Novel risk scoring system for immune checkpoint inhibitors treatment in non-small cell lung cancer

Chuling Li; Meiqi Shi; Xinqing Lin; Yongchang Zhang; Shaorong Yu; Chengzhi Zhou; Nong Yang; Jianya Zhang; Fang Zhang; Tangfeng Lv; Hongbing Liu; Yong Song

doi:10.21037/tlcr-20-832

Novel risk scoring system for immune checkpoint inhibitors treatment in non-small cell lung cancer

Transl Lung Cancer Res. 2021 Feb;10(2):776-789. doi: 10.21037/tlcr-20-832.

Authors

Chuling Li¹, Meiqi Shi², Xinqing Lin³, Yongchang Zhang⁴, Shaorong Yu², Chengzhi Zhou³, Nong Yang⁴, Jianya Zhang⁵, Fang Zhang⁵, Tangfeng Lv⁵, Hongbing Liu⁵, Yong Song^{1

5}

Affiliations

¹ Department of Respiratory Medicine, Jinling Hospital, Nanjing Medical University, Nanjing, China.
² Department of Medical Oncology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China.
³ State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
⁴ Department of Medical Oncology, Lung Cancer and Gastrointestinal Unit, Hunan Cancer Hospital/The affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
⁵ Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.

Abstract

Background: Immune checkpoint inhibitor (ICI)-based immunotherapy has improved the clinical outcome of non-small cell lung cancer (NSCLC). However, current indicators, such as programmed cell death-ligand 1 (PD-L1) expression in tumors or tumor mutational burden (TMB), are not considered ideal biomarkers for prognosis. Thus, there is an urgent requirement for a comprehensive risk scoring system.

Methods: In this study, we enrolled 464 NSCLC patients who received ICIs between March 2017 and January 2020 at four clinical centers. Univariate and multivariate (the logistic and the Cox regression) analyses were conducted to screen clinically relevant variables. Significant parameters (P<0.05) including absolute lymphocyte count (ALC, L), Eastern Cooperative Oncology Group Performance Status (ECOG PS, E) and lung/pleural metastasis (M) were selected for LEM score. Weighted values based on odds ratio and hazard ratio of multiple analyses were assigned to each parameter. LEM score was the sum of weighted values of each variable (Good, 0-1; Intermediate, 2-3; Poor, 4-6). Kaplan-Meier curves were used to evaluate the association between LEM score and progression-free survival (PFS).

Results: In total, 258 patients were pooled and stratified into three risk categories based on the LEM score. Objective response rate (ORR) was significantly higher in the good-risk group compared with the poor-risk group [55.9% vs. 7.3%, odds ratio (OR), 0.023; 95% confidence interval (CI), 0.005-0.099; P<0.001]. Patients with good risk [hazard ratio (HR), 0.130; 95% CI, 0.084-0.203; median PFS, 12.5 months; P<0.001] or intermediate risk (HR, 0.330; 95% CI, 0.222-0.490; median PFS, 4.2 months; P<0.001) had longer PFS than those with poor risk (median PFS, 2.1 months). DNA sequencing was performed in 41 patients [no durable benefit (NDB): n=29; durable clinical benefit (DCB): n=12] and epidermal growth factor receptor (EGFR) mutations were enriched in samples of the NDB group vs. the DCB group (11/29 vs. 1/12; Fisher's exact P=0.073; OR, 6.722; 95% CI, 0.760-59.479). Additionally, patients with EGFR mutations had higher LEM scores than those with wild-type EGFR.

Conclusions: In conclusion, the LEM score provided a potential prognostic biomarker for NSCLC patients treated with ICIs.

Keywords: LEM; Non-small cell lung cancer (NSCLC); immune checkpoint inhibitors (ICIs); prognostic biomarker; risk scoring system.