The proliferation of the biomarker Ki67 has been extensively studied in colorectal cancer (CRC). Although numerous Ki67 cut-off values have previously been reported, the optimal cut-off value remains unclear with previous studies providing contrasting results. The present retrospective cohort study aimed to determine the optimal cut-off value for CRC. Ki67 levels and the prognosis of patients with non-metastatic CRC were obtained from the Electronic Health Information System of a tertiary hospital in Kunming City. The Restricted Cubic Spline (RCS) model was used to analyze the non-linear association between Ki67 levels and the risk of patient death and metastasis. Moreover, the RCS model was used to determine the optimal cut-off value of Ki67. Cox proportional hazards models were used to verify the effects of the cut-off value. In total, 210 patients with CRC and a median age of 62.5 years (age range, 23.0-88.0 years) were studied. Results of the present study demonstrated a non-linear association between Ki67 levels and the risk of patient death based on the RCS model, and at Ki67 levels â¥60%, the hazard ratio (HR) of patient death gradually increased. Using multivariate-adjusted Cox proportional hazards models, the results of the present study demonstrated that Ki67 â¥60% indicated a high-risk ratio for both distant metastasis and death [HR, 2.640; 95% confidence interval (CI), 1.066-6.539], compared with Ki67 <60% (HR, 2.558; 95% CI, 1.079-6.064). Therefore, Ki67 â¥60% may be the optimal cut-off value for the prediction of death and metastasis in patients with CRC. Thus, Ki67 may act as a biomarker for predicting the prognosis of patients with CRC, and the optimal cut-off value for the prediction of both death and metastasis of patients with CRC is 60%.
Ki67 testing in the clinical management of patients with non-metastatic colorectal cancer: Detecting the optimal cut-off value based on the Restricted Cubic Spline model.
Ki67 检测在非转移性结直肠癌患者临床管理中的应用:基于限制性三次样条模型检测最佳临界值
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作者:Lei Hong Tao, Yan Shan, He Yin Hua, Xu Ning, Zhao Min, Yu Chun Jiao, Li Hong Lin, Kuang Sai, Cui Zhan Hang, Fang Jing
| 期刊: | Oncology Letters | 影响因子: | 2.200 |
| 时间: | 2022 | 起止号: | 2022 Oct 7; 24(6):420 |
| doi: | 10.3892/ol.2022.13540 | 研究方向: | 肿瘤 |
| 疾病类型: | 肠癌 | ||
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