Academic Journal
Influencing factors and establishment of a prediction model for the tumor regression after neoadjuvant chemoradiotherapy in locally advanced rectal cancer
| العنوان: | Influencing factors and establishment of a prediction model for the tumor regression after neoadjuvant chemoradiotherapy in locally advanced rectal cancer |
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| المؤلفون: | LIU Zhiyu, XU Dong, CHEN Xihao, LI Jipeng |
| المصدر: | Zhongguo aizheng zazhi, Vol 34, Iss 2, Pp 191-200 (2024) |
| بيانات النشر: | Editorial Office of China Oncology, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| مصطلحات موضوعية: | rectal cancer, local advanced, neoadjuvant chemoradiotherapy, tumor regression prediction, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| الوصف: | Background and purpose: The standard therapy for locally advanced rectal cancer (LARC) is neoadjuvant chemoradiotherapy (nCRT) followed by surgery. NCRT can make the tumor regress and downstage, and increase the R0 resection rate. However, individual differences in rectal cancer are large, and some patients respond poorly to nCRT and cannot benefit from nCRT. Therefore, it is necessary to establish effective screening measures to identify patients with poor response to nCRT. This study aimed to analyze the influencing factors of nCRT for LARC and construct the tumor regression prediction model. Methods: Data of 158 LARC patients who underwent total mesenteric resection after receiving nCRT at the First Hospital Affiliated to Air Force Medical University from January 2016 to December 2020 were collected. Baseline clinical indicators before nCRT were collected, including laboratory examination, tumor markers and magnetic resonance imaging (MRI). According to the tumor size reported by MRI before and after nCRT, Response Evaluation Criteria in Solid Tumors (RECIST) was used to evaluate the extent of tumor regression after nCRT. After receiver operating characteristic (ROC) curve was used to standardize the clinical baseline indicators, logistic regression analysis was carried out to screen the factors affecting the tumor regression. The tumor regression prediction model was constructed by logistic regression, and the performance of the model was evaluated based on decision curve analysis (DCA) and the calibration curve. The accuracy of the model was tested by 10-fold cross-validation. Results: This retrospective cohort study enrolled 158 patients, in which, 98 patients achieved complete response (CR) or partial response (PR). The objective response rate was 62%. Sixty patients had poor response to nCRT, either stable disease (SD) or progressive disease (PD). Multivariate logistic regression analysis showed that tumor diameter before treatment (P |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English Chinese |
| تدمد: | 1007-3639 |
| Relation: | http://www.china-oncology.com/fileup/1007-3639/PDF/1710376758512-844925324.pdf; https://doaj.org/toc/1007-3639 |
| DOI: | 10.19401/j.cnki.1007-3639.2024.02.007 |
| URL الوصول: | https://doaj.org/article/b77bd520a4a84a82b5f4130d6dc40948 |
| رقم الانضمام: | edsdoj.b77bd520a4a84a82b5f4130d6dc40948 |
| قاعدة البيانات: | Directory of Open Access Journals |
| تدمد: | 10073639 |
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| DOI: | 10.19401/j.cnki.1007-3639.2024.02.007 |