PDF(Pubmed)
Abstract：
OBJECTIVE: Using the preoperative pan-immune-inflammation value (PIV) and the monocyte to high-density lipoprotein ratio (MHR) to reflect inflammation, immunity, and cholesterol metabolism, we aim to develop and visualize a novel nomogram model for predicting the survival outcomes in patients with colorectal cancer (CRC).
METHODS: A total of 172 patients with CRC who underwent radical resection were retrospectively analyzed. Survival analysis was conducted after patients were grouped according to the optimal cut-off values of PIV and MHR. Univariate and multivariate analyses were performed using Cox proportional hazards regression to screen the independent prognostic factors. Based on these factors, a nomogram was constructed and validated.
RESULTS: The PIV was significantly associated with tumor location (P < 0.001), tumor maximum diameter (P = 0.008), and T stage (P = 0.019). The MHR was closely related to gender (P = 0.016), tumor maximum diameter (P = 0.002), and T stage (P = 0.038). Multivariate analysis results showed that PIV (Hazard Ratio (HR) = 2.476, 95% Confidence Interval (CI) = 1.410-4.348, P = 0.002), MHR (HR = 3.803, 95%CI = 1.609-8.989, P = 0.002), CEA (HR = 1.977, 95%CI = 1.121-3.485, P = 0.019), and TNM stage (HR = 1.759, 95%CI = 1.010-3.063, P = 0.046) were independent prognostic indicators for overall survival (OS). A nomogram incorporating these variables was developed, demonstrating robust predictive accuracy for OS. The area under the curve (AUC) values of the predictive model for 1-, 2-, and 3- year are 0.791,0.768,0.811, respectively. The calibration curves for the probability of survival at 1-, 2-, and 3- year presented a high degree of credibility. Furthermore, Decision curve analysis (DCA) for the probability of survival at 1-, 2-, and 3- year demonstrate the significant clinical utility in predicting survival outcomes.
CONCLUSIONS: Preoperative PIV and MHR are independent risk factors for CRC prognosis. The novel developed nomogram demonstrates a robust predictive ability, offering substantial utility in facilitating the clinical decision-making process.
METHODS: A total of 172 patients with CRC who underwent radical resection were retrospectively analyzed. Survival analysis was conducted after patients were grouped according to the optimal cut-off values of PIV and MHR. Univariate and multivariate analyses were performed using Cox proportional hazards regression to screen the independent prognostic factors. Based on these factors, a nomogram was constructed and validated.
RESULTS: The PIV was significantly associated with tumor location (P < 0.001), tumor maximum diameter (P = 0.008), and T stage (P = 0.019). The MHR was closely related to gender (P = 0.016), tumor maximum diameter (P = 0.002), and T stage (P = 0.038). Multivariate analysis results showed that PIV (Hazard Ratio (HR) = 2.476, 95% Confidence Interval (CI) = 1.410-4.348, P = 0.002), MHR (HR = 3.803, 95%CI = 1.609-8.989, P = 0.002), CEA (HR = 1.977, 95%CI = 1.121-3.485, P = 0.019), and TNM stage (HR = 1.759, 95%CI = 1.010-3.063, P = 0.046) were independent prognostic indicators for overall survival (OS). A nomogram incorporating these variables was developed, demonstrating robust predictive accuracy for OS. The area under the curve (AUC) values of the predictive model for 1-, 2-, and 3- year are 0.791,0.768,0.811, respectively. The calibration curves for the probability of survival at 1-, 2-, and 3- year presented a high degree of credibility. Furthermore, Decision curve analysis (DCA) for the probability of survival at 1-, 2-, and 3- year demonstrate the significant clinical utility in predicting survival outcomes.
CONCLUSIONS: Preoperative PIV and MHR are independent risk factors for CRC prognosis. The novel developed nomogram demonstrates a robust predictive ability, offering substantial utility in facilitating the clinical decision-making process.
摘要：
目的:使用术前泛免疫-炎症值(PIV)和单核细胞与高密度脂蛋白比值(MHR)来反映炎症,豁免权,和胆固醇代谢，我们旨在开发并可视化一种新的列线图模型,用于预测结直肠癌(CRC)患者的生存结局.
方法：对172例接受根治性切除术的CRC患者进行回顾性分析。根据PIV和MHR的最佳临界值对患者进行分组后进行生存分析。使用Cox比例风险回归进行单变量和多变量分析以筛选独立的预后因素。基于这些因素,构建并验证了列线图.
结果：PIV与肿瘤位置显著相关（P<0.001），肿瘤最大直径（P=0.008），和T阶段(P=0.019)。MHR与性别密切相关(P=0.016),肿瘤最大直径（P=0.002），和T阶段(P=0.038)。多因素分析结果显示,PIV(危险比(HR)=2.476,95%置信区间(CI)=1.410-4.348,P=0.002),MHR（HR=3.803，95CI=1.609-8.989，P=0.002），CEA（HR=1.977，95CI=1.121-3.485，P=0.019），和TNM分期（HR=1.759，95CI=1.010-3.063，P=0.046）是总生存期（OS）的独立预后指标。开发了包含这些变量的列线图，证明了操作系统的强大预测准确性。预测模型的曲线下面积（AUC）值1-，2-,和3年分别为0.791,0.768,0.811。在1-，2-,和3年提出了很高的可信度。此外，在1-，2-,和3年证明了预测生存结果的重要临床效用。
结论：术前PIV和MHR是影响CRC预后的独立危险因素。新开发的列线图展示了强大的预测能力，在促进临床决策过程中提供了实质性的效用。
方法：对172例接受根治性切除术的CRC患者进行回顾性分析。根据PIV和MHR的最佳临界值对患者进行分组后进行生存分析。使用Cox比例风险回归进行单变量和多变量分析以筛选独立的预后因素。基于这些因素,构建并验证了列线图.
结果：PIV与肿瘤位置显著相关（P<0.001），肿瘤最大直径（P=0.008），和T阶段(P=0.019)。MHR与性别密切相关(P=0.016),肿瘤最大直径（P=0.002），和T阶段(P=0.038)。多因素分析结果显示,PIV(危险比(HR)=2.476,95%置信区间(CI)=1.410-4.348,P=0.002),MHR（HR=3.803，95CI=1.609-8.989，P=0.002），CEA（HR=1.977，95CI=1.121-3.485，P=0.019），和TNM分期（HR=1.759，95CI=1.010-3.063，P=0.046）是总生存期（OS）的独立预后指标。开发了包含这些变量的列线图，证明了操作系统的强大预测准确性。预测模型的曲线下面积（AUC）值1-，2-,和3年分别为0.791,0.768,0.811。在1-，2-,和3年提出了很高的可信度。此外，在1-，2-,和3年证明了预测生存结果的重要临床效用。
结论：术前PIV和MHR是影响CRC预后的独立危险因素。新开发的列线图展示了强大的预测能力，在促进临床决策过程中提供了实质性的效用。
