Influence of sarcopenia on postoperative complications and long-term survival in pancreatic cancer patients undergone pancreaticoduodenectomy

sarcopenia 03 medical and health sciences 0302 clinical medicine complications Nutrition. Foods and food supply pancreatic cancer TX341-641 pancreaticoduodenectomy skeletal muscle index Nutrition
DOI: 10.3389/fnut.2024.1434630 Publication Date: 2024-07-04T04:55:14Z
ABSTRACT
Background Sarcopenia has the potential to impact postoperative results and extended prognosis of various types tumors. Nevertheless, specific sarcopenia on long-term survival pancreatic cancer (PC) following pancreaticoduodenectomy (PD) remains inadequately elucidated. This study investigates significance according Asian standards complications in PC patients who have undergone PD. Methods retrospective systematically analyzed with underwent PD from January 2015 December 2022. was diagnosed by skeletal muscle index (SMI) obtained area normalized for height squared third lumbar vertebra computed tomography (CT) images. Univariate multivariate logistic regression analysis were performed analyze correlation between complications, while Cox utilized explore influence overall (OS) recurrence-free (RFS) after Results We enrolled 162 (92 males 70 females, mean age: 63.78 ± 10.27 years), including 83 79 non-sarcopenia, respectively. Compared non-sarcopenia patients, exhibited higher rates recurrence rate (75% versus 59%, p = 0.039). showed that did not affect incidence three criteria. Multivariate indicated an independent risk factor OS (hazard ratio [HR]: 2.49, 95% confidence interval [CI]: 1.73–3.60, < 0.001) RFS(hazard 1.70, 95%confidence 1.12–2.50, 0.012) Japanese Society Hepatology Meanwhile, population standard, is affecting 2.59, 1.80–3.70, RFS 2.00, 1.36–3.00, While recognized as a 1.81, 1.08–3.10, 0.025) based Fujiwara criteria, it found be associated 1.60, 0.90–3.00, 0.10). The model clinical characteristics high predictive ability RFS. Conclusion Various diagnostic criteria do link significant survival, its combination can aid clinicians predicting outcomes.
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