Wang Xueping, Guo Zhixing, Wu Xingping, Chen Da, Wang Fang, Yang Lewei, Luo Min, Wu Shaocong, Yang Chuan, Huang Lamei, Fu Liwu
State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Esophageal Cancer Institute; Cancer Center, Sun Yat-sen University, Guangzhou, 510060, People's Republic of China.
Immunotargets Ther. 2023 Jan 4;12:1-16. doi: 10.2147/ITT.S373866. eCollection 2023.
Various studies have reported that anti-PD-1/PD-L1 treatment may lead to the rapid development of tumors called hyperprogressive disease (HPD). A nomogram for HPD prediction in NSCLC patients is urgently needed.
This retrospective cohort study included 176 cases for establishing a model of HPD prediction and 85 cases for validation in advanced NSCLC patients treated with PD-1/PD-L1 inhibitors. HPD was defined as tumor growth rate (TGR, ≥ 2), tumor growth kinetics (TGK, ≥ 2) or time to treatment failure (TTF, ≤ 2 months). Univariate and multivariate logistic regression were used to estimate the specified factors associated with HPD. Then, the nomogram was developed and validated.
Anti-PD-1/PD-L1 therapy resulted in a 9.66% (17/176) incidence of HPD in advanced NSCLC. The overall survival (OS) and progression-free survival (PFS) in patients with HPD were significantly shorter than those in patients without HPD (OS: 7.00 vs 12.00 months, P<0.01; PFS: 2.00 vs 5.00 months, P<0.001, respectively). The HPD prediction nomogram included APTT (P<0.01), CD4+ CD25+ CD127-low cells (Treg cells) (P<0.01), the presence of liver metastasis (P<0.05), and more than two metastatic sites (P<0.05). Then, patients were divided into two groups by the "HPD score" calculated by the nomogram. The C-index was 0.845, while the area under the curve (AUC) was 0.830 (sensitivity 75.00%, specificity 91.70%). The calibration plot of HPD probability showed an optimal agreement between the actual observation and prediction by the nomogram. In the validation cohort, the AUC was up to 0.960 (sensitivity 88.70%, specificity 89.80%).
The nomogram was constructed with the presence of liver metastasis, more than two metastatic sites, lengthened APTT and a high level of Treg cells, which could be used to predict HPD risk.
多项研究报告称，抗程序性死亡蛋白1（PD-1）/程序性死亡配体1（PD-L1）治疗可能导致肿瘤快速进展，即所谓的高进展性疾病（HPD）。目前迫切需要一种用于预测非小细胞肺癌（NSCLC）患者发生HPD的列线图。
这项回顾性队列研究纳入了176例患者用于建立HPD预测模型，85例患者用于在接受PD-1/PD-L1抑制剂治疗的晚期NSCLC患者中进行验证。HPD定义为肿瘤生长率（TGR，≥2）、肿瘤生长动力学（TGK，≥2）或至治疗失败时间（TTF，≤2个月）。采用单因素和多因素逻辑回归分析来评估与HPD相关的特定因素。然后，构建并验证列线图。
抗PD-1/PD-L1治疗导致晚期NSCLC患者中HPD的发生率为9.66%（17/176）。发生HPD的患者的总生存期（OS）和无进展生存期（PFS）显著短于未发生HPD的患者（OS：7.00个月对12.00个月，P<0.01；PFS：2.00个月对5.00个月，P<0.001）。HPD预测列线图包括活化部分凝血活酶时间（APTT）（P<0.01）、CD4+CD25+CD127低表达细胞（调节性T细胞，Treg细胞）（P<0.01）、肝转移的存在（P<0.05）以及两个以上转移部位（P<0.05）。然后，根据列线图计算的“HPD评分”将患者分为两组。一致性指数（C指数）为0.845，而曲线下面积（AUC）为0.830（敏感性75.00%，特异性91.70%）。HPD概率的校准图显示实际观察结果与列线图预测之间具有最佳一致性。在验证队列中，AUC高达0.960（敏感性88.70%，特异性89.80%）。
该列线图基于肝转移的存在、两个以上转移部位、延长的APTT以及高水平的Treg细胞构建而成，可用于预测HPD风险。
