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The ratio of skeletal muscle mass to body mass index combined with inflammatory immune markers to stratify survival of pancreatic cancer after pancreatoduodenectomy

列线图 接收机工作特性 医学 胰腺癌 体质指数 癌症 内科学 曲线下面积 队列 胃肠病学 肿瘤科
作者
Jikuan Jin,Guangbing Xiong,Feng Peng,Feng Zhu,Min Wang,Renyi Qin
出处
期刊:Ejso [Elsevier BV]
卷期号:50 (7): 108355-108355 被引量:1
标识
DOI:10.1016/j.ejso.2024.108355
摘要

Background We sought to combine skeletal muscle index and inflammatory immune markers to stratify long-term survival in patients with pancreatic cancer after pancreatoduodenectomy (PD). Methods A total of 581 patients with pancreatic cancer underwent PD were included, and divided into the training and validation cohort. Image analysis of computed tomography scans was used to calculate the ratio of skeletal muscle (SM) area to body mass index (BMI). Naples prognostic score (NPS) was calculated from blood-test inflammatory immune markers. Propensity score matching (PSM) analysis was performed to minimize biases of clinicopathological characteristics. To estimate the overall survival (OS), a nomogram was developed using the training cohort. The predictive accuracy of nomogram was estimated by concordance index (C-index), calibration curve, and receiver operating characteristics (ROC) curve. Results After PSM analysis, SM/BMI ratio, NPS, lymph node metastasis, TNM stage, surgical margin, tumor grade and adjuvant therapy were independent predictors of OS, which were all assembled into nomogram. The SM/BMI ratio was the best single-predictor for 3- and 5-year OS, with an AUC of 0.805 (95% CI: 0.755-0.855) and 0.812 (95% CI: 0.736-0.888), respectively. Harrell's c-index of the nomogram in the training cohort was 0.786 (95% CI: 0.770–0.802), and the area under ROC curve of 1-year, 3- and 5-year OS prediction were 0.869 (95%CI: 0.837 - 0.901), 0.846 (95%CI: 0.810 - 0.882) and 0.849 (95%CI: 0.801 - 0.896). Conclusions The nomogram based on SM/BMI ratio and NPS had excellent predictive performance, which should be incorporated to conventional risk scores to stratify survival of patients with PDAC after PD.
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