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Predicting survival time of Korean hepatocellular carcinoma patients using the Cox proportional hazards model: a retrospective study based on big data analysis.

AIM
To predict survival time of Korean hepatocellular carcinoma (HCC) patients by analyzing big data using Cox proportional hazards model.


METHODS
Big data of the patients who underwent treatment for HCC from 2008 to 2015, provided by Korea Central Cancer Registry, National Cancer Center, and Ministry of Health and Welfare, were analyzed. A total of 10 742 patients with HCC were divided into two groups, with Group I (3021 patients) confirmed on biopsy and Group II (5563 patients) diagnosed as HCC according to HCC diagnostic criteria as outlined in Korean Liver Cancer Association guidelines. Univariate and multivariate Cox regression analyses were performed to identify independent risk factors of recurrence after treatment and survival status.


RESULTS
A total of 3021 patients in Group I and 5563 patients in Group II were included in the study and the difference in survival time between the two groups was statistically significant (P < 0.05). Recurrence was only included in intrahepatic cases, and the rates were 21.2 and 19.8% while the periods from the first treatment to recurrence were 15.57 and 14.19 months, respectively. Age, diabetes, BMI, platelet, alpha-fetoprotein, histologic tumor maximum size, imaging T stage, presence of recurrence, and duration of recurrence were included in multivariate analysis.


CONCLUSION
By using nationwide, multicenter big data, it is possible to predict recurrence rate and survival time which can provide the basis for treatment response to develop a predictive program.