Construction of Nomogram-Based Prediction Model for Clinical Prognosis of Patients with Stage II and III Colon Cancer Who Underwent Xelox Chemotherapy after Laparoscopic Radical Resection. (30th September 2022)
- Record Type:
- Journal Article
- Title:
- Construction of Nomogram-Based Prediction Model for Clinical Prognosis of Patients with Stage II and III Colon Cancer Who Underwent Xelox Chemotherapy after Laparoscopic Radical Resection. (30th September 2022)
- Main Title:
- Construction of Nomogram-Based Prediction Model for Clinical Prognosis of Patients with Stage II and III Colon Cancer Who Underwent Xelox Chemotherapy after Laparoscopic Radical Resection
- Authors:
- Sun, Qiang
Xu, Kai
Teng, Shifeng
Wang, Wenqiang
Zhang, Wei
Li, Xinxing
Hu, Zhiqian - Other Names:
- Liman Recep Academic Editor.
- Abstract:
- Abstract : Objective . To construct a nomogram-based prediction model for the clinical prognosis of patients with stage II and III colon cancer who underwent Xelox chemotherapy after laparoscopic radical resection based on large data sets. Methods . A total of 7, 832 patients with colorectal cancer who received postoperative Xelox-based chemotherapy were screened from the Surveillance, Epidemiology, and End Results database (USA) as the training data set. In addition, 348 domestic patients were screened as the validation data set. Multivariate Cox regression analysis was performed to identify variables for inclusion in the nomogram-based prediction model. The predictive accuracy of the model was assessed using C-index and calibration curve. Results . Age, cell differentiation, nerve invasion, T and N stages of tumours, number of dissected lymph nodes, and carcinoembryonic antigen (CEA) level were found to influence the efficacy of postoperative chemotherapy. The nomogram-based prediction model was successfully constructed. The C-index of both the training set and validation set were higher than those of the 7th edition of TNM staging system published by the American Joint Commission on Cancer (C − index of training data set = 0.728, C − index of validation data set = 0.734 ). The prediction results of the model in the calibration curve showed a good fit with the actual situation. Conclusion . We successfully constructed a nomogram-based model to predict theAbstract : Objective . To construct a nomogram-based prediction model for the clinical prognosis of patients with stage II and III colon cancer who underwent Xelox chemotherapy after laparoscopic radical resection based on large data sets. Methods . A total of 7, 832 patients with colorectal cancer who received postoperative Xelox-based chemotherapy were screened from the Surveillance, Epidemiology, and End Results database (USA) as the training data set. In addition, 348 domestic patients were screened as the validation data set. Multivariate Cox regression analysis was performed to identify variables for inclusion in the nomogram-based prediction model. The predictive accuracy of the model was assessed using C-index and calibration curve. Results . Age, cell differentiation, nerve invasion, T and N stages of tumours, number of dissected lymph nodes, and carcinoembryonic antigen (CEA) level were found to influence the efficacy of postoperative chemotherapy. The nomogram-based prediction model was successfully constructed. The C-index of both the training set and validation set were higher than those of the 7th edition of TNM staging system published by the American Joint Commission on Cancer (C − index of training data set = 0.728, C − index of validation data set = 0.734 ). The prediction results of the model in the calibration curve showed a good fit with the actual situation. Conclusion . We successfully constructed a nomogram-based model to predict the clinical prognosis of patients with colorectal cancer receiving postoperative Xelox-based chemotherapy after laparoscopic radical resection, which showed good clinical application value for predicting the efficacy of postoperative Xelox-based chemotherapy in patients with colorectal cancer. … (more)
- Is Part Of:
- Journal of oncology. Volume 2022(2022)
- Journal:
- Journal of oncology
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09-30
- Subjects:
- Oncology -- Research -- Periodicals
Tumors -- Periodicals
Neoplasms
Oncology -- Research
Tumors
Periodicals
Periodicals
616.994 - Journal URLs:
- https://www.hindawi.com/journals/jo/ ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=859&action=archive ↗ - DOI:
- 10.1155/2022/7742035 ↗
- Languages:
- English
- ISSNs:
- 1687-8450
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24086.xml