ArticleBMC cancer2022
Nomogram-based development and evaluation for predictions of 30-day and 1-year survival in patients with spontaneously ruptured hepatocellular carcinoma.
Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Machine learning prediction of 30-day all-cause mortality risk factors in HCC rupture.Frontiers in oncology · 2026Article
- Nomogram for Estimation of Acute Liver Failure Risk in Spontaneous Ruptured Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2023Article
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6 authors.
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Abstract
backgroundAccurately predicting the prognosis of patients with spontaneously ruptured hepatocellular carcinoma (HCC) is crucial for effective clinical management. The aim of the present study was to establish and evaluate prediction models for 30-day and 1-year survival in patients with spontaneously ruptured HCC.
methodsA total of 118 patients with spontaneous rupture HCC were enrolled. Univariate and multivariate analyses were performed using logistic-regression model and Cox proportional-hazard model. The identified indicators were used to establish prediction models, the performance of which we compared with those of commonly used liver disease scoring models. The survival possibilities of different risk categories were calculated using the newly developed models.
resultsLargest tumor size (LTS), serum albumin (ALB), total bilirubin (TBil), and serum creatinine were identified as independent predictors, which were used to establish a 30-day survival prediction model. LTS, BCLC staging, ALB, TBil, hepatectomy at rupture, and TACE during follow-up were identified as independent predictors of 1-year survival model. The 30-day survival model had sensitivity of 79.3%, specificity of 87.1%, and an AUC of 0.879, exhibiting better predictive performance than scores for Chronic Liver Failure Consortium Acute Decompensation score (CLIF-C ADs) and Model for End-stage Liver Disease (MELD). The 1-year survival model had sensitivity of 66.7%, specificity of 94.6%, and an AUC of 0.835, showing better predictive performance than Albumin-Bilirubin (ALBI), Child-Pugh, CLIF-C ADs, and MELD. After stratification, survival possibilities were 90.9 and 21.1% in low- and high-risk groups within 30 days, respectively, and 43.90, 4.35%, and 0 in low-, intermediate-, and high-risk groups at 1 year, respectively.
conclusionsThe established models exhibited good performance in predicting both 30-day and 1-year survival in patients with spontaneously ruptured HCC.
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