Leyao Wang1, Sicong Wang2, Xiaohong Ma1, and Xinming Zhao1
1National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 2GE healthcare, MR Research China, Beijing, China
Synopsis
Keywords: Liver, Liver
Motivation: Evaluate the performance of the LI-RADS v2018 features and clinical-pathological factors for predicting the prognosis of AFP-negative HCC.
Goal(s): To evaluate the performance of the LI-RADS v2018 features and clinical-pathological factors for predicting the prognosis of AFP-negative HCC.
Approach: A total of 169 AFP-negative HCC patients were enrolled. Risk factors associated with prognosis were identified by Cox regression analysis.
Results: Six risk factors, namely the LI-RADS category, blood products in mass, MVI, tumor size, cirrhosis, and ALBI grade, were associated with recurrence-free survival. The model effectively stratified patients with AFP-negative HCC into high- and low-risk groups with significantly different outcomes (p < 0.05).
Impact: In this study, our prognostic model composed of the LI-RADS category, blood products in mass, MVI, tumor size, cirrhosis, and ALBI grade accurately classified patients into different recurrence risk groups.
Introduction
Alpha-fetoprotein (AFP), an important serological marker for screening and diagnosing HCC, reflects the burden and invasive phenotype of hepatocellular carcinoma (HCC) to some extent. Serum AFP is an important indicator commonly used in diagnosis and therapeutic efficacy monitoring of HCC. Patients with high serum AFP levels usually exhibit an aggressive phenotype that results in poor survival outcomes [1,2, 3]. However, AFP levels are not evaluated in approximately 30–40% of patients with HCC, which limits its use in prognostic prediction and disease diagnosis [4]. The prognosis for AFP-negative patients is uncertain, and prognostic studies in AFP-negative patients are urgently needed. As far as we are aware, there is limited information on the prognostic role of standardized imaging features in patients with AFP-negative HCC. In addition, the performance of several existing staging systems, such as the BCLC staging system and the AJCC-TNM staging system, remains unclear in terms of HCC recurrence prediction. Therefore, accurate prognostic risk assessment models should be developed to guide individualized treatment, postoperative management, and surveillance strategies in patients with AFP-negative HCC. The objective of this study was to construct and evaluate a predictive model incorporating imaging characteristics and clinical-pathological parameters for predicting prognosis and achieving risk stratification in patients with AFP-negative HCC after hepatectomy.Methods
We retrospectively enrolled 169 patients with AFP-negative HCC who received preoperative MRI and hepatectomy between January 2015 and August 2020 (derivation dataset: validation dataset = 118: 51). Two observers independently reviewed the presence or absence of LI-RADS version 2018 major imaging features, ancillary imaging features, and non-LI-RADS imaging features without knowledge of clinical-pathological and follow-up information. Additionally, each lesion was categorized as either LR-4 (probably HCC), LR-M (probably or definitely malignant, not necessarily HCC), or LR-5 (definitely HCC) according to LI-RADS version 2018. Recurrence-free survival (RFS) was the follow-up endpoint of this study. A prognostic model was constructed using the risk factors identified via Cox regression analysis. Predictive performance and discrimination capability were evaluated and compared with those of two traditional staging systems.Results
The median follow-up time was 38.10 months (range, 2.33–92.93 months). Of the 89 patients who presented with tumor recurrence or metastasis, eighty patients (89.89%) had intrahepatic recurrence, nine patients (10.11%) had extrahepatic recurrence, included three bone metastasis, one adrenal metastasis, three lymph node metastasis, and two lung metastasis. In the derivation dataset, the median follow-up time was 37.53 months (range, 2.33–89.93 months). In the validation dataset, the median follow-up time was 38.10 months (range, 5.2–92.93 months). Six risk factors, namely the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin–bilirubin grade, were associated with recurrence-free survival. The prognostic model constructed using these factors achieved C-index of 0.705 and 0.674 in the derivation and validation datasets, respectively. Furthermore, the model performed better in predicting patient prognosis than traditional staging systems. The model effectively stratified patients with AFP-negative HCC into high- and low-risk groups with significantly different outcomes (p < 0.05). Furthermore, we evaluated the validity of the nomogram in predicting RFS against that of the AJCC-TNM and BCLC staging systems. The C-index of the AJCC-TNM staging system was 0.599 and 0.596 in the derivation and validation cohorts, respectively. The C-index of the BCLC staging system was 0.534 and 0.538 in the derivation and validation cohorts, respectively.Conclusion
A prognostic model integrating the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin–bilirubin grade may serve as a valuable tool for refining risk stratification in patients with AFP-negative HCC.Acknowledgements
No acknowledgement found.References
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