710)。骨骼肌指标与BMI之间没有线性关系,强调了BMI在检测肌肉减少症方面的局限性。SMG值< 87,816 AU的男性和女性的生存率均显著降低(HR 2.34, 95% CI 1.48-3.69; p < 0.001)。结论:在预测早期NSCLC肺切除术后的总生存率方面,SMG优于个体骨骼肌指数。这些发现支持了这种综合方法在评估癌症相关肌肉减少症方面的临床应用,并提倡将自动身体成分分析纳入术前评估。
期刊介绍:
The Annals of Surgical Oncology is the official journal of The Society of Surgical Oncology and is published for the Society by Springer. The Annals publishes original and educational manuscripts about oncology for surgeons from all specialities in academic and community settings.