DataSheet_1_Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy.pdf

Tumor growth rate (TGR; percent size change per month [%/m]) is postulated as an early radio-graphic predictor of response to anti-cancer treatment to overcome limitations of RECIST. We aimed to evaluate the predictive value of pre-treatment TGR (TGR0) for outcomes of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1/PD-L1 monotherapy. We retrospectively screened all aNSCLC patients who received PD-1 axis inhibitors in Sun Yat-Sen University Cancer Center between August 2016 and June 2018. TGR0 was calculated as the percentage change in tumor size per month (%/m) derived from two computed tomography (CT) scans during a “wash-out” period before the initiation of PD-1 axis inhibition. Final follow-up date was August 28, 2019. The X-tile program was used to identify the cut-off value of TGR0 based on maximum progression-free survival (PFS) stratification. Patients were divided into two groups per the selected TGR0 cut-off. The primary outcome was the difference of PFS between the two groups. The Kaplan-Meier methods and Cox regression models were performed for survival analysis. A total of 80 eligible patients were included (54 [67.5%] male; median [range] age, 55 [30-74] years). Median (range) TGR0 was 21.1 (-33.7-246.0)%/m. The optimal cut-off value of TGR0 was 25.3%/m. Patients with high TGR0 had shorter median PFS (1.8 months; 95% CI, 1.6 - 2.1 months) than those with low TGR0 (2.7 months; 95% CI, 0.5 - 4.9 months) (P = 0.005). Multivariate Cox regression analysis revealed that higher TGR0 independently predicted inferior PFS (hazard ratio [HR] 1.97; 95% CI, 1.08-3.60; P = 0.026). Higher TGR0 was also significantly associated with less durable clinical benefit rate (34.8% vs. 8.8%, P = 0.007). High pre-treatment TGR was a reliable predictor of inferior PFS and clinical benefit in aNSCLC patients undergoing anti-PD-1/PD-L1 monotherapy. The findings highlight the role of TGR0 as an early biomarker to predict benefit from immunotherapy and could allow tailoring patient’s follow-up.

肿瘤生长率（Tumor growth rate, TGR；即每月肿瘤大小变化百分比[%/月]）被假设为一种早期影像学预测指标，用于评估抗肿瘤治疗的响应情况，以克服实体瘤疗效评价标准（Response Evaluation Criteria in Solid Tumors, RECIST）的局限性。本研究旨在评估治疗前肿瘤生长率（TGR0）对于接受抗PD-1/PD-L1单药治疗的晚期非小细胞肺癌（advanced non-small cell lung cancer, aNSCLC）患者预后的预测价值。我们回顾性筛选了2016年8月至2018年6月期间在中山大学肿瘤防治中心接受PD-1通路抑制剂治疗的所有aNSCLC患者。TGR0的计算基于PD-1通路抑制剂治疗开始前的「洗脱期」内的两次计算机断层扫描（computed tomography, CT）结果，以每月肿瘤大小变化百分比（%/月）进行计算。最终随访日期为2019年8月28日。本研究采用X-tile软件，基于最大无进展生存期（progression-free survival, PFS）分层来确定TGR0的截断值。根据所选的TGR0截断值，将患者分为两组。本研究的主要结局为两组患者的PFS差异。采用Kaplan-Meier法与Cox回归模型进行生存分析。本研究共纳入80例符合入组标准的患者，其中男性54例（占比67.5%）；患者年龄的中位数[范围]为55岁[30~74岁]。TGR0的中位数[范围]为21.1%/月[-33.7~246.0%/月]。TGR0的最优截断值为25.3%/月。与TGR0较低的患者相比，TGR0较高的患者中位PFS更短（1.8个月；95%置信区间[CI]：1.6~2.1个月），而TGR0较低的患者中位PFS为2.7个月（95%CI：0.5~4.9个月）（P=0.005）。多变量Cox回归分析显示，较高的TGR0可独立预测较差的PFS（风险比[hazard ratio, HR]=1.97；95%CI：1.08~3.60；P=0.026）。较高的TGR0同时与更低的临床获益率显著相关（34.8% vs. 8.8%，P=0.007）。治疗前较高的TGR0可可靠预测接受抗PD-1/PD-L1单药治疗的aNSCLC患者的较差PFS与临床获益。本研究结果凸显了TGR0作为早期生物标志物的作用，可用于预测免疫治疗获益，并有助于实现患者的个体化随访管理。