{"title":"基于术前甲胎蛋白、白蛋白和肿瘤负荷评分的新模型,用于预测早期 HCC 的微血管侵犯。","authors":"Yuan-Sheng Chang, Mu-Jung Tsai, Chieh-Jui Tsai, Chih-Chi Wang, Chih-Che Lin, Yi-Hao Yen, Chao-Hung Hung, Yuan-Hung Kuo, Ding-Sen Huang, Wei-Chen Tai, Tsung-Hui Hu, Ming-Chao Tsai","doi":"10.62347/ZGRJ7827","DOIUrl":null,"url":null,"abstract":"<p><p>Microscopic vascular invasion (MVI) has been demonstrated as a strong risk factor associated with tumor recurrence and poor overall survival among hepatocellular carcinoma (HCC) patients after resection, but the preoperative prediction of MVI is still challenging. We aimed to build and validate a novel model to predict MVI in the preoperative setting. We retrospectively collected 857 patients with Barcelona Clinic Liver Cancer (BCLC) stage 0 or A HCC who underwent primary resection at Kaohsiung Chang Gung Hospital between January 2001 and June 2016. The patients were randomized into derivation (n = 648) and validation groups (n = 209). Logistic regression analysis was used to screen out independent risk factors for MVI and further constructed a predictive model for MVI. Prediction performance was compared by the area under the receiver operating characteristic curve (AUC). The multivariable logistic regression analysis of the training cohort found that alpha-fetoprotein (AFP) ≥ 20 ng/mL (OR = 1.96, 95% CI: 1.41-2.73, P < 0.001), albumin < 3.5 g/dL (OR = 1.48, 95% CI: 1.06-2.05, P = 0.019) and tumor burden score (TBS) ≥ 8.6 (OR = 2.54, 95% CI: 1.49-4.35, P = 0.001) to be independent risk factors for MVI. The three factors were chosen to build a model for prediction of MVI. The AUC for the training and validation group was 0.619 (95% CI: 0.575-0.663) and 0.642 (95% CI: 0.562-0.722), respectively, and the calibration plot showed good performance of the prediction model, with a low mean absolute error at 0.01. In conclusion, the new model comprised AFP, albumin, and TBS that can predict risk of MVI for early-stage HCC.</p>","PeriodicalId":7437,"journal":{"name":"American journal of cancer research","volume":"14 10","pages":"4979-4988"},"PeriodicalIF":3.6000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11560811/pdf/","citationCount":"0","resultStr":"{\"title\":\"A new model based on preoperative AFP, albumin, and tumor burden score for predicting microvascular invasion in early-stage HCC.\",\"authors\":\"Yuan-Sheng Chang, Mu-Jung Tsai, Chieh-Jui Tsai, Chih-Chi Wang, Chih-Che Lin, Yi-Hao Yen, Chao-Hung Hung, Yuan-Hung Kuo, Ding-Sen Huang, Wei-Chen Tai, Tsung-Hui Hu, Ming-Chao Tsai\",\"doi\":\"10.62347/ZGRJ7827\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Microscopic vascular invasion (MVI) has been demonstrated as a strong risk factor associated with tumor recurrence and poor overall survival among hepatocellular carcinoma (HCC) patients after resection, but the preoperative prediction of MVI is still challenging. We aimed to build and validate a novel model to predict MVI in the preoperative setting. We retrospectively collected 857 patients with Barcelona Clinic Liver Cancer (BCLC) stage 0 or A HCC who underwent primary resection at Kaohsiung Chang Gung Hospital between January 2001 and June 2016. The patients were randomized into derivation (n = 648) and validation groups (n = 209). Logistic regression analysis was used to screen out independent risk factors for MVI and further constructed a predictive model for MVI. Prediction performance was compared by the area under the receiver operating characteristic curve (AUC). The multivariable logistic regression analysis of the training cohort found that alpha-fetoprotein (AFP) ≥ 20 ng/mL (OR = 1.96, 95% CI: 1.41-2.73, P < 0.001), albumin < 3.5 g/dL (OR = 1.48, 95% CI: 1.06-2.05, P = 0.019) and tumor burden score (TBS) ≥ 8.6 (OR = 2.54, 95% CI: 1.49-4.35, P = 0.001) to be independent risk factors for MVI. The three factors were chosen to build a model for prediction of MVI. The AUC for the training and validation group was 0.619 (95% CI: 0.575-0.663) and 0.642 (95% CI: 0.562-0.722), respectively, and the calibration plot showed good performance of the prediction model, with a low mean absolute error at 0.01. In conclusion, the new model comprised AFP, albumin, and TBS that can predict risk of MVI for early-stage HCC.</p>\",\"PeriodicalId\":7437,\"journal\":{\"name\":\"American journal of cancer research\",\"volume\":\"14 10\",\"pages\":\"4979-4988\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11560811/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of cancer research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.62347/ZGRJ7827\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.62347/ZGRJ7827","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
A new model based on preoperative AFP, albumin, and tumor burden score for predicting microvascular invasion in early-stage HCC.
Microscopic vascular invasion (MVI) has been demonstrated as a strong risk factor associated with tumor recurrence and poor overall survival among hepatocellular carcinoma (HCC) patients after resection, but the preoperative prediction of MVI is still challenging. We aimed to build and validate a novel model to predict MVI in the preoperative setting. We retrospectively collected 857 patients with Barcelona Clinic Liver Cancer (BCLC) stage 0 or A HCC who underwent primary resection at Kaohsiung Chang Gung Hospital between January 2001 and June 2016. The patients were randomized into derivation (n = 648) and validation groups (n = 209). Logistic regression analysis was used to screen out independent risk factors for MVI and further constructed a predictive model for MVI. Prediction performance was compared by the area under the receiver operating characteristic curve (AUC). The multivariable logistic regression analysis of the training cohort found that alpha-fetoprotein (AFP) ≥ 20 ng/mL (OR = 1.96, 95% CI: 1.41-2.73, P < 0.001), albumin < 3.5 g/dL (OR = 1.48, 95% CI: 1.06-2.05, P = 0.019) and tumor burden score (TBS) ≥ 8.6 (OR = 2.54, 95% CI: 1.49-4.35, P = 0.001) to be independent risk factors for MVI. The three factors were chosen to build a model for prediction of MVI. The AUC for the training and validation group was 0.619 (95% CI: 0.575-0.663) and 0.642 (95% CI: 0.562-0.722), respectively, and the calibration plot showed good performance of the prediction model, with a low mean absolute error at 0.01. In conclusion, the new model comprised AFP, albumin, and TBS that can predict risk of MVI for early-stage HCC.
期刊介绍:
The American Journal of Cancer Research (AJCR) (ISSN 2156-6976), is an independent open access, online only journal to facilitate rapid dissemination of novel discoveries in basic science and treatment of cancer. It was founded by a group of scientists for cancer research and clinical academic oncologists from around the world, who are devoted to the promotion and advancement of our understanding of the cancer and its treatment. The scope of AJCR is intended to encompass that of multi-disciplinary researchers from any scientific discipline where the primary focus of the research is to increase and integrate knowledge about etiology and molecular mechanisms of carcinogenesis with the ultimate aim of advancing the cure and prevention of this increasingly devastating disease. To achieve these aims AJCR will publish review articles, original articles and new techniques in cancer research and therapy. It will also publish hypothesis, case reports and letter to the editor. Unlike most other open access online journals, AJCR will keep most of the traditional features of paper print that we are all familiar with, such as continuous volume, issue numbers, as well as continuous page numbers to retain our comfortable familiarity towards an academic journal.