1. An FDG PET/CT metabolic parameter-based nomogram for predicting the early recurrence of hepatocellular carcinoma after liver transplantation
- Author
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Wenjie Miao, Wei Rao, Yujun Zhao, Guangjie Yang, Fengyu Wu, Ting Yu, Mingming Yu, Pei Nie, Lei Yan, Yangyang Wang, and Zhenguang Wang
- Subjects
medicine.medical_specialty ,Carcinoma, Hepatocellular ,Early Recurrence ,medicine.medical_treatment ,Liver transplantation ,Milan criteria ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Fluorodeoxyglucose F18 ,Positron Emission Tomography Computed Tomography ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Retrospective Studies ,Receiver operating characteristic ,business.industry ,Liver Neoplasms ,General Medicine ,Nomogram ,medicine.disease ,BCLC Stage ,Liver Transplantation ,Nomograms ,030220 oncology & carcinogenesis ,Hepatocellular carcinoma ,Fdg pet ct ,Radiology ,Neoplasm Recurrence, Local ,business - Abstract
To construct an FDG PET/CT metabolic parameter-based model to predict early recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT). A total of 62 patients with HCC after LT were enrolled with a follow-up period of 1 year. Basic clinical, pathology, and laboratory data, CT features (CPLC), and PET metabolic parameters (CPLCP) were collected for model construction. A CPLC nomogram without metabolic parameters and a CPLCP nomogram with metabolic parameters were established. The net reclassification index (NRI) and integrated discrimination improvement (IDI) of the two models were calculated. The constructed model was compared with Milan criteria and University of California San Francisco (UCSF) criteria. The time-dependent area under the receiver operating characteristic curve (time-AUC) was used to compare the efficiency of the models, and the bootstrap method was used to for verification. Harrell’s concordance index (C-index) was used to evaluate the performance of these models. Decision curve analysis (DCA) was used to evaluate the clinical practicability of each model. Thirty out of 62 patients experienced a recurrence during the 1-year follow-up. BCLC stage (P = 0.009), MVI (P = 0.032), AFP (P = 0.004), CTdmax (P = 0.033), and MTV (P = 0.039) were the independent predictors. The CPLC nomogram and the CPLCP nomogram were established. Compared with the CPLC nomogram, the NRI of the CPLCP nomogram increased by 38.98% (95% CI = −18.77–60.43%) and the IDI increased by 4.40% (95% CI = −1.00–16.62%). The AUC value of the CPLCP nomogram was higher than those of Milan criteria and UCSF criteria in the time-AUC curve. Moreover, the CPLCP nomogram had a higher C-index (0.774) than other models. Finally, the DCA curve showed that clinical practicability of the CPLCP nomogram outperformed the Milan criteria and UCSF criteria. The CPLCP nomogram combining basic clinical data, pathology data, laboratory data, CT features, and PET metabolic parameters showed good efficacy and high clinical practicability in predicting the early recurrence of HCC after LT.
- Published
- 2021
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