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Background <p>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.</p> Patients and Methods <p>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.</p> Results <p>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 &lt; 87,816 AU were associated with significantly worse survival in both sexes (HR 2.34, 95% CI 1.48–3.69; <i>p</i> &lt; 0.001).</p> Conclusions <p>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.</p>

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Skeletal Muscle Gauge as a Prognosticator of Survival in Resected Early-Stage Non-small Cell Lung Cancer

  • 期刊论文

  • 发表日期：

    2025年10月15日

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  • 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

摘要

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.