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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.
European Journal of Surgical Oncology 2024 April 18
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.
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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