基于动态临床病理指标的模型预测结直肠癌患者围手术期预后
Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer.
作者信息
Ma Yifei, Lu Ping, Liang Xinjun, Wei Shaozhong
机构信息
Department of Gastrointestinal Oncology Surgery, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Department of Abdominal Oncology, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
出版信息
J Inflamm Res. 2021 Apr 21;14:1591-1601. doi: 10.2147/JIR.S302435. eCollection 2021.
BACKGROUND
Recent studies have found that clinicopathological indices, such as inflammatory and biochemical indices, play a significant role in the prognosis of colorectal cancer (CRC) patients. However, few studies have focused on the effect of dynamic changes in these indicators. In our study, we studied the influence of dynamic changes in inflammatory and biochemical indices on patient outcomes during the perioperative period.
METHODS
We enrolled 551 patients from Hubei Cancer Hospital who had undergone radical resection of CRC and collected the results of laboratory examinations performed within 1 week before surgery and at the first admission after surgery. The whole population was randomly divided into the training (386) and testing (185) cohorts. We used postoperative inflammatory and biochemical indices/preoperative inflammatory and biochemical indices (ΔX) to reflect the dynamic changes. Chi-square tests, Kaplan-Meier survival analyses, and univariate and multivariate Cox regression analyses were used to evaluate the prognosis. The prediction accuracies of models for overall survival (OS) and disease-free survival (DFS) were estimated through Harrell's concordance index (the C-index) and Brier scores. Nomograms of the prognostic models were plotted for evaluations of individualized outcomes.
RESULTS
The median follow-up time of the 551 patients was 35.6 (range: 1.1-73.8) months. Ultimately, the prognostic models based on age, sex, TNM stage, pathological conditions, inflammatory and biochemical indices, CEA, and CA199 were found to have exceptional performance for OS and DFS. The C-index of the nomogram for OS was 0.806 (95% CI, 0.75-0.86) in the training cohort and 0.921 (95% CI, 0.87-0.96) in the testing cohort. The C-index of the nomogram for DFS was 0.781 (95% CI, 0.74-0.82) in the training cohort and 0.835 (95% CI, 0.78-0.88) in the testing cohort.
CONCLUSION
We successfully established a novel model based on inflammatory and biochemical indices to guide clinical decision-making for CRC.
背景
近期研究发现，临床病理指标，如炎症和生化指标，在结直肠癌（CRC）患者的预后中起着重要作用。然而，很少有研究关注这些指标的动态变化的影响。在我们的研究中，我们研究了炎症和生化指标的动态变化对围手术期患者预后的影响。
方法
我们纳入了551例在湖北省肿瘤医院接受CRC根治性切除术的患者，并收集了手术前1周内及术后首次入院时的实验室检查结果。将全部人群随机分为训练组（386例）和测试组（185例）。我们用术后炎症和生化指标/术前炎症和生化指标（ΔX）来反映动态变化。采用卡方检验、Kaplan-Meier生存分析以及单因素和多因素Cox回归分析来评估预后。通过Harrell一致性指数（C指数）和Brier评分估计总生存（OS）和无病生存（DFS）模型的预测准确性。绘制预后模型的列线图以评估个体化结局。
结果
551例患者的中位随访时间为35.6（范围：1.1 - 73.8）个月。最终，发现基于年龄、性别、TNM分期、病理状况、炎症和生化指标、癌胚抗原（CEA）和糖类抗原199（CA199）的预后模型在OS和DFS方面具有出色的表现。训练组中OS列线图的C指数为0.806（95%CI，0.75 - 0.86），测试组中为0.921（95%CI，0.87 - 0.96）。训练组中DFS列线图的C指数为0.781（95%CI，0.74 - 0.82），测试组中为0.835（95%CI，0.78 - 0.88）。
结论
我们成功建立了一种基于炎症和生化指标的新型模型，以指导CRC的临床决策。
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