Multicenter evaluation of predictive clinical and imaging factors for pathological response in non-small cell lung cancer patients treated with neoadjuvant chemotherapy and immune checkpoint inhibitors.

Abstract

Background: This study aimed to identify clinical factors and develop a predictive model for pathological complete response (pCR) and major pathological response (MPR) in non-small cell lung cancer (NSCLC) patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors (ICIs).

Methods: Cases meeting inclusion criteria were divided into high- and low-risk groups according to 75 clinical indicators based on tenfold LASSO selection. Logistic regression was employed to analyze both pCR and MPR. The accuracy of the nomograms was assessed using the time-dependent area under the curve (AUC).

Results: A total of 297 patients from four multiple centers were included in the study, with 212 assigned to the training set and 85 to the testing set. The AUC was determined for the prediction of pCR (training: 0.97; testing: 0.88) and MPR (training: 0.98; testing: 0.81). Significant associations were observed between the preoperative tumor maximum diameter, preoperative tumor maximum standardized uptake value (SUV_max), changes in tumor SUV_max, percentage of tumor reduction, baseline total prostate-specific antigen (TPSA) and pathological response (P < 0.001).

Conclusions: The combined application of clinical indicators including non-invasive tumor imaging and hematology can help clinicians to obtain a higher ability to predict NSCLC patient's pathological remission, and the effect is better than that of clinical factors alone. These findings could help guide personalized treatment strategies in this patient population.