Clinical value of peripheral blood circulating tumor DNA in predicting the efficacy of immunotherapy for non-small cell lung cancer

作者
Jing Wang,Xirong Fan,Jinshu Zhang,Cheng Huang
出处
期刊:Journal of Thoracic Disease [AME Publishing Company]
卷期号:15 (5): 2659-2667 被引量:5
标识
DOI:10.21037/jtd-23-379
摘要

Background: The high expression of programmed cell death 1-ligand 1 (PD-L1) is a valid biological indicator of the therapeutic benefit of pembrolizumab in non-small cell lung cancer (NSCLC) patients. However, the response rate of NSCLC patients with positive PD-L1 expression to anti-PD-1/PD-L1 therapy is still low. Methods: From January 2019 to January 2021, a retrospective study was conducted at the Fujian Medical University Xiamen Humanity Hospital. In total, 143 patients with advanced NSCLC were treated with immune checkpoint inhibitors, and the efficacy of the treatment [complete remission (CR), partial remission (PR), stable disease (SD), or progression disease (PD)] was evaluated. Patients with a CR and PR were defined as an objective response (OR) group (n=67), and the other patients were defined as a control group (n=76). The differences in the circulating tumor DNA (ctDNA) and clinical features between the 2 groups were compared, and the receiver operating characteristic (ROC) curve was used to analyze the value of ctDNA in predicting the failure to achieve an OR after immunotherapy in patients with NSCLC, and a multivariate regression analysis was conducted to analyze the factors affecting the OR after immunotherapy in NSCLC patients. R4.0.3 statistical software (Ross Ihaka Robert Gentleman, New Zealand) was used to establish and verify the prediction model of OR after immunotherapy in NSCLC patients. Results: CtDNA was valuable in predicting the non-OR of patients with NSCLC after immunotherapy, and the area under the curve was 0.750 [95% CI: 0.673-0.828, P<0.001]. CtDNA <3.72 ng/µL can be used to predict which NSCLC patients will achieve objective remission after immunotherapy (P<0.001). Based on the regression model, a prediction model was established. The data set was randomly divided into the training set and validation set. The sample size of the training set was 72 and that of the validation set was 71. The area under the ROC curve of the training set was 0.850 (95% CI: 0.760-0.940), and that of the validation set was 0.732 (95% CI: 0.616-0.847). Conclusions: CtDNA was valuable in predicting the efficacy of immunotherapy in NSCLC patients.

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