基于炎症反应综合指数(AISI)构建前列腺癌 根治术后生化复发的列线图预测模型

Nomogram Prediction Model of Biochemical Recurrence after Radical Prostatectomy Based on Aggregate Index of Systemic Inflammation (AISI)

摘要: 目的：探究影响前列腺癌根治术后生化复发的独立危险因素，评估炎症反应综合指数(AISI)等新型指标的预测价值并构建预测模型。方法：选取2019年1月至2022年12月于安徽医科大学第二附属医院泌尿外科确诊并接受腹腔镜下前列腺癌根治术的185例患者数据进行回顾性分析。根据术后是否发生生化复发分为两组。连续型变量采用t检验或Mann-Whitney U检验，分类变量采用卡方检验。使用Cox比例风险回归分析独立危险因素。基于筛选出的因素构建列线图，通过受试者工作特征(ROC)曲线和校准曲线来对预测模型的区分度、校准度进行评价。结果：多因素分析显示，术前高AISI (>264.625, HR = 1.90, P = 0.015)、手术切缘阳性(HR = 1.70, P = 0.050)、脉管癌栓阳性(HR = 1.97, P = 0.019)、淋巴结转移(HR = 1.96, P = 0.02)及Gleason评分 ≥ 8 (HR = 2.26, P = 0.041)是BCR的独立危险因素。基于上述因素构建的列线图模型，在预测术后1年、2年及3年无生化复发生存率时，ROC曲线下面积(AUC)分别为0.84、0.85和0.83。校准曲线显示预测概率与实际观测概率高度一致。临床决策曲线显示，该模型在临床常用风险阈值范围内净获益显著优于全干预与全不干预策略，具备良好的临床应用价值。结论：整合了系统性炎症指标AISI与传统病理特征的列线图模型，能有效预测前列腺癌患者根治术后的生化复发风险。为术后个体化风险分层及辅助治疗决策提供了新的参考工具。

Abstract: Objective: To explore the independent risk factors of biochemical recurrence after radical prostatectomy and evaluate the predictive value of new indicators such as systemic inflammatory response composite index (AISI). Methods: This study was a single center retrospective study, including 185 patients who were diagnosed and underwent laparoscopic radical prostatectomy in the Department of Urology, the Second Affiliated Hospital of Anhui Medical University from January 2019 to December 2022. They were divided into two groups according to whether biochemical recurrence occurred after surgery. T test or Mann Whitney U test was used for continuous variables, and chi square test was used for categorical variables. A nomogram was constructed based on the selected factors, and the discrimination and calibration of the prediction model were evaluated by receiver operating characteristic (ROC) curve and calibration curve. Results: multivariate analysis showed that high preoperative AISI (>264.625, HR = 1.90, P = 0.015), positive surgical margin (HR = 1.70, P = 0.050), positive vascular tumor thrombus (HR = 1.97, P = 0.019), lymph node metastasis (HR = 1.96, P = 0.02) and Gleason score ≥ 8 (HR = 2.26, P = 0.041) were independent risk factors for BCR. The area under the ROC curve (AUC) of the nomogram model based on the above factors was 0.84, 0.85 and 0.83, respectively, when predicting the 1-, 2- and 3-year biochemical recurrence free survival rate after surgery. The calibration curve shows that the predicted probability is highly consistent with the actual observed probability. DCA showed that the net benefit of this model within the range of commonly used clinical risk thresholds was significantly better than that of the full intervention and no intervention strategies, which had good clinical application value. Conclusion: The nomogram model, which integrates the systemic inflammatory index AISI and traditional pathological characteristics, can effectively predict the biochemical recurrence risk of prostate cancer patients after radical prostatectomy. It provides a new reference tool for postoperative individualized risk stratification and adjuvant treatment decision-making.