Competing risks analysis of external versus internal radiation in patients with hepatocellular carcinoma after controlling for immortal time bias.

J Cancer Res Clin Oncol

Department of Health Statistics, College of Public Health, Zhengzhou University, No. 100 Science Avenue, Zhengzhou, 450001, Henan Province, People's Republic of China.

Published: September 2023

Purpose: In cohort studies on liver cancer, there are often immortal time bias and interference of competing risk events. This study proposes to explore the role of internal and external radiotherapy for hepatocellular carcinoma using SEER data, using a competing risk model and controlling immortal time bias.

Methods: Data of SEER from 2004 till 2015 was included. To analyze whether there was a difference in survival between HCC (hepatocellular carcinoma) patients receiving external radiation and internal radiation, we used a competing risk analysis after excluding immortal time bias, and created a nomogram to assess the risk of cancer-specific death (CSD) in hepatocellular carcinoma patients receiving radiotherapy.

Results: Potential confounding factors adjusted, there was no significant difference in CSD between external and internal radiation therapy [HR and its 95% CI = 1.098 (0.874-1.380)]. The constructed nomogram performed better than the traditional AJCC model. The AUC and calibration curve results showed that this well-calibrated nomogram could be used to make clinical decisions regarding the prognosis and personalized treatment of hepatocellular carcinoma treated. There was no difference in the cumulative risk of death between patients with liver cancer treated with external radiation therapy and internal radiation therapy.

Conclusion: There is no difference in the cumulative risk of death between patients with liver cancer treated with external radiation therapy and internal radiation therapy. The nomogram predicts the results more accurately. These results can be used to guide the choice of treatment options for patients with HCC and to predict their survival prognosis.

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Source
http://dx.doi.org/10.1007/s00432-023-04915-8DOI Listing

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