Abstract
Background: A more accurate assessment of extrahepatic metastases (EHMs) with colorectal cancer liver metastases (CRLMs) improve patient prognosis without unnecessary surgery and economic burden. At present, PET-CT can only be used as a second-line modality. We aimed to construct a predictive model for EHMs, and provide guidance for the selective application of (18)F-FDG PET/CT. Methods: The clinical data of patients with CRLMs between December 2018 and February 2023 were retrospectively retrieved from the medical records of three large-capacity hospitals. Moreover, we explored the need for (18)F-FDG PET/CT to be used selectively for detecting EHMs with CRLMs. Results: A total of 471 patients from two hospitals were included in the training set, 174 of whom had CRLMs and EHMs. Notably, the percentages of patients with positive serum CEA, CA19-9 and CA-125 levels were significantly greater in patients with CRLMs and EHMs than in those with liver-limited metastases. Univariate and multivariate logistic regression analyses revealed that the serum levels of CEA and CA-125 and multiple liver metastases were independent risk factors for EHMs. Additionally, we recruited 190 patients with CRLMs from one of the hospitals as the validation set. The nomogram model achieved stable and accurate prediction results in the training and validation sets (AUC = 0.768 and 0.733), and was significantly superior to CEA and CA19-9. Moreover, the sensitivity and specificity of (18)F-FDG PET/CT for the diagnosis of EHMs were 100% and 88%, respectively. Conclusions: We constructed and validated a nomogram on predicting the risk of EHMs in patients with CRLMs, which can guide clinicians to selective application of (18)F-FDG PET/CT.