Bibliographic Details
| Title: |
Application of Clinical Prediction Models for Postoperative Complications of Colorectal Cancer |
| Authors: |
LIN Hao, HU Ting, WANG Chaoyang, ZHANG Haibao, JU Jiahua, YU Yongjiang |
| Source: |
Zhongliu Fangzhi Yanjiu, Vol 50, Iss 9, Pp 908-912 (2023) |
| Publisher Information: |
Magazine House of Cancer Research on Prevention and Treatment, 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
colorectal cancer, complications, clinical prediction model, risk factors, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
Postoperative complications of colorectal cancer (CRC) are the main cause of postoperative death and seriously affect the quality of life and survival time of patients. The application of a clinical prediction model for postoperative complications of CRC can help promptly identify high-risk patients. Accordingly, reasonable intervention measures can be actively taken to reduce the incidence of postoperative complications of CRC. A scientific basis can also be provided to improve the prognosis of patients. In this work, literature on the risk-factor analysis and prediction-model construction of postoperative complications of CRC at home and abroad in recent years was collected and reviewed. The evaluation content and efficiency of the clinical prediction models in postoperative complications of CRC were summarized. Their advantages and disadvantages were also analyzed. The purpose of this study was to provide a reference for the subsequent optimization of such models and the development of a strong, clinically practical, and universal risk-screening tool for postoperative complications of CRC. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
Chinese |
| ISSN: |
1000-8578 |
| Relation: |
http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.23.0293; https://doaj.org/toc/1000-8578 |
| DOI: |
10.3971/j.issn.1000-8578.2023.23.0293 |
| Access URL: |
https://doaj.org/article/2718e1793ce44b3286044904eaea71f1 |
| Accession Number: |
edsdoj.2718e1793ce44b3286044904eaea71f1 |
| Database: |
Directory of Open Access Journals |
