In a recent publication in Nature, researchers conducted a single-center retrospective observational study to gain more insight into the association between the risk of postoperative recurrence and baseline PD-L1 expression in NSCLC patients while considering the potential impact of adjuvant treatments on outcomes.
The authors wrote, “Accurate prediction of postoperative recurrence is important for optimizing the treatment strategies for non-small cell lung cancer (NSCLC). Previous studies identified the PD-L1 expression in NSCLC as a risk factor for postoperative recurrence.”
Using machine learning, the researchers created a postoperative recurrence prediction model based on the clinical and pathological features of patients who had undergone NSCLC resection. The authors wrote, “By analyzing this prediction model, we evaluated the contribution of differences in the expression of PD-L1 to postoperative recurrence and explored the relationship between increased PD-L1 expression and increased recurrence risk.”
The study population included 647 patients who underwent lung cancer resection between April 2017 and June 2022. The patients were randomly stratified into training (517 patients, 80%), validation (65 patients, 10%), and test groups (65 patients, 10%).
The results revealed that among this cohort, the recurrence rate was 23.3%, which was consistent with previously reported rates of 20% to 26% in larger cohorts studying lung cancer. This study demonstrated that groups with higher PD-L1 expression levels had shorter recurrence-free survival (RFS) in the conventional classification based on PD-L1 expression levels (no expression [<1%], low expression [1%-49%], and high expression [50%-100%]).
The authors also noted that using a machine learning model with a random forest algorithm and a multivariate Cox proportional hazards model with statistical analysis, they investigated the impact of PD-L1 expression on the postoperative recurrence of NSCLC. Moreover, their results showed a nonlinear increase in the risk of postoperative recurrence based on PD-L1 expression level.
Based on their findings, the authors wrote, “In conclusion, our study using machine learning and statistical analysis revealed a significant nonlinear association between the expression of PD-L1 and risk of postoperative recurrence in NSCLC. We demonstrated that even minimal PD-L1 expression levels (as low as 1%) are associated with an increased risk of recurrence, suggesting the potential impact of subtle immune interactions.”
The authors added that a constant rise in the expression of PD-L1 beyond 1% corresponded to a linear increase in the risk of recurrence. These novel findings imply a nonlinear relationship between the expression of PD-L1 and postoperative recurrence and provide valuable insight into individualized therapeutic strategies for the treatment of NSCLC.
Lastly, the authors indicated that their findings suggest that variations in PD-L1 expression may provide valuable information for clinical decision-making regarding lung cancer treatment strategies.
The content contained in this article is for informational purposes only. The content is not intended to be a substitute for professional advice. Reliance on any information provided in this article is solely at your own risk.