NLR-based Prediction Score In The Evaluation Of Efficacy And Prognosis Prediction Of Immune Combination Therapy For Advanced NSCLC

BACKGROUND AND AIMSCombination therapy based on immune checkpoint inhibitors(ICIs)has become the standard first-line treatment strategy for patients with advanced non-small cell lung cancer(NSCLC)with negative driver mutations.However,the 5-year survival rate in programmed cell death-ligand 1(PD-L1)low-expressing population is still less than 20%.PD-L1 expression is not a perfect immune predictive marker for those receiving first-line immune combination therapy with low or no PD-L1 expression,and the search for combination or superior biomarkers is still needed in the future.In addition,most of the patients currently receiving immune combination therapy for the first time in second-or post-line therapy are advanced NSCLC patients with positive driver mutations.For the epidermal growth factor receptor(EGFR)mutation population with unknown resistance mechanisms,second-line immune combination therapy is currently recommended in the guidelines,however,the efficiency rate is only about 40%,and there is an urgent need to find suitable markers to screen the beneficiary population.There is increasing evidence that systemic inflammatory response is associated with the efficacy and prognosis of tumor immunotherapy.Therefore,this project proposes to explore systemic inflammatory response markers and establish a combination score based on this non-invasive index to screen the population that can significantly benefit from immune combination therapy.METHODSThis study included 131 advanced NSCLC patients without driver mutations who received first-line immune combination therapy;and 40 patients with driver mutations who received second-or post-line immune combination therapy after unexplained resistance to targeted therapy.Based on the ROC curve and the area below the ROC curve(AUC),the best cut-off values were determined,and patients were divided into two groups.The differences in short-term efficacy between the two groups were compared using the chi-square test or Fisher’s exact test.The KaplanMeier method was applied to analyse the survival of both groups,and the difference between groups was measured by log-rank.The Cox proportional risk model was applied to analyze the multivariate regression.Multiple groups of normally distributed continuous variables were analyzed for variance by one-way ANOVA,and multiple groups of non-normally distributed continuous variables were analyzed for variance by nonparametric tests.RESULTS1.Pre-treatment NLR>3.3 and FIB>3.196 were bad predictors of efficacy of first-line immune combination therapy,as well as independent risk factors for PFS;dynamic changes in NLR before and after treatment were associated witih treatment efficacy.2.Pre-treatment NLR>3.53 was bad predictors of efficacy of second-or postline immune combination therapy,as well as independent risk factors for PFS;NLR>3.53 and TKI-PFS>12 months were independent risk factors for prognosis of subsequent immune combination therapy.CONCLUSION1.Blood-based NF score can predicts the response population and long-term benefit population for first-line immune combination therapy and is superior to PDL1(TPS≥ 1%)based on tumor tissue detection.2.NTP score can predict OS and PFS benefit from second-or post-line immune combination therapy and helps screen those most likely to benefit from subsequent immune combination therapy after TKI resistance.