Abstract
PURPOSE: The presence of a sarcopenia adversely affects the prognosis of patients with pancreatic cancer. There is an emerging role for using computed tomography (CT) to calculate skeletal muscle index (SMI) and the presence of sarcopenia. The aim of this study was to assess if detecting 'computed tomographic sarcopenia' is feasible and can contribute to the management of patients with locally advanced pancreatic cancer (LAPC). METHODS: Patients diagnosed with LAPC referred for endoscopic ultrasound-guided biopsy (EUS-B) by our regional cancer network were identified. Age, body mass index (BMI), and Eastern Cooperative Oncology Group performance status (ECOG-PS) were noted. CT images were analysed for SMI and the presence of sarcopenia. Decision outcomes on receiving chemotherapy or not were collected from the regional oncology database. RESULTS: In total, 51/204 (25%) patients with LAPC who underwent EUS-B were not given chemotherapy and received best supportive care (BSC) only. The prevalence of sarcopenia (p = 0.0003), age ≥ 75 years old (p = 0.03), and ECOG-PS 2-3 (p = 0.01) were significantly higher in the patients receiving BSC only. Logistic regression analysis demonstrated that SMI was the only independent associated factor identifying patients with LAPC who were treated with BSC only and not chemotherapy after adjusting for age and ECOG-PS. CONCLUSION: Our study has shown that computed tomographic skeletal muscle analysis at the time of a diagnostic CT for patients with pancreatic cancer is feasible and can detect sarcopenia and malnourished patients who are much less likely to take up chemotherapy. These patients could be triaged to oncology assessment prior to EUS-B to avoid unnecessary investigations.