南方医科大学学报

南方医科大学学报 ›› 2023, Vol. 43 ›› Issue (12): 2139-2144.doi: 10.12122/j.issn.1673-4254.2023.12.20

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PET/CT代谢参数与血液炎症标志物对一线化疗的非小细胞肺癌患者预后列线图的构建及临床意义

孔德贤，宋丽萍，向 阳   

  1. 锦州医科大学附属第一医院核医学科，辽宁 锦州 121000
  • 出版日期:2023-12-20 发布日期:2023-12-29

Construction of a prognostic nomogram combining PET/CT metabolic parameters and blood inflammatory markers for non-small cell lung cancer treated with first-line chemotherapy

KONG Dexian, SONG Liping, XIANG Yang   

  1. Department of Nuclear Medicine, First Affiliated Hospital of Jinzhou Medical University, Jinzhou 121000, China
  • Online:2023-12-20 Published:2023-12-29

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摘要： 目的 探讨18F-FDG-PET/CT代谢参数与血液炎症标志物，对一线化疗联合免疫治疗的晚期（IV期/IIIB期）非小细胞肺癌患者的预后价值，并建立联合指标，构建诺模图预测模型。方法 回顾性分析2019年3月~2021年6月接受化疗联合免疫治疗前基线18F-FDG-PET/CT检查的105例晚期NSCLC患者的代谢参数（最大标准摄取值SUVmax，肿瘤代谢体积MTV和病灶糖酵解总量TLG）及血液炎症标志物（中性粒细胞/淋巴细胞比值NLR、衍生中性粒细胞/淋巴细胞比值dNLR，血小板/淋巴细胞比值PLR，全身免疫炎症指数SII）。使用ROC曲线计算最佳截断点进行分组，进行单因素和多因素COX回归分析以筛选患者预后的独立预测因子，进行联合诊断分析，最终将有效生物标志物纳入预测模型，使用R语言软件的rms函数包中的cph函数构建模型（列线图nomogram）。结果 105列患者的中位随访时间为17.5个月，PFS中位数为16个月，OS位数为13.6个月。其中高PLR（≥151.050）和高TLG≥（101.940）是多变量分析中PFS的独立预后因素，高SII（941.385）和高TLG≥（101.940）是OS的独立预后因素。结合PET和血液炎症标志物的列线图具有较好的预后优势（PFS和OS的C-index指数分别为0.682和0.727），校准曲线拟合较好。决策曲线表现出良好的临床效用。结论 基线PET/CT代谢参数和血液炎症标志物与晚期一线化疗的NSCLC患者的 PFS和OS相关，且二者结合构建出的列线图具有良好的预后预测效果。

关键词: 非小细胞肺癌；PET/CT；代谢参数；血液炎症标志物；列线图

Abstract: Objective To investigate the prognostic value of 18F-FDG-PET/CT metabolic parameters and blood inflammatory markers for advanced non-small cell lung cancer (NSCLC, stage IV/IIIB) treated with first-line chemotherapy combined with immunotherapy and construct a nomogram prediction model for NSCLC. Methods We retrospectively analyzed the metabolic parameters (SUVmax, MTV and TLG) and blood markers of inflammation (NLR, DNLR, PLR and SII) in 105 patients with advanced NSCLC receiving chemotherapy combined with baseline 18F-FDG-PET/CT prior to immunotherapy from March, 2019 to June, 2021. ROC curve was used to calculate the best cut-off points for grouping, and univariate and multivariate COX regression analyses were performed to screen the independent predictors of prognosis for a combined diagnostic analysis. The effective biomarkers were included in the prediction model, and the nomogram model was constructed using the cph function in the rms function package of R language software. Results The patients were followed up for a median of 17.5 months, and their median progression-free survival (PFS) was 16 months with a median overall survival (OS) of 13.6 months. A high PLR (≥151.050) and a high TLG (≥101.940) were significant independent prognostic factors for PFS, and a high SII (≥941.385) and a high TLG (≥101.940) were independent prognostic factors for OS. The nomogram combining PET and blood markers of inflammation showed a good performance for prognostic prediction (with C-index of 0.682 for PFS and of 0.727 for OS) and good fitting of the calibration curve. The clinical decision curve showed good clinical utility of the nomogram. Conclusion The baseline PET/CT metabolic parameters and blood inflammatory markers are associated with PFS and OS of patients with advanced NSCLC receiving first-line chemotherapy, and the constructed nomogram based on these parameters has a good performance for prognostic prediction in these patients.

Key words: non-small cell lung cancer; PET/CT; metabolic parameters; blood inflammatory markers; nomogram