RESUMEN
BACKGROUND: Hepatocellular carcinoma (HCC) recurrence following surgical resection remains a significant clinical challenge, necessitating reliable predictive models to guide personalised interventions. In this study, we sought to harness the power of artificial intelligence (AI) to develop a robust predictive model for HCC recurrence using comprehensive clinical datasets. METHODS: Leveraging data from 958 patients across multiple centres in Australia and Hong Kong, we employed a multilayer perceptron (MLP) as the optimal classifier for model generation. RESULTS: Through rigorous internal cross-validation, including a cohort from the Chinese University of Hong Kong (CUHK), our AI model successfully identified specific pre-surgical risk factors associated with HCC recurrence. These factors encompassed hepatic synthetic function, liver disease aetiology, ethnicity and modifiable metabolic risk factors, collectively contributing to the predictive synergy of our model. Notably, our model exhibited high accuracy during cross-validation (.857 ± .023) and testing on the CUHK cohort (.835), with a notable degree of confidence in predicting HCC recurrence within accurately classified patient cohorts. To facilitate clinical application, we developed an online AI digital tool capable of real-time prediction of HCC recurrence risk, demonstrating acceptable accuracy at the individual patient level. CONCLUSION: Our findings underscore the potential of AI-driven predictive models in facilitating personalised risk stratification and targeted interventions to mitigate HCC recurrence by identifying modifiable risk factors unique to each patient. This model aims to aid clinicians in devising strategies to disrupt the underlying carcinogenic network driving recurrence.
RESUMEN
Hepatocellular carcinoma (HCC) has been linked to the gut microbiota, with recent studies revealing the potential of gut-generated responses to influence several arms of the immune responses relevant to HCC formation. The pro- or anti-tumor effects of specific bacterial strains or gut microbiota-related metabolites, such as bile acids and short-chain fatty acids, have been highlighted in many human and animal studies. The critical role of the gut microbiota in HCC development has spurred interest in modulating the gut microbiota through dietary interventions, probiotics, and fecal microbiota transplantation as a potential strategy to improve liver cancer outcomes. Encouragingly, preclinical and clinical studies have demonstrated that modulation of the gut microbiota can ameliorate liver function, reduce inflammation, and inhibit liver tumor growth, underscoring the potential of this approach to improve HCC outcomes. As research continues to unravel the complex and dynamic mechanisms underlying the gut-liver axis, the development of safe and effective interventions to target this pathway for liver cancer prevention and treatment appears to be on the horizon, heralding a significant advance in our ongoing efforts to combat this devastating disease.