models should be developed to assist choice between liver resection (lr) and transarterial chemoembolization (tace) for hepatocellular carcinoma.
after separating 520 cases from 5 hospitals into training (n = 302) and validation (n = 218) data sets, we weighted the cases to control baseline difference and ensured the causal effect between treatments (lr and tace) and estimated progression-free survival (pfs) difference. a noninvasive pfs model was constructed with clinical factors, radiological characteristics, and radiomic features. we compared our model with other 4 state-of-the-art models. finally, patients were classified into subgroups with and without significant pfs difference between treatments.
我们将来自5家医院的520例患者分为试验组(n = 302)和验证组(n = 218)数据集，然后对这些病例进行加权以控制基线差异，并确保治疗(lr和tace)和无进展生存(pfs)差异估值之间的因果关系。结合临床因素、影像学特点和放射特征，建立无创pfs模型。将我们的模型与其他4种最先进的模型进行了比较。最后，将患者分为治疗后pfs是否存在显著性差异的亚组。
our model included treatments, age, sex, modified barcelona clinic liver cancer stage, fusion lesions, hepatocellular carcinoma capsule, and 3 radiomic features, with good discrimination and calibrations (area under the curve for 3-year pfs was 0.80 in the training data set and 0.75 in the validation data set; similar results were achieved in 1- and 2-year pfs). the model had better accuracy than the other 4 models. a nomogram was built, with different scores assigned for lr and tace. separated by the threshold of score difference between treatments, for some patients, lr provided longer pfs and might be the better option (training: hazard ratio [hr] = 0.50, p = 0.014; validation: hr = 0.52, p = 0.026); in the others, lr provided similar pfs with tace (training: hr = 0.84, p = 0.388; validation: hr = 1.14, p = 0.614). tace may be better because it was less invasive.
we propose an individualized model predicting pfs difference between lr and tace to assist in the optimal treatment choice.