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

Disclosures

Transl Lung Cancer Res. 2021;10(2):776-789. 

In This Article

Abstract and Introduction

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.

Introduction

In the past decade, immune checkpoint inhibitors (ICIs) have dramatically altered the management of non-small-cell lung cancer (NSCLC).[1–3] Consequently, programmed cell death-1 (PD-1) inhibitors have proven more effective than conventional chemotherapy for the treatment of metastatic NSCLC.[3–6] Additionally, the combination of PD-1 inhibitors and chemotherapy has also resulted in improved outcomes of NSCLC.[7,8]

Despite the advances in ICIs therapy, some patients do not respond to ICIs. Some of the diagnostic tests performed for ICIs include Programmed cell death ligand-1 (PD-L1) immunohistochemistry (IHC) and tumor mutational burden (TMB); however, these have proven to be imperfect biomarkers. Studies have shown that several patients without PD-L1 expression did respond to ICIs, while those with PD-L1 expression did not.[3,9] TMB is another potential indicator, which represents the number of somatic mutations detected by DNA sequencing.[10] The lack of uniform methodology limits its widespread application. Therefore, there is an urgent need to develop a robust and reproducible scoring system to predict ICIs' response.

Several studies have tried to predict ICIs' response using various parameters, such as clinical features [e.g., metastatic site,[11] computational image-based features,[12,13]], laboratory parameters [e.g., neutrophil-to-lymphocyte ratio (NLR),[14–16] lactate dehydrogenase (LDH),[17] tumor markers[18]], and genetic landscape.[19,20] Most of these parameters have yielded a poor performance due to lack of comprehensive evaluation in risk stratification. Recent studies have shown that the anti-tumor response to ICIs is a complicated process involving several factors. Previous studies have developed various prognostic models for prognostic evaluation in ICIs therapy. For example, a lung immune prognostic index (LIPI) combining derived NLR (dNLR) and LDH,[21] as well as a risk scoring criteria including monocyte-to-lymphocyte ratio (MLR), sites of metastasis, and nutritional index-body mass index (BMI)[22] were respectively developed for NSCLC and metastatic renal cell cancer (mRCC) patients treated with ICIs.

Thus, we generated a novel risk scoring system for ICIs treatment in NSCLC. This index was labeled "LEM" and included absolute lymphocyte count (ALC) <1.5×109/L, Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≥2, and lung/pleura metastasis. Patients who received PD-1 inhibitors were stratified into three risk stratifications (good, intermediate, and poor) based on the LEM score. Here, we developed this scoring system to explore the association between LEM score and clinical outcome.

We present the following article in accordance with the TRIPOD reporting checklist (available at http://dx.doi.org/10.21037/tlcr-20-832).

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