Neoadjuvant camrelizumab, nab-paclitaxel, and carboplatin in patients with stage IB-IIIA non-small cell lung cancer (NANE-LC): a study protocol of prospective, single-arm, multicenter, phase II study

Abstract

Background: Previous studies have shown that neoadjuvant immune checkpoint inhibitors (ICIs) combined with chemotherapy in patients with stage IB-IIIA non-small cell lung cancer (NSCLC) significantly improved the major pathological response (MPR) and the pathological complete response (pCR) rates. However, high-level evidence-based medical data confirming this effect are still lacking. In addition, there is an urgent need to develop an appropriate strategy to predict the benefit for patients receiving ICIs. In this study, we describe an ongoing study on the effect of neoadjuvant therapy with camrelizumab, nab-paclitaxel, and carboplatin on stage IB-IIIA NSCLC patients. The aim of this study is to establish a multiomics artificial intelligence system for predicting neoadjuvant therapy efficacy and assisting decision-making.

Methods: This prospective, single-arm, multicenter, phase II trial will enroll a total of 40 patients who will undergo surgery after three cycles of neoadjuvant therapy with camrelizumab, nab-paclitaxel, and carboplatin. The MPR rate is the primary endpoint, while the rates of pCR, complete resection, objective response, disease-free survival (DFS), adverse events (AEs), and quality of life (QOL) are secondary endpoints. Exploratory endpoints will serve to establish a multiomics artificial intelligence system for neoadjuvant therapy effect prediction and decision-making assistance based on radiomics, metabolism, genetic, and clinic-pathological characteristics and to explore the mechanisms of drug resistance.

Discussion: The efficacy of ICIs is influenced by many factors, including patient's driver genes and smoking status. Thus, further subgroup analysis is needed. This study will indicate if our new multiomics artificial intelligence system constitutes a valid strategy for neoadjuvant therapy effect prediction and decision-making assistance in the context of neoadjuvant camrelizumab, nab-paclitaxel, and carboplatin treatment for patients with stage IB-IIIA NSCLC.

Trial registration: This trial has been registered at ClinicalTrials.gov (identification number: NCT04541251).

Keywords: Neoadjuvant therapy; artificial intelligence; checkpoint inhibitors; immune; major pathological response; non-small cell lung cancer (NSCLC).

Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jtd-21-1022). The authors have no conflicts of interest to declare.

2021 Journal of Thoracic Disease. All rights reserved.

Figures

Figure 1

Flowchart of the trial. AUC, area under the curve; CT, computed tomography.

Figure 2

Key inclusion and exclusion criteria. NSCLC, non-small cell lung cancer; ECOG PS, Eastern Cooperative Oncology Group performance status; HIV, human immunodeficiency virus; HBV, hepatitis B virus; HCV, hepatitis C virus.

Figure 3

Detailed description of the artificial intelligence prediction system used to assess neoadjuvant-based therapy efficacy. MPR, major pathologic response; CT, computed tomography; WES, whole genome sequencing; WTS, whole transcriptome resequencing; TCR, T cell receptor.