ArticleCancer medicine2020
Development and validation of a clinicopathological-based nomogram to predict seeding risk after percutaneous thermal ablation of primary liver carcinoma.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 9 citations in OpenAlex.
- Constructing and validating a prognostic prediction nomogram model for hepatocellular carcinoma patients following high-intensity focused ultrasound treatment.Frontiers in oncology · 2026Article
- Establishment of a risk prediction model for hydrocephalus complicated by neonatal bacterial meningitis.BMC infectious diseases · 2025Article
- A Nomogram Model to Predict Deep Vein Thrombosis Risk After Surgery in Patients with Hip Fractures.Indian journal of orthopaedics · 2024Article
- Factors associated with increased risk of peritoneal seeding after radiofrequency ablation for hepatocellular carcinoma.Abdominal radiology (New York) · 2023Article
- Development and validation of a clinicopathological-based nomogram to predict seeding risk after percutaneous thermal ablation of primary liver carcinoma.Cancer medicine · 2020Article
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7 authors at 1 institution in 1 country.
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Abstract
objectivesTo develop a clinicopathological-based nomogram to improve the prediction of the seeding risk of after percutaneous thermal ablation (PTA) in primary liver carcinoma (PLC).
methodsA total of 2030 patients with PLC who underwent PTA were included between April 2009 and December 2018. The patients were grouped into a training dataset (n = 1024) and an external validation dataset (n = 1006). Baseline characteristics were collected to identify the risk factors of seeding after PTA. The multivariate Cox proportional hazards model based on the risk factors was used to develop the nomogram, which was used for assessment for its predictive accuracy using mainly the Harrell's C-index and receiver operating characteristic curve (AUC).
resultsThe median follow-up time was 30.3 months (range, 3.2-115.7 months). The seeding risk was 0.89% per tumor and 1.5% per patient in the training set. The nomogram was developed based on tumor size, subcapsular, α-fetoprotein (AFP), and international normalized ratio (INR). The 1-, 2-, and 3-year cumulative seeding rates were 0.1%, 0.7% and 1.2% in the low-risk group, and 1.7%, 6.3% and 6.3% in the high-risk group, respectively, showing significant statistical difference (P < .001). The nomogram had good calibration and discriminatory abilities in the training set, with C-indexes of 0.722 (95% confidence interval [CI]: 0.661, 0.883) and AUC of 0.850 (95% CI: 0.767, 0.934). External validation with 1000 bootstrapped sample sets showed a good C-index of 0.706 (95% CI: 0.546, 0.866) and AUC of 0.736 (95% CI: 0. 646, 0.827).
conclusionsThe clinicopathological-based nomogram could be used to quantify the probability of seeding risk after PTA in PLC.
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