مورد إلكتروني
Establishment of Nomogram Model for Minimally Invasive Treatment of Small Hepatocellular Carcinoma Based on CD8+T Cell Counts
| العنوان: | Establishment of Nomogram Model for Minimally Invasive Treatment of Small Hepatocellular Carcinoma Based on CD8+T Cell Counts |
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| المؤلفون: | Pu,Qing, Yu,Lihua, Wang,Xinhui, Yan,Huiwen, Xie,Yuqing, Du,Juan, Yang,Zhiyun |
| بيانات النشر: | Dove Press 2022-08-31 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Qing Pu,1,* Lihua Yu,1,* Xinhui Wang,1 Huiwen Yan,1 Yuqing Xie,1 Juan Du,2 Zhiyun Yang1 1Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, Peopleâs Republic of China; 2Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, Peopleâs Republic of China*These authors contributed equally to this workCorrespondence: Juan Du, Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, Peopleâs Republic of China, Email duj656@163.com Zhiyun Yang, Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, Peopleâs Republic of China, Tel/Fax +86-10-84322148, Email yangzhiyun2016@163.comPurpose: Minimally invasive treatment of small hepatocellular carcinoma (HCC) is the main way of treatment, which can cause the change of HCC immune microenvironment. T lymphocytes are an important part of the immune microenvironment and may be powerful predictors of prognosis. The purpose of this study was to explore the effect of T lymphocytes on the prognosis of HCC and establish a prognostic model.Patients and Methods: We conducted a retrospective study of 300 patients with small HCC and developed a clinical prediction model. The selection of modeling variables was performed by combining backward stepwise Cox regression using Akaikeâs Information Criteria (AIC) and the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Establish a dynamic nomogram model to predict 1-, 2-, and 3-year overall survival (OS). Receiver operating characteristic curve (ROC curve) was used to verify the model discriminative ability, calibration curve was used to examine the model calibration ability, and decision curve analysis (DCA) was used to evaluate the clinical value.R |
| مصطلحات الفهرس: | OncoTargets and Therapy, Original Research, info:eu-repo/semantics/article |
| URL: | info:eu-repo/semantics/altIdentifier/doi/10.2147/OTT.S373631 |
| الإتاحة: | Open access content. Open access content info:eu-repo/semantics/openAccess |
| ملاحظة: | text/html English |
| أرقام أخرى: | NZDMP oai:dovepress.com/77823 1351714976 |
| المصدر المساهم: | DOVE MEDL PRESS LTD From OAIster®, provided by the OCLC Cooperative. |
| رقم الأكسشن: | edsoai.on1351714976 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |