Nanchang University, Nanchang, Jiangxi, China (mainland).
Department of Digestive Endoscopy, Jiangxi Cancer Hospital, Nanchang, Jiangxi, China (mainland).
Med Sci Monit. 2022 Aug 10;28:e936745. doi: 10.12659/MSM.936745.
BACKGROUND This retrospective study from a single center in China was conducted using data from medical records between 2012 and 2020, to identify hematological factors that distinguish between patients with colorectal carcinoma (CRC) and colorectal adenoma. MATERIAL AND METHODS In this case-control study, 856 eligible patients were randomly divided into a training set (n=600) and a testing set (n=256). Routine blood parameters, blood coagulation, and liver and kidney function parameters were collected. Univariate and multivariate Cox regression analyses were used to explore diagnostic indicators. The values of the area under the curve and calibration curves were used to evaluate the model. RESULTS The study included 325 colorectal adenoma and 531 CRC patients. The prediction model for diagnosing CRC using hemoglobin-to-platelet ratio, fibrinogen-albumin ratio (FAR), albumin-globulin ratio (A/G), platelet-lymphocyte ratio, carcinoembryonic antigen (CEA), and thrombin time (TT) was developed on the basis of the patients grouped into the CRC and colorectal adenoma groups. The prediction model for diagnosing CRC stage was developed using prothrombin time (PT), TT, CEA, A/G, FAR, and HPR. The prediction model for diagnosing CRC grade was developed using PT, TT, A/G, plateletcrit, FAR, and HPR. The AUCs of the 3 prediction models were [0.848, 95% CI: (0.800-0.896)], [0.806, 95% CI: (0.775-0.836)], and [0.829, 95% CI: (0.797-0.860)] in the testing set. CONCLUSIONS Three diagnostic prediction models for early screening of CRC, stage of CRC, and grade of CRC were established through a panel of readily available hematological parameters, which could provide auxiliary tools for early screening of CRC.
本研究回顾性分析了 2012 年至 2020 年中国某单中心的病历资料,旨在确定区分结直肠癌(CRC)和结直肠腺瘤患者的血液学因素。
在这项病例对照研究中,856 名合格患者被随机分为训练集(n=600)和测试集(n=256)。收集了常规血液参数、凝血和肝肾功能参数。采用单因素和多因素 Cox 回归分析探讨诊断指标。采用曲线下面积和校准曲线的值来评估模型。
本研究纳入了 325 例结直肠腺瘤和 531 例 CRC 患者。根据将患者分为 CRC 和结直肠腺瘤组的血红蛋白/血小板比、纤维蛋白原/白蛋白比(FAR)、白蛋白/球蛋白比(A/G)、血小板/淋巴细胞比、癌胚抗原(CEA)和凝血酶时间(TT)建立了诊断 CRC 的预测模型。基于凝血酶原时间(PT)、TT、CEA、A/G、FAR 和 HPR 建立了诊断 CRC 分期的预测模型。基于 PT、TT、A/G、血小板比容、FAR 和 HPR 建立了诊断 CRC 分级的预测模型。这 3 个预测模型在测试集中的 AUC 值分别为 [0.848,95%CI:(0.800-0.896)]、[0.806,95%CI:(0.775-0.836)]和[0.829,95%CI:(0.797-0.860)]。
通过一组易于获得的血液学参数建立了用于早期筛查 CRC、CRC 分期和 CRC 分级的三个诊断预测模型,可为 CRC 的早期筛查提供辅助工具。