Identification of risk factors for sarcopenia in patients with pancreatic cancer and construction of a nomogram for prediction

LI Yue; MA Yue; ZHANG Xiaoqi; LI Yanyan; HAN Binru; LIN Haishan

doi:10.3969/j.issn.1009-0460.2025.06.008

Abstract：Objective To explore the independent risk factors of sarcopenia in patients with pancreatic cancer and establish a nomogram.Methods A retrospective analysis was conducted on the data of 144 patients with pancreatic cancer in the Fifth Medical Center of the PLA General Hospital and Friendship Hospital Affiliated to Capital Medical University from October 2018 to December 2024.Sarcopenia was diagnosed by measuring the skeletal muscle area at the L3 level CT.The differences in clinical characteristics between the sarcopenia group(n=66)and the non-sarcopenia group(n=78)were compared.The risk factors were analyzed by stepwise backward Logistic regression and a nomogram model was constructed.Internal verification was conducted through the Bootstrap method.Results The incidence of sarcopenia was 45.83%(66/144).The levels of white blood cells,neutrophils,monocytes,red blood cells and hemoglobin in the sarcopenia group were significantly decreased(all P<0.05).Logistic multivariate analysis showed white blood cells(OR=1.32,95%CI:1.08-1.62),lymphocytes(OR=0.56,95%CI:0.35-0.89),and red blood cells(OR=0.41,95%CI:0.22-0.76),ApoA1(OR=0.18,95%CI:0.05-0.63)and PLR(OR=1.01,95%CI:1.00-1.02)were independent risk factors(all P<0.05);Based on the above influencing factors,a nomogram prediction model for sarcopenia in pancreatic cancer was constructed.After internal verification by Bootstrap,the calibration curve of this model is close to the standard curve and has good consistency.Model validation showed that the AUC of the training set was 0.733(95%CI:0.618-0.848),the AUC of the validation set was 0.833(95%CI:0.667-1.000),and the calibration curve showed good consistency.Conclusion White blood cells,lymphocytes,red blood cells,ApoA1,and PLR are independent risk factors for sarcopenia in patients with pancreatic cancer.The nomogram prediction model constructed based on the above five risk factors is helpful for early monitoring and intervention of sarcopenia in pancreatic cancer.