Background: Hepatocellular carcinoma (HCC) poses a significant challenge for patients ineligible for surgical resection or liver transplantation. Local therapies like Stereotactic Body Radiotherapy (SBRT) are crucial for those with liver-limited disease. Insulin-like growth factor-1 (IGF-1) is a potential biomarker for liver function. This study evaluates IGF-1's prognostic value in predicting survival outcomes in HCC patients undergoing SBRT.
Methods: We analyzed 42 HCC patients treated with SBRT between May 2021 and January 2024, with IGF-1 levels measured within four weeks before SBRT. Patient demographics, tumor metrics, and clinical outcomes were examined. The prognostic significance of IGF-1 was assessed using Cox proportional hazards and ROC curve analysis to determine optimal IGF-1 cutoffs for survival prediction. A nomogram predicting 1-year and 2-year survival was constructed using a multivariate Cox model.
Results: IGF-1 levels were significantly lower in patients with cirrhosis or sarcopenia. Median overall survival (OS) was 24 months, with a significant survival difference favoring patients with IGF-1 levels above 62.4 ng/ml (Hazard Ratio [HR]: 5.9, P = 0.0025). A multivariable Cox model including Child-Turcotte-Pugh (CTP) score, IGF-1, and tumor volume effectively predicted survival. IGF-1 and tumor volume significantly impacted OS (HR: 6.9 and 1.004, p = 0.014 and 0.0022, respectively). Integrating IGF-1 with CTP score improved predictive accuracy (c-index 0.66 to 0.75, p = 0.052).The nomogram, integrating IGF-1 with the CTP and tumour volume, exhibited robust predictive accuracy with an area under the curve (AUC) of 0.84 for 2-year survival.
Conclusion: IGF-1 is a reliable biomarker for liver function and survival prediction in HCC patients undergoing SBRT. Higher IGF-1 levels indicate better prognosis. The developed nomogram, incorporating IGF-1, enhances clinical decision-making for SBRT management. Further validation in larger cohorts is needed.
Keywords: Hepatocellular carcinoma; IGF-1; Liver cancer prognosis; Nomogram; SBRT; Survival analysis.
© 2024 The Author(s).