Relationship between serum inflammatory markers and prognosis of advanced non-small cell lung cancer patients treated with first-line immunosuppressants
Relationship between serum inflammatory markers and prognosis of advanced non-small cell lung cancer patients treated with first-line immunosuppressants
Objective The aim of this study was to explore the application of baseline neutrophil-lymphocyte ratio(NLR),platelet count-lymphocyte ratio(PLR),monocyte-lymphocyte ratio(MLR),and pan-immune inflammation value(PIV)in the use of PD-1 inhibitors combined with chemotherapy in advanced non-small cell lung cancer(NSCLC),and establish a prognosis-related nomogram model.Methods The clinical data of 77 patients with driver gene-negative advanced NSCLC who received first-line PD-1 inhibitor combined with chemotherapy at Harbin Medical University Cancer Hospital from January 2019 to January 2021 were retro-spectively analyzed.Univariate and multivariate Cox regression analysis were used to determine the independent prognostic factors of progression-free survival(PFS);A prognostic-related nomogram model was established,and the accuracy of prediction model was e-valuated through consistency index.Results Multivariate Cox regression analyses showed that MLR,PIV,brain metastasis,and pleu-ral metastasis were independent factors affecting PFS in patients with driver gene-negative advanced NSCLC(P<0.05).The nomo-gram prognostic model constructed based on the Cox regression results had a good predictive ability(C-index value was 0.786,95%CI:0.721-0.851).The ROC curve showed that the combined effect of MLR and PIV in detecting the prognosis of PFS(AUC=0.717,P=0.001)was better than that of MLR(AUC=0.643)and PIV(AUC=0.640).Conclusion MLR,PIV,brain metastasis,and pleural metastasis can predict the prognosis of driver gene-negative advanced NSCLC patients treated with first-line chemothera-py combined with PD-1 inhibitors.The established nomogram model has high accuracy and clinical practicability.The predictive per-formance of combined detection of MLR and PIV may be better than that of separate detection of MLR and PIV.
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