Prognostic significance of identification of traditional Chinese medicine syndromes in colorectal cancer

TRADITIONAL MEDICINE RESEARCH(2023)

引用 0|浏览7
暂无评分
摘要
Background: Traditional Chinese medicine (TCM) syndrome is the basic unit of TCM treatment, which help clinicians assess the disease progression and treatment preoperative of tumor patients. However, the prognostic significance of TCM syndrome is still unclear. This study aims to detect the differences in overall survival between different TCM syndrome and further develop a new nomogram with TCM syndrome for predicting overall survival in colorectal cancer. Methods: A total of 324 patients with colorectal cancer were enrolled and categorized into three groups based on TCM syndrome: deficiency, excess, and deficiency-excess. The prognosis of colorectal cancer patients with different TCM syndromes was evaluated using Kaplan-Meier analysis and Cox regression analysis. Results: The proportion of advanced stage and lymph metastasis in the patients with deficiency syndrome was higher, and the overall survival was shorter than other syndromes. Meanwhile, the TCM syndrome (P < 0.001), tumor invasion depth (P < 0.001), lymph metastasis (P = 0.018), organic metastasis (P = 0.005) and tumor node metastasis (TNM) stage (P = 0.029) were the independent prognostic factor. Then, a new nomogram with TCM syndrome was established and assessed. 324 colorectal cancer patients were randomly divided into training (n = 215) and validation cohorts (n = 109). A nomogram incorporating preoperative TCM syndrome, gender, age, T, N, and M status was developed, which had good discrimination and calibration. Conclusion: Taken together, our results indicated that TCM syndrome could assess the prognosis of colorectal cancer. The nomogram incorporating TCM syndromes and tumor information is helpful for risk stratification and prognostic predictions in colorectal cancer preoperatively.
更多
查看译文
关键词
colorectal cancer, traditional Chinese medicine syndromes, overall survival, prognosis, nomogram
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要