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

Li-Na He; Xuanye Zhang; Haifeng Li; Tao Chen; Chen Chen; Yixin Zhou; Zuan Lin; Wei Du; Wenfeng Fang; Yunpeng Yang; Yan Huang; Hongyun Zhao; Shaodong Hong; Li Zhang

doi:10.3389/fonc.2020.621329

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

Front Oncol. 2021 Jan 19:10:621329. doi: 10.3389/fonc.2020.621329. eCollection 2020.

Authors

Li-Na He^{1

2

3}, Xuanye Zhang^{1

2

3}, Haifeng Li^{1

2

3}, Tao Chen^{1

2

4}, Chen Chen^{1

2

5}, Yixin Zhou^{1

2

6}, Zuan Lin^{1

2

7}, Wei Du^{1

2

3}, Wenfeng Fang^{1

2

3}, Yunpeng Yang^{1

2

3}, Yan Huang^{1

2

3}, Hongyun Zhao^{1

2

7}, Shaodong Hong^{1

2

3}, Li Zhang^{1

2

3}

Affiliations

¹ State Key Laboratory of Oncology in South China, Guangzhou, China.
² Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
³ Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁴ Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁵ Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁶ Department of VIP Region, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁷ Department of Clinical Research, Sun Yat-sen University Cancer Center, Guangzhou, China.

Abstract

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.

Keywords: NSCLC; anti-PD-1/PD-L1 therapy; immunotherapy; non-small cell lung cancer; progression-free survival; tumor growth rate.