Abstract
Prophylactic transarterial chemoembolization (p-TACE) is frequently conducted for patients with hepatocellular carcinoma (HCC) in China, but the question of who could benefit from it remains controversial. Hence, we wanted to establish a nomogram model to identify patients eligible for p-TACE. Data from HCC patients receiving R0 resection with or without p-TACE between January 2013 and December 2014 were identified, using primary liver cancer big data, to establish a nomogram model to predict overall survival (OS). Based on the model, Patients receiving R0 resection between January 2015 and December 2015 were divided into three subgroups, and survival curves were constructed using the Kaplan-Meier method and analyzed by the log-rank test among patients in each subgroup. A nomogram integrating the neutrophil to lymphocyte ratio, AFP, tumor diameter, and microvascular invasion was developed to predict the OS of patients with HCC receiving R0 resection, and significant differences were observed in the median OS of the subgroups of low-risk (≤20), intermediate-risk (20~120), and high-risk (>120) identified by the current model. This model showed good calibration and discriminatory power in the validation cohort and the external cohort (c-index of 0.669 and 0.676, respectively). In the external cohort, the Kaplan-Meier curves showed that p-TACE could only significantly prolong the median OS of high-risk patients (25.6 vs. 33.7 months, P<0.05), but no differences were observed in any subgroups stratified by the current staging systems (all P>0.05). This readily available nomogram model could help guide decisions about p-TACE, but it needs further validation.
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