Department of Minimal invasive intervention, Sun Yat-sen University Cancer Center, Guangzhou, China.
State Key Laboratory of Oncology in South China, Guangzhou, China.
Cancer Med. 2020 Sep;9(18):6497-6506. doi: 10.1002/cam4.3250. Epub 2020 Jul 23.
To develop a clinicopathological-based nomogram to improve the prediction of the seeding risk of after percutaneous thermal ablation (PTA) in primary liver carcinoma (PLC).
A 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).
The 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).
The clinicopathological-based nomogram could be used to quantify the probability of seeding risk after PTA in PLC.
建立一种基于临床病理特征的列线图，以提高对原发性肝癌（PLC）经皮热消融（PTA）后种植风险的预测能力。
本研究纳入了 2009 年 4 月至 2018 年 12 月期间接受 PTA 的 2030 例 PLC 患者。将患者分为训练数据集（n=1024）和外部验证数据集（n=1006）。收集基线特征，以确定 PTA 后种植的危险因素。基于危险因素的多变量 Cox 比例风险模型用于建立列线图，并主要使用 Harrell 的 C 指数和受试者工作特征曲线（AUC）评估其预测准确性。
中位随访时间为 30.3 个月（范围：3.2-115.7 个月）。在训练集中，每个肿瘤的种植风险为 0.89%，每个患者的种植风险为 1.5%。该列线图是基于肿瘤大小、包膜下、甲胎蛋白（AFP）和国际标准化比值（INR）建立的。低危组的 1、2、3 年累积种植率分别为 0.1%、0.7%和 1.2%，高危组分别为 1.7%、6.3%和 6.3%，差异有统计学意义（P<0.001）。该列线图在训练集中具有良好的校准和区分能力，C 指数为 0.722（95%可信区间[CI]：0.661，0.883），AUC 为 0.850（95%CI：0.767，0.934）。对 1000 个 bootstrap 样本集进行外部验证显示，C 指数为 0.706（95%CI：0.546，0.866），AUC 为 0.736（95%CI：0.646，0.827），具有良好的效果。
该基于临床病理特征的列线图可用于量化 PLC 患者 PTA 后种植风险的概率。
