基于炎症的评分可以优化考虑早期临床试验的晚期癌症患者的选择。
An inflammation based score can optimize the selection of patients with advanced cancer considered for early phase clinical trials.
机构信息
Wellcome Trust McMichael Clinical Research Facility, Imperial College London, Hammersmith Hospital, London, United Kingdom.
University College London Clinical Research Facility, University College London Hospital, London, United Kingdom.
出版信息
PLoS One. 2014 Jan 7;9(1):e83279. doi: 10.1371/journal.pone.0083279. eCollection 2014.
BACKGROUND
Adequate organ function and good performance status (PS) are common eligibility criteria for phase I trials. As inflammation is pathogenic and prognostic in cancer we investigated the prognostic performance of inflammation-based indices including the neutrophil (NLR) and platelet to lymphocyte ratio (PLR).
METHODS
We studied inflammatory scores in 118 unselected referrals. NLR normalization was recalculated at disease reassessment. Each variable was assessed for progression-free (PFS) and overall survival (OS) on uni- and multivariate analyses and tested for 90 days survival (90DS) prediction using receiving operator curves (ROC).
RESULTS
We included 118 patients with median OS 4.4 months, 23% PS>1. LDH≥450 and NLR≥5 were multivariate predictors of OS (p<0.001). NLR normalization predicted for longer OS (p<0.001) and PFS (p<0.05). PS and NLR ranked as most accurate predictors of both 90DS with area under ROC values of 0.66 and 0.64, and OS with c-score of 0.69 and 0.60. The combination of NLR+PS increased prognostic accuracy to 0.72. The NLR was externally validated in a cohort of 126 subjects.
CONCLUSIONS
We identified the NLR as a validated and objective index to improve patient selection for experimental therapies, with its normalization following treatment predicting for a survival benefit of 7 months. Prospective validation of the NLR is warranted.
背景
足够的器官功能和良好的表现状态（PS）是 I 期试验的常见入选标准。由于炎症在癌症中具有发病机制和预后意义，我们研究了包括中性粒细胞（NLR）和血小板与淋巴细胞比值（PLR）在内的炎症相关指标的预后表现。
方法
我们研究了 118 例未经选择的患者的炎症评分。在疾病重新评估时重新计算 NLR 的正常化。在单变量和多变量分析中评估每个变量的无进展生存（PFS）和总生存（OS），并使用接收者操作特征曲线（ROC）测试 90 天生存率（90DS）预测。
结果
我们纳入了 118 例患者，中位 OS 为 4.4 个月，23%的 PS>1。LDH≥450 和 NLR≥5 是 OS 的多变量预测因素（p<0.001）。NLR 正常化预测更长的 OS（p<0.001）和 PFS（p<0.05）。PS 和 NLR 是预测 90DS 和 OS 的最准确预测因素，ROC 曲线下面积分别为 0.66 和 0.64，c-分数分别为 0.69 和 0.60。NLR+PS 的组合增加了预测准确性，达到 0.72。NLR 在另一组 126 例患者中进行了外部验证。
结论
我们确定 NLR 是一种经过验证和客观的指标，可以改善患者对实验性治疗的选择，治疗后 NLR 的正常化预测生存获益 7 个月。需要前瞻性验证 NLR。
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