Increasing studies have highlighted the potential utility of non-invasive prognostic biomarkers in advanced lung cancer patients receiving immune checkpoint inhibitor (ICI) based anti-cancer therapies. Here, a novel prognostic predictor named as C-PLAN integrating C-reactive protein (CRP), Performance status (PS), Lactate dehydrogenase (LDH), Albumin (ALB), and derived Neutrophil-to-lymphocyte ratio (dNLR) was identified and validated in a single-center retrospective cohort.
The clinical data of 192 ICI-treated lung cancer patients was retrospectively analyzed. The pretreatment levels of CRP, PS, LDH, ALB and dNLR were scored respectively and then their scores were added up to form C-PLAN index. The correlation of C-PLAN index with the progression-free survival (PFS) or overall survival (OS) was analyzed by a Kaplan–Meier model. The multivariate analysis was used to identify whether C-PLAN index was an independent prognostic predictor.
A total of 88 and 104 patients were included in the low and high C-PLAN index group respectively. High C-PLAN index was significantly correlated with worse PFS and OS in ICI-treated lung cancer patients (both p<0.001). The multivariate analysis revealed high C-PLAN index was an independent unfavorable factor affecting PFS (hazard ratio (HR)=1.821; 95%confidence interval (CI)=1.291-2.568) and OS (HR=2.058, 95%CI=1.431-2.959). The high C-PLAN index group had a significantly lower disease control rate than the low C-PLAN index group (p=0.024), while no significant difference was found for objective response rate (p=0.172). The subgroup analysis based on clinical features (pathological type, therapy strategy, TNM stage and age) confirmed the prognostic value of C-PLAN index, except for patients receiving ICI monotherapy or with age ranging from 18 to 65 years old. Finally, a nomogram was constructed based on C-PLAN index, age, gender, TNM stage and smoking status, which could predict well the 1-, 2- and 3-year survival of ICI-treated lung cancer patients.
The C-PLAN index has great potential to be utilized as a non-invasive, inexpensive and reliable prognostic predictor for advanced lung cancer patients receiving ICI-based anti-cancer therapies.