建立并验证一种甲胎蛋白肿瘤负担评分模型以预测肝癌患者复发后的生存情况。
Development and Validation of an α-Fetoprotein Tumor Burden Score Model to Predict Postrecurrence Survival among Patients with Hepatocellular Carcinoma.
机构信息
From the Department of Hepatobiliary Surgery and Institute of Advanced Surgical Technology and Engineering, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China (Ding, Lv, Zhang).
the Department of Hepatobiliary Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Medical University, Shanghai, China (Yang).
出版信息
J Am Coll Surg. 2023 May 1;236(5):982-992. doi: 10.1097/XCS.0000000000000638. Epub 2023 Feb 6.
BACKGROUND
The purpose of this study is to establish a prognostic model to predict postrecurrence survival (PRS) probability after initial resection of hepatocellular carcinoma (HCC).
STUDY DESIGN
Patients with recurrent HCC after curative resection were identified through a multicenter consortium (training cohort, TC); data were from a separate institution were used as validation cohort (VC). The α-fetoprotein (AFP) tumor burden score (ATS) was defined as the distance from the origin on a 3-dimensional Cartesian coordinate system that incorporated 3 variables: largest tumor diameter ( x axis), number of tumors ( y axis), and ln AFP ( z axis). ATS was calculated using the Pythagorean theorem: ATS 2 = (largest tumor diameter) 2 + (number of tumors) 2 + (ln AFP) 2 , where ATS d and ATS r represent ATS at the time of initial diagnosis and at the time of recurrence, respectively. The final model was ATS m = ATS d + 4 × ATS r . Predictive performance and discrimination of the ATS model were evaluated and compared with traditional staging systems.
RESULTS
The ATS model demonstrated strong predictive performance of PRS in both the TC (area under the curve [AUC] 0.70) and VC (AUC 0.71). An ATS-based nomogram was able to stratify patients accurately into low- and high-risk categories relative to PRS (TC: ATS m ≤ 27, 74.9 months vs. ATS m ≥ 28, 23.3 months; VC: ATS m ≤ 27, 59.4 months vs. ATS m ≥ 28, 15.1 months; both p < 0.001). The ATS model predicted PRS among patients undergoing curative or noncurative treatment of HCC recurrence (both p < 0.05). Of note, the ATS model outperformed the Barcelona Clinic Liver Cancer (BCLC), China Liver Cancer (CNLC), and American Joint Committee on Cancer (AJCC) staging systems relative to 1-, 2-, 3-, 4- and 5-year PRS (AUC 0.70, vs. BCLC, AUC 0.50, vs. CNLC, AUC 0.54, vs. AJCC, AUC 0.51).
CONCLUSIONS
The ATS model had excellent prognostic discriminatory power to stratify patients relative to PRS.
背景
本研究旨在建立一个预测肝癌（HCC）初始切除后复发后生存（PRS）概率的预后模型。
研究设计
通过一个多中心联盟（训练队列 TC）确定复发 HCC 患者；数据来自另一个机构作为验证队列（VC）。甲胎蛋白（AFP）肿瘤负担评分（ATS）定义为包含 3 个变量的三维笛卡尔坐标系原点的距离：最大肿瘤直径（x 轴）、肿瘤数量（y 轴）和 lnAFP（z 轴）。ATS 通过勾股定理计算：ATS 2 =（最大肿瘤直径）2 +（肿瘤数量）2 +（lnAFP）2，其中 ATS d 和 ATS r 分别代表初始诊断时和复发时的 ATS。最终模型为 ATS m = ATS d + 4 × ATS r。评估和比较了 ATS 模型的预测性能和区分度，并与传统分期系统进行了比较。
结果
ATS 模型在 TC（曲线下面积 [AUC] 0.70）和 VC（AUC 0.71）中均表现出对 PRS 的良好预测性能。基于 ATS 的列线图能够根据 PRS 准确地将患者分层为低风险和高风险类别（TC：ATS m ≤ 27，74.9 个月 vs. ATS m ≥ 28，23.3 个月；VC：ATS m ≤ 27，59.4 个月 vs. ATS m ≥ 28，15.1 个月；均 p < 0.001）。ATS 模型预测了 HCC 复发患者接受根治性或非根治性治疗的 PRS（均 p < 0.05）。值得注意的是，与巴塞罗那临床肝癌（BCLC）、中国肝癌（CNLC）和美国癌症联合委员会（AJCC）分期系统相比，ATS 模型在 1、2、3、4 和 5 年 PRS 方面表现更好（AUC 0.70，vs. BCLC，AUC 0.50，vs. CNLC，AUC 0.54，vs. AJCC，AUC 0.51）。
结论
ATS 模型具有出色的预后区分能力，可根据 PRS 对患者进行分层。
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