目的 探讨结直肠癌(CRC)患者术后血清神经营养因子-3(NT-3)、钙黏蛋白 3(CDH3)、丙酮酸脱氢酶 E1α 亚基 (PDHA1)的时序变化特征,并构建基于多指标动态监测的复发转移预测模型。 方法 采用前瞻性研究设计,选取 2021 年 6 月 至 2022 年 6 月于邢台市中心医院胃肠外科接受根治性手术的 108 例 CRC 患者作为研究对象。 分别于术前及术后 6、12、24、 36 个月采集血清样本,检测 NT-3、CDH3 和 PDHA1 水平。 随访截至 2025 年 6 月,记录复发及转移事件,构建预测模型。 结果 本研究通过对 108 例结直肠癌术后患者的动态监测发现,复发患者脉管侵犯率、神经侵犯率更高(P<0. 05),临床分期中,TNM Ⅲ期和淋巴结转移≥3 枚比例增加(P= 0. 008),且复发患者血清标志物水平高于无复发组:NT-3 术后 6 个月(25. 30 ng / ml 比 21. 70 ng / ml,P= 0. 018)、12 月(30. 50 ng / ml 比 20. 80 ng / ml,P= 0. 004),CDH3 术后 12 个月(22. 90 pg / ml 比 17. 50 pg / ml,P= 0. 010),PDHA1 术后 12 个月(11. 30 ng / L 比 8. 00 ng / L,P= 0. 003)。 单因素分析确定术后 NT-3、CDH3、PDHA1 水平及临床 分期为复发独立预测因子。 基于此构建随机生存森林模型预测效能优异(AUC = 0. 853) 显著优于传统 TNM 分期(AUC = 0. 671)和 Cox 比例风险回归模型(AUC= 0. 789),且临床实用性强。 结论 血清 NT-3、CDH3 及 PDHA1 的时序动态变化可作为 CRC 术后复发转移的有效预测指标。 联合多时间点检测构建的 RSF 模型能够显著提高预测准确性。

Objective To investigate the temporal changes in serum neurotrophin-3 NT-3 cadherin-3 CDH3 and pyruvate dehydrogenase E1α subunit PDHA1 after radical surgery in colorectal cancer CRC patients and to construct a dynamic multi-index prediction model for postoperative recurrence and metastasis. Method A prospective cohort of 108 CRC patients who underwent radical resection in the Department of Gastrointestinal Surgery from June 2021 to June 2022 was enrolled. Serum samples were collected preoperatively and at 6 12 24 and 36 months postoperatively. Follow-up ended in June 2025. Recurrence and metastasis events were recorded and prediction models were constructed. Result Dynamic monitoring of 108 postoperative CRC patients revealed that the recurrence group had higher rates of vascular invasion and perineural invasion P < 0. 05 a higher proportion of TNM stage Ⅲ and ≥ 3 lymph node metastases P = 0. 008 and elevated serum biomarker levels compared to the non-recurrence group NT-3 at 6 months 25. 30 ng / ml vs 21. 70 ng / ml P = 0. 018 and 12 months 30. 50 ng / ml vs 20. 80 ng / ml P = 0. 004 CDH3 at 12 months 22. 90 pg / ml vs 17. 50 pg / ml P = 0. 010 and PDHA1 at 12 months 11. 30 ng / L vs 8. 00 ng / L P = 0. 003 . Univariate analysis confirmed that postoperative NT - 3 CDH3 and PDHA1 levels and clinical stage were independent predictors of recurrence. The random survival forest model constructed based on these factors showed excellent predictive performance AUC = 0. 853 significantly outperforming the traditional TNM staging model AUC = 0. 671 and the Cox model AUC = 0. 789 with strong clinical utility. Conclusion The temporal dynamic changes in serum NT-3 CDH3 and PDHA1 can serve as effective predictive indicators for postoperative recurrence and metastasis in CRC. The RSF model incorporating multi - timepoint detection significantly improves predictive accuracy.