Abstract: Objective To investigate the influential factors of sarcopenia in cancer patients, establish a risk prediction model and verify it, and provide a screening tool for early identification of high-risk groups of sarcopenia in cancer patients. Methods Cancer patients in the department of oncology of a three A grade hospital in Baoding city were randomly divided into modeling group and validation group according to a ratio of 7∶3. For the modeling group, univariate analysis and multivariate Logistic regression analysis were used to screen out independent predictors of sarcopenia, and the prediction model was constructed. The predictive performance of the model was evaluated according to the area under the ROC curve(AUC). Results Age, calf circumference, smoking history, diabetes mellitus, tumor stage and PG-SGA score were the independent factors influencing the occurrence of sarcopenia in tumor patients. The prediction model equation logit(P)= 6.686 + 0.244x₁-0.806x₂+1.036x₃+1.186x₄+1.828x₅₊2.635x₆(x₁: age,x₂: calf circumference, x₃: smoking history, x₄: combined diabetes, x₅: tumor stage, x₆: PG-SGA score), P>27.53% could be considered as high risk group of sarcopenia. Conclusion The constructed prediction model has the advantages of high fitting degree, good differentiation ability, simple and non-invasive, which can effectively predict the occurrence of sarcopenia in tumor patients.

Key words: tumor, sarcopenia, influencing factors, prediction model