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Lasso-Cox interpretable model of AFP-negative hepatocellular carcinoma.
Li, Han; Zhou, Chengyuan; Wang, Chenjie; Li, Bo; Song, Yanqiong; Yang, Bo; Zhang, Yan; Li, Xueting; Rao, Mingyue; Zhang, Jianwen; Su, Ke; He, Kun; Han, Yunwei.
Afiliação
  • Li H; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • Zhou C; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • Wang C; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • Li B; Department of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
  • Song Y; School of Medicine, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Yang B; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • Zhang Y; Department of Oncology, Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University, Luzhou, 646000, China.
  • Li X; Department of Oncology, 363 Hospital, Chengdu, China.
  • Rao M; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • Zhang J; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • Su K; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
  • He K; Department of Radiation Oncology, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Han Y; Clinical Medical College, Southwest Medical University, Luzhou, 646000, China. hktongji@swmu.edu.cn.
Clin Transl Oncol ; 2024 Jul 04.
Article em En | MEDLINE | ID: mdl-38965191
ABSTRACT

BACKGROUND:

In AFP-negative hepatocellular carcinoma patients, markers for predicting tumor progression or prognosis are limited. Therefore, our objective is to establish an optimal predicet model for this subset of patients, utilizing interpretable methods to enhance the accuracy of HCC prognosis prediction.

METHODS:

We recruited a total of 508 AFP-negative HCC patients in this study, modeling with randomly divided training set and validated with validation set. At the same time, 86 patients treated in different time periods were used as internal validation. After comparing the cox model with the random forest model based on Lasso regression, we have chosen the former to build our model. This model has been interpreted with SHAP values and validated using ROC, DCA. Additionally, we have reconfirmed the model's effectiveness by employing an internal validation set of independent periods. Subsequently, we have established a risk stratification system.

RESULTS:

The AUC values of the Lasso-Cox model at 1, 2, and 3 years were 0.807, 0.846, and 0.803, and the AUC values of the Lasso-RSF model at 1, 2, and 3 years were 0.783, 0.829, and 0.776. Lasso-Cox model was finally used to predict the prognosis of AFP-negative HCC patients in this study. And BCLC stage, gamma-glutamyl transferase (GGT), diameter of tumor, lung metastases (LM), albumin (ALB), alkaline phosphatase (ALP), and the number of tumors were included in the model. The validation set and the separate internal validation set both indicate that the model is stable and accurate. Using risk factors to establish risk stratification, we observed that the survival time of the low-risk group, the middle-risk group, and the high-risk group decreased gradually, with significant differences among the three groups.

CONCLUSION:

The Lasso-Cox model based on AFP-negative HCC showed good predictive performance for liver cancer. SHAP explained the model for further clinical application.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Transl Oncol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Itália
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Transl Oncol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Itália