Association between socioeconomic status and survival in patients with hepatocellular carcinoma

Background The effect of socioeconomic status (SES) on hepatocellular carcinoma (HCC) is still unclear, and there is no nomogram integrated SES and clinicopathological factors to predict the prognosis of HCC. This research aims to confirm the effects of SES on predicting patients' survival and to establish a nomogram to predict the prognosis of HCC. Methods The data of HCC patients were collected from the Surveillance, Epidemiology, and Final Results (SEER) database from 2011 to 2015. SES (age at diagnosis, race and sex, median family income, education level, insurance status, marital status, residence, cost of living index, poverty rate) and clinicopathological factors were included in univariate and multivariate Cox regression analysis. Nomograms for predicting 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS) were established and evaluated by the concordance index (C-index), the receiver operating characteristic curve (ROC), the calibration plot, the integrated discrimination improvement (IDI), and the net reclassification improvement (NRI). Results A total of 33,670 diagnosed HCC patients were involved, and nomograms consisting of 19 variables were established. The C-indexes of the nomograms are higher than TNM staging system, which predicts the CSS (0.789 vs. 0.692, p < 0.01) and OS (0.777 vs. 0.675, p < 0.01). The ROC curve, calibration diagram, IDI, and NRI showed the improved prognostic value in 1-, 3-, and 5-year survival rates. Conclusion SES plays an important role in the prognosis of HCC patients. Therefore, policymakers can make more precise and socially approved policies to improve HCC patients' CSS and OS.

Automated summary

This study confirmed the impact of SES on predicting the survival of HCC patients and established a nomogram for predicting the prognosis. The results showed that SES plays a significant role in the prognosis of HCC patients, suggesting that more precise policies based on SES can improve patients' survival rates.