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

Methods

Patient selection

This study retrospectively screened 464 metastatic NSCLC patients who had been treated with PD-1 inhibitors [pembrolizumab (Merck Sharp & Dohme), nivolumab (Bristol-Myers Squibb), sintilimab (Innovent), or toripalimab (Topalliance)] between March 2017 and January 2020 at four clinical centers. We excluded the patients who received initial PD-1 immunotherapy at out hospital but was lost-to-follow-up thereafter (n=110) and those who do not receive sufficient sessions for evaluation at the time of study (n=79). The final analysis included 258 patients. Data from Jingling Hospital (n=87) were used to develop the risk scoring system, and the remaining data were used for validation (Figure S1).

Prior to treatment, we obtained clinical information and routine laboratory test records. Laboratory tests included blood platelet count, lymphocyte count, neutrophil count, NLR, levels of albumin, globulin, LDH and albumin to globulin ratio (A/G). Clinical data included demographic information, ECOG PS, TNM stage, metastatic site, and the number of prior therapies. PD-L1 (Dako 22C3) IHC staining was performed at the pathology department of each center. Response and progression were evaluated based on the RECIST v1.1 criterion.[23] Patients were stratified as a durable clinical benefit (DCB: partial or stable response lasting >6 months) and no durable benefit (NDB) groups based on the published metrics.[19,24] The primary endpoint was progression-free survival (PFS) (time from initial ICIs administration to confirmed progressive disease radiologically or death due to any cause). We also measured other objectives including treatment efficacy (DCB/NDB), objective response rate (ORR) and one-year overall survival (OS) (time from initial ICIs administration to death due to any cause) rate.

Sintilimab and toripalimab are both domestic PD-1 inhibitors which have not yet been approved by FDA for NSCLC treatment. In the study, patients who received sintilimab or toripalimab were undergoing approved clinical trials. All procedures performed in this study were in accordance with the Declaration of Helsinki (as revised in 2013) and approved by the local ethics committee of Jinling Hospital (registration ID. 2017NZHX-022). Informed consent from individuals was waived based on the retrospective nature of this study.

DNA Sequencing and Data Sources

Tumor tissue and corresponding blood samples (n=41) collected from Jinling Hospital were sent to a gene company for DNA extraction and sequencing. DNA was extracted from the blood samples, and formalin-fixed paraffin embedded (FFPE) slices were prepared. Deep sequencing (139 genes, 10,000×) based on Illumina Hiseq2000 system platform (Illumina, USA) was used to detect gene alterations, such as missense mutation, insertion, deletion, copy number variation, etc. TMB was expressed as the number of non-synonymous mutations.

To further explore the genetic factors that influenced the clinical efficacy of ICIs, we compared the gene expression data with Helmann[19] (MSK, Cancer Cell 2018) (n=75) and Rizvi[25] (MSKCC, J Clin Oncol 2018) (n=240). The genomic information of NSCLC cohorts treated with ICIs was shared in the cBioPortal (www.cbioportal.org).

Statistical Analysis

The Mann-Whitney U test was used for univariate analyses. The logistic regression model and the Cox regression model were used to evaluate the association between characteristics and best response/PFS. After multivariate analyses, factors of statistical significance were included in the risk scoring system, and the weight values of all indices were determined based on the odds ratio (OR) for response and hazard ratio (HR) for PFS. Survival estimates were generated by Kaplan-Meier analysis, and the log-rank test was used to compare the differences in PFS among subgroups. Statistical analysis was done using the SPSS software (v22.0, SPSS, Inc., Chicago) and expressed using GraphPad Prism 5 and R 3.3.2 software. A two-sided P<0.05 was considered statistically significant.

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