Endoscopic and Minimally Invasive Surgery Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Lung Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Cancer Med. 2024 May;13(10):e7225. doi: 10.1002/cam4.7225.
Various hematologic parameters have been proposed as prognostic factors in rectal cancer management, but data are conflicting and unclear. This study is designed to investigate the prognostic factor capability of preoperative hematologic parameters with postoperative morbidities and mortality in rectal cancer patients undergoing curative resection.
All 200 consecutive rectal cancer patients diagnosed at Ghaem University Hospital from 2017 to 2022 were retrospectively evaluated. The receiver operating characteristic (ROC) curves and machine learning (ML) algorithms of Random Forest, Recursive Feature Elimination, simulated annealing, Support Vector Machine, Decision Tree, and eXtreme Gradient Boosting were administered to investigate the role of preoperative hematologic parameters accompanied by baseline characteristics on three clinical outcomes including surgical infectious complications, recurrence, and death.
The frequency of infectious complications was correlated with the surgical procedure, while tumor recurrence was significantly influenced by T stage and N stage. In terms of mortality, alongside T and N stage, the status of resection margin involvement was significantly correlated. Based on the ROC analysis, the NLR >2.69, MPV ≤9 fL, and PDW ≤10.5 fL were more classified patients to mortality status. Likewise, the PLT >220 10/L, MPV ≤9 fL, PDW ≤10.4 fL, and PLR >13.6 were correlated with recurrence. However, all factors examined in this study were not significant classifiers for the outcome of surgical infectious complications. The results of ML algorithms were also in line with ROC analysis.
According to the results of both ROC analysis and ML models, preoperative hematologic parameters are considerable prognostic factors of postoperative outcomes in rectal cancer patients, and are recommended to be monitored by clinicians to prevent unfavorable outcomes.
各种血液学参数已被提出作为直肠癌管理的预后因素，但数据存在冲突且不明确。本研究旨在探讨术前血液学参数对接受根治性切除术的直肠癌患者术后并发症和死亡率的预后因素能力。
回顾性评估了 2017 年至 2022 年在 Ghaem 大学医院诊断的 200 例连续直肠癌患者。应用随机森林、递归特征消除、模拟退火、支持向量机、决策树和极端梯度提升的接收者操作特征（ROC）曲线和机器学习（ML）算法，探讨术前血液学参数与基线特征对包括手术感染性并发症、复发和死亡在内的三个临床结局的作用。
感染性并发症的发生频率与手术过程有关，而肿瘤复发则与 T 分期和 N 分期显著相关。就死亡率而言，除 T 分期和 N 分期外，手术切缘受累状态也与死亡率显著相关。基于 ROC 分析，NLR >2.69、MPV ≤9 fL 和 PDW ≤10.5 fL 更能将患者分类为死亡状态。同样，PLT >220 10/L、MPV ≤9 fL、PDW ≤10.4 fL 和 PLR >13.6 与复发相关。然而，本研究中检查的所有因素都不是手术感染性并发症结果的显著分类器。ML 算法的结果也与 ROC 分析一致。
根据 ROC 分析和 ML 模型的结果，术前血液学参数是直肠癌患者术后结局的重要预后因素，建议临床医生监测这些参数，以防止不良结局的发生。
