Nomograms for postsurgical extrahepatic recurrence prediction of hepatocellular carcinoma based on presurgical circulating tumor cell status and clinicopathological factors

Author:

Wei Hao‐Wen12ORCID,Qin Shui‐Ling12,Xu Jing‐Xuan12,Huang Yi‐Yue12,Chen Yuan‐Yuan3,Ma Liang124,Qi Lu‐Nan124ORCID

Affiliation:

1. Department of Hepatobiliary Surgery Guangxi Medical University Cancer Hospital Nanning China

2. Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education Nanning China

3. Department of Ultrasound First Affiliated Hospital of Guangxi Medical University Nanning China

4. Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center Nanning China

Abstract

AbstractBackground and AimsExtrahepatic recurrence (EHR) is one of the major reasons for the poor prognosis of hepatocellular carcinoma (HCC). The present study aimed to develop and assess the performance of predictive models by using a combination of presurgical circulating tumor cell (CTCs) data and clinicopathological features to screen patients at high risk of EHR to achieve precise decision‐making.Patients and MethodsA total of 227 patients with recurrent HCC and preoperative CTC data from January 2014 to August 2019 were enrolled. All patients were randomly assigned to one of two cohorts: development or validation. Two preoperative and postoperative nomogram models for EHR prediction were developed and multi‐dimensionally validated.ResultsPatients with EHR had generally lower recurrence‐free survival (p < 0.001), and overall survival (p < 0.001), and significantly higher CTC counts (epithelial CTCs, epithelial/mesenchymal hybrid CTCs, and mesenchymal CTCs count, all p < 0.05) than those without EHR. Univariate and multivariate analyses revealed that EHR was associated with four risk factors in the development cohort: total CTC count (p = 0.014), tumor size (p = 0.028), node number (p = 0.045), and microvascular invasion (p = 0.035). These factors were incorporated into two nomogram models (preoperative and postoperative), which reliably predicted EHR through multidimensional verification (e.g., calibration plot, receiver operating characteristic analysis, decision curve analysis, and clinical impact curve analysis) in the development and validation cohorts, respectively. With threshold of scores of 100.3 and 176.8 before and after surgery respectively, both nomograms were able to stratify patients into two distinct prognostic subgroups (all p < 0.05).ConclusionThe present study proposed two nomogram models integrating presurgical CTC counts and clinicopathological risks and showed relatively good predictive performance of EHR, which may be beneficial to the clinical practice of HCC recurrence. Further multicenter studies are needed to assess its general applicability.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

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