Discussion
NSCLC, gene-mutation, tumor, thoracic tumors
TUMOR, INFILTRATION, NSCLC, INFILTRATING, REGRESSION, SQUAMOUS CARCINOMA
Accurate treatment response prediction is critical to stratifying and selecting patients who can benefit most from neoadjuvant immunochemotherapy and avoiding ir-sAEs. The present study developed and validated an accurate radiomics-clinical combined model to predict a major pathologic response to neoadjuvant immunochemotherapy in patients with potentially resectable NSCLC, with a favorable AUC (0.84) and a high sensitivity (80%) and specificity (79%), outperforming radiomics-only and clinical-only models.Pre-treatment CT images show intratumor spatial variation. Previous studies have shown that pre-treatment CT radiomics could reflect tumor CD8 cell infiltration and objective response to immune checkpoint blockade (ICB) monotherapy (Due to the multiple mechanisms of immunotherapy, atypical patterns of response produced by immunotherapy (e.g., pseudo-progression, delayed responses, and hyper-progression) cannot be correctly assessed using traditional response criteria, making it difficult to judge the benefits of immunotherapy. The pathological test remains the gold standard. MPR is an early surrogate of long-term survival. The nomogram constructed in the present study only contains Rad-score and pathological type, which can be obtained with a routine CT scan and biopsy. The present model can also apply to advanced NSCLC patients to some extent, patients with higher score according to the nomogram are likely to respond better to immunochemotherapy.Pathological type was the only chosen clinical variable to build the nomogram through univariate and multivariate logistic regression analyses in the present work. Some phase 3 randomized trials, such as Keynote 024 (PD-L1 failed to predict MPR in our study and was not chosen for model construction. Several neoadjuvant immunochemotherapy clinical trials, such as NADIM, LCMC3, and NEOSTAR, have already confirmed that PD-L1 is not an ideal biomarker for predicting MPR (NLR also failed to predict MPR in NSCLC patients receiving neoadjuvant immunochemotherapy in the present work, which is inconsistent with a previous study on the topic (Our nomogram, which was constructed based on Rad-score and pathological type, performed exceptionally well on calibration curve and decision curve analysis, which means that the nomogram fitted well with our data and was useful clinically.Despite its promising results, our study has several limitations. First, this is a retrospective study, making bias inevitable. A prospective study is needed to further verify our proposed model. Second, our sample size was small and imbalanced. As neoadjuvant immunochemotherapy was recently approved by the FDA in March 2022, the study period was short. Moreover, most participants were male smokers, had squamous carcinoma, and had PD-L1 levels >1%. Third, only pretreatment CT images were able to predict neoadjuvant immunochemotherapy response. Dynamic changes in radiomics (delta radiomics) and other potentially useful clinic-pathological factors, such as tumor infiltrating lymphocyte, gene-mutation profile, PET images, or serum densities of specific subgroups of immune cells has not yet been investigated. Fourth, only the targeted thoracic tumors were delineated manually and analyzed. Accurate automatic segmentation methods should be explored and developed in the future. The radiomics of lymph nodes may also provide valuable information for predicting the response to neoadjuvant immunochemotherapy. Although our current results proved that this model was useful, further confirmation in a larger cohort is mandatory before it can be applied to routine clinical practice.