Li Xiangyong, Zhou Zeyang, Zhou Chenxi, Xiong Mengya, Xing Chungen, Wu Yong
Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.
Operating Room, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.
J Inflamm Res. 2024 Dec 17;17:11161-11174. doi: 10.2147/JIR.S500900. eCollection 2024.
Preoperative albumin to alkaline phosphatase ratio (AAPR) and inflammatory burden index (IBI) are prognostic indicators for a multitude of cancers, and our study focuses on evaluating the prognostic significance of the AAPR and the IBI on rectal cancer (RC) patients to provide a more accurate guideline for patient prognosis.
This study enrolled patients who underwent laparoscopic rectal cancer surgery from January 2016 to January 2021. We utilized three machine learning approaches to select variables most relevant to prognosis in the training cohort. Finally, based on the screened variables, a nomogram was established to predict RC patients' overall survival (OS). The improvement in predictive ability and clinical benefit was assessed through the concordance index (C-index), receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA).
A total of 356 patients were enrolled and they were randomly divided into a training cohort (60%, n=214) and a validation cohort (40%, n=143). Overall survival (OS) was worse for patients in either the low AAPR or the high AAPR group, whereas patients in the low AAPR with both high IBI group had the lowest OS (P<0.001). Finally, five variables were obtained after screening the best variables by three machine learning, and the nomogram was constructed. In both the development and validation cohorts, the C-index values exceeded 0.85, indicating that the predictive model has a strong predictive performance in terms of overall survival. The calibration curves and the decision curve analysis (DCA) showed that the nomogram demonstrated a superior benefit.
Preoperative AAPR and IBI can serve as effective indicators for predicting the OS of RC patients. We have developed a nomogram for predicting the OS of patients who underwent laparoscopic rectal cancer surgery.
术前白蛋白与碱性磷酸酶比值（AAPR）和炎症负荷指数（IBI）是多种癌症的预后指标，本研究旨在评估AAPR和IBI对直肠癌（RC）患者的预后意义，为患者预后提供更准确的指导。
本研究纳入了2016年1月至2021年1月接受腹腔镜直肠癌手术的患者。我们采用三种机器学习方法在训练队列中选择与预后最相关的变量。最后，基于筛选出的变量，建立了一个列线图来预测RC患者的总生存期（OS）。通过一致性指数（C指数）、受试者工作特征曲线（ROC）、校准曲线和决策曲线分析（DCA）评估预测能力和临床获益的改善情况。
共纳入356例患者，随机分为训练队列（60%，n = 214）和验证队列（40%，n = 143）。低AAPR组或高AAPR组患者的总生存期（OS）均较差，而低AAPR且高IBI组患者的OS最低（P < 0.001）。最后，通过三种机器学习筛选出最佳变量后获得了五个变量，并构建了列线图。在开发队列和验证队列中，C指数值均超过0.85，表明该预测模型在总生存期方面具有很强的预测性能。校准曲线和决策曲线分析（DCA）表明列线图显示出更好的获益。
术前AAPR和IBI可作为预测RC患者OS的有效指标。我们开发了一种列线图来预测接受腹腔镜直肠癌手术患者的OS。
