Exploring clinical factors to predict the survival for resectable non-small cell lung cancer patients with neoadjuvant immunotherapy

Abstract OBJECTIVES To explore clinical factors and build a predictive model for the disease-free and overall survival in non-small cell lung cancer patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors. METHODS Inclusion criteria for patients in this multicentre study were: (1) patients were diagnosed with stage I–III non-small cell lung cancer diagnosed by bronchoscopy biopsy or puncture; (2) computed tomography/positron emission tomography-computed tomography was applied before treatment and surgery; (3) neoadjuvant chemotherapy combined with immune checkpoint inhibitors were applied for 2–6 cycles preoperatively; (4) peripheral blood indicators and tumour markers were assessed before treatment and surgery; (5) patients underwent radical lung cancer surgery after neoadjuvant therapy. Cases were divided into high- and low-risk groups according to 78 clinical indicators based on 10-fold LASSO selection. We employed Cox proportional hazards models in predicting disease-free and overall survival. Then, we used time-dependent area under the curve and decision curve analyses to examine the accuracy of the results. RESULTS Data were collected continuously, and 212 and 85 cases were randomly assigned to training and testing sets, respectively. The area under curve for the prediction of disease-free survival (training-1-year, 0.83; 2-year, 0.81; 3-year, 0.83 vs testing-1-year, 0.65; 2-year, 0.66; 3-year, 0.70), overall survival (training-1-year, 0.86; 2-year, 0.85; 3-year, 0.86 vs testing-1-year, 0.66; 2-year, 0.57; 3-year, 0.70) were determined. The coefficient factors including pathological response, preoperative tumour maximum diameter, preoperative lymph shorter-diameter, preoperative tumour&lymph maximum standardized uptake value, change in tumour standardized uptake value preoperative, and blood related risk factors were favorably associated with prognosis (P < 0.001). CONCLUSIONS Our prediction model integrating data from preoperative positron emission tomography-CT, preoperative blood parameters, and pathological response was able to make high accuracy predictions for disease-free and overall survival in non-small cell lung cancer patients receiving neoadjuvant immunity with chemical therapy.