医学
彭布罗利珠单抗
内科学
肿瘤科
肺癌
比例危险模型
混淆
回顾性队列研究
单变量分析
性能状态
癌症
多元分析
免疫疗法
作者
Ishani Joshi,Monica Peravali,Xue Geng,Suman Rao,Kevin Y. Chen,Irina Veytsman,Giuseppe Giaccone,Stephen V. Liu,Chul Kim
标识
DOI:10.1016/j.cllc.2022.03.010
摘要
Abstract
Background
: While the introduction of immune checkpoint inhibitors (ICI) such as pembrolizumab has significantly improved survival for patients with metastatic non-small cell lung cancer (NSCLC), there remains a need for improved predictive and prognostic biomarkers. Patients and Methods
: We conducted a retrospective, three-center study using electronic medical record data for patients with stage IV NSCLC treated with first-line pembrolizumab, either as monotherapy or in combination with chemotherapy, between 2014 and 2019. We categorized variables as covariates or confounders. Covariates, which were the focus of analysis due to their emerging prognostic value, included pre-treatment body mass index (BMI), neutrophil-to-lymphocyte ratio (NLR), albumin, and antibiotic exposure. Confounders, which highlighted characteristics for each patient and their cancer included sex, age at start of immunotherapy, Programmed death-ligand 1 (PD-L1) expression, performance status (PS), tumor mutational burden (TMB) and whether therapy was combination therapy or monotherapy. The association between these variables with time to treatment failure (TTF) and overall survival (OS) was assessed using Kaplan-Meier method and Cox proportional hazards models. Results
: 136 patients were included in our study. Usage of antibiotics, serum albumin, NLR have univariate relationships with TTF. Serum albumin NLR, and BMI were associated with OS in univariate analyses. In a multivariate analysis, antibiotic usage had a strong negative association with TTF when adjusting for all six confounders. Conclusion
: Pre-treatment usage of antibiotics, as well as albumin, NLR, and BMI have potential to predict treatment outcomes in patients with advanced NSCLC receiving first-line immunotherapy.
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