Association between lateral pterygoid muscle index as a predictor for sarcopenia and overall survival in non-small cell lung cancer patients with brain metastasis.

BACKGROUND & AIMS: Sarcopenia has emerged as a significant prognostic factor for lung cancer. However, it remains unclear how the lateral pterygoid muscle index (LPMI) calculated based on the lateral pterygoid muscle area correlates with sarcopenia in lung cancer patients with brain metastasis (BM). This study aims to determine whether LPMI can serve as a predictor for sarcopenia in lung cancer patients with BM and assess its utility in predicting survival.

METHODS

This study retrospectively analyzed the initial brain magnetic resonance imaging (MRI) parameters of non-small cell lung cancer (NSCLC) patients with BM at our hospital between March 2017 and June 2024. We examined the correlation between LPMI and the lumbar skeletal muscle index (LSMI) at the third lumbar vertebra (L3). After adjusting for key prognostic factors, we performed a multivariate Cox regression analysis of overall survival (OS) to evaluate the prognostic significance of LPMI.

RESULTS

A total of 223 patients were included. The LPMI was positively correlated with LSMI in NSCLC patients with BM (r = 0.618, p < 0.001). Multivariate linear regression analysis indicated LPMI was associated with the risk of sarcopenia (β = 0.427,p < 0.001). The optimal cut-off value of LPMI for identifying NSCLC with sarcopenia was 120.06. Multivariate logistic regression showed an increased blood urea nitrogen/creatinine ratio (BUN/Cr) was associated with lower LPMI values (OR = 1.014, p = 0.013). Patients with an LPMI thicker than the median had a longer OS compared to those with an LPMI thinner than the median (9 months vs. 14.5 months, p = 0.011). Multivariate Cox analysis showed a thicker LPMI measurement was a predictor of longer OS (HR = 0.993,p = 0.036).

CONCLUSIONS

Our results indicate that LPMI has the potential to serve as an alternative diagnostic indicator for sarcopenia in NSCLC patients with BM and as an independent predictor of OS.