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| Analysis of risk factors and Bayesian network model for the survival of patients with primary hepatic cancer |
| 1Liu Sainan,2Zhao Heping,1Wei Manzhen,3Huang He |
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Abstract Objective The complex network relationship among risk factors of primary hepatic cancer PHC was deeply studied by
Bayesian network model and investigate the risk factors that affect the 30-month survival. Method The clinical data of 363 patients
with PHC from October 2016 to November 2020 in the First Hospital of Shanxi Medical University were retrospectively analyzed.
Through follow-up surveys we have learned about the PHC patients' survival status etc. The survival was counted in months starting
from the time of initial diagnosis and the follow-up surveys ended in October 2022. Based on literature reports and in combination
with the average survival of PHC patients in this study 29. 6 months a final decision was made to select 30 months as the research
node for survival. The related factors affecting the 30 - month survival of PHC patients were analyzed using both univariate and
multivariate logistic regression. Additionally a Bayesian network model was established to further explore the complex network
relationship among the risk factors for survival in PHC patients and to calculate the conditional probability among the factors. The
effectiveness of the model was verified by receiver operating characteristic and calibration plot. Result Among the 363 patients with
PHC 167 patients had a survival of < 30 months 46. 01% . The results of the univariate analysis showed significant statistical
differences between the two groups of patients in terms of γ-glutamyl transferase γ-GT levels tumor size and the occurrence or
absence of distant metastasis. The results of the multivariate logistic regression analysis revealed that γ-GT >40 U/ L tumor size >
3 cm and distant metastasis were risk factors for 30-month survival node of PHC patients P<0. 05 for all . The Bayesian network
model showed that for PHC patients tumor size γ-GT levels and the occurrence or absence of distant metastasis were direct risk
factors that affected their 30-month survival while tumor count and age were indirect risk factors that also influenced their 30-month survival. The conditional probability distribution table showed that tumor size >3 cm γ-GT >40 U/ L and distant metastasis in patients
with PHC had the highest probability of survival <30 months 98. 408% . Conclusion The tumor size >3 cm γ-GT level >40 U/ L
and distant metastasis are the risk factors affecting the 30-month survival of PHC patients. Age have a indirect relationship with the
30-month survival of PHC patients by affecting tumor size and the occurrence or absence of distant metastasis.
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