Real-world outcomes of 18,186 metastatic solid tumor outpatients: Baseline blood cell counts correlate with survival after immune checkpoint inhibitor therapy

18186例转移性实体瘤门诊患者的真实世界结果:基线血细胞计数与免疫检查点抑制剂治疗后的生存率相关

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Abstract

BACKGROUND: Patient survival in advanced/metastatic melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC) has improved with immune checkpoint inhibitors (ICI). Biomarkers' role in prognosis and treatment has been limited by conflicting trial results. METHODS: This retrospective, observational study analyzed baseline demographic, clinical, laboratory, and treatment data versus outcomes of The US Oncology Network adult outpatients. Patients with advanced/metastatic melanoma, NSCLC, or RCC treated between January 1, 2015 and November 30, 2020 were given ICI monotherapy or combination therapy with ipilimumab, pembrolizumab, nivolumab, or atezolizumab. Treatment outcomes (overall survival [OS], time to treatment discontinuation, time to next treatment) were followed longitudinally until May 31, 2021, last patient record, or date of death. Baseline blood cell counts, including absolute monocyte count (AMC), absolute lymphocyte count (ALC), monocyte-to-lymphocyte ratio (MLR), absolute neutrophil count (ANC), and eosinophil count, were subdivided into quintiles for univariate and multivariable Cox regression analyses. RESULTS: Data from 18,186 patients with advanced/metastatic melanoma (n = 3314), NSCLC (n = 12,416), and RCC (n = 2456) were analyzed. Better OS correlated with increased baseline serum albumin concentration, increased eosinophil and lymphocyte counts, and Western United States physician practice location. Decreased OS correlated with increased AMC, MLR, ANC, age, and worse Eastern Cooperative Oncology Group performance status. CONCLUSIONS: To our knowledge, this study is the largest to date to associate baseline survival indicators and outcomes in outpatients with advanced/metastatic melanoma, NSCLC, or RCC and receiving ICIs. Results may inform disease-specific prognostic models and help providers identify patients most likely to benefit from ICI therapy.

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