Liu Chang-Qing, Yu Zhong-Bei, Gan Jin-Xian, Mei Tian-Ming
Department of Gastrointestinal Anorectal Surgery, Suzhou Hospital Affiliated to Anhui Medical University, Suzhou 234000, Anhui Province, China.
World J Gastrointest Surg. 2024 Feb 27;16(2):451-462. doi: 10.4240/wjgs.v16.i2.451.
Colorectal cancer (CRC) has one of the highest morbidity and mortality rates among digestive tract tumors. Intra-abdominal infection (IAI) is a common postoperative complication that affects the clinical outcomes of patients with CRC and hinders their rehabilitation process. However, the factors influencing abdominal infection after CRC surgery remain unclear; further, prediction models are rarely used to analyze preoperative laboratory indicators and postoperative complications.
To explore the predictive value of preoperative blood markers for IAI after radical resection of CRC.
The data of 80 patients who underwent radical resection of CRC in the Anorectal Surgery Department of Suzhou Hospital affiliated with Anhui Medical University were analyzed. These patients were categorized into IAI ( = 15) and non-IAI groups ( = 65) based on whether IAI occurred. Influencing factors were compared; general data and laboratory indices of both groups were identified. The relationship between the indicators was assessed. Further, a nomogram prediction model was developed and evaluated; its utility and clinical applicability were assessed.
The risk factors for IAI after radical resection of CRC were neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and carcinoembryonic antigen (CEA) levels. NLR was correlated with PLR and SII ( = 0.604, 0.925, and 0.305, respectively), while PLR was correlated with SII ( = 0.787). The nomogram prediction model demonstrated an area under the curve of 0.968 [95% confidence interval (CI): 0.948-0.988] in the training set ( = 60) and 0.926 (95%CI: 0.906-0.980) in the validation set ( = 20). The average absolute errors of the calibration curves for the training and validation sets were 0.032 and 0.048, respectively, indicating a good model fit. The decision curve analysis curves demonstrated high net income above the 5% threshold, indicating the clinical practicality of the model.
The nomogram model constructed using NLR, PLR, SII, and CEA levels had good accuracy and reliability in predicting IAI after radical resection of CRC, potentially aiding clinical treatment decision-making.
结直肠癌（CRC）是消化道肿瘤中发病率和死亡率最高的肿瘤之一。腹腔内感染（IAI）是一种常见的术后并发症，会影响CRC患者的临床结局并阻碍其康复进程。然而，影响CRC手术后腹腔感染的因素仍不清楚；此外，预测模型很少用于分析术前实验室指标和术后并发症。
探讨术前血液标志物对CRC根治性切除术后IAI的预测价值。
分析安徽医科大学附属苏州医院肛肠外科80例行CRC根治性切除术患者的数据。根据是否发生IAI将这些患者分为IAI组（n = 15）和非IAI组（n = 65）。比较影响因素；确定两组的一般数据和实验室指标。评估指标之间的关系。此外，开发并评估了列线图预测模型；评估其效用和临床适用性。
CRC根治性切除术后IAI的危险因素为中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、全身免疫炎症指数（SII）和癌胚抗原（CEA）水平。NLR与PLR和SII相关（分别为r = 0.604、0.925和0.305），而PLR与SII相关（r = 0.787）。列线图预测模型在训练集（n = 60）中的曲线下面积为0.968 [95%置信区间（CI）：0.948 - 0.988]，在验证集（n = 20）中的曲线下面积为0.926（95%CI：0.906 - 0.980）。训练集和验证集校准曲线的平均绝对误差分别为0.032和0.048，表明模型拟合良好。决策曲线分析曲线在5%阈值以上显示出较高的净收益，表明该模型具有临床实用性。
使用NLR、PLR、SII和CEA水平构建的列线图模型在预测CRC根治性切除术后IAI方面具有良好的准确性和可靠性，可能有助于临床治疗决策。
