Combing NLR, V20 and mean lung dose to predict radiation induced lung injury in patients with lung cancer treated with intensity modulated radiation therapy and chemotherapy.
Combing NLR, V20 and mean lung dose to predict radiation induced lung injury in patients with lung cancer treated with intensity modulated radiation therapy and chemotherapy.
复制标题
结合 NLR、V20 和平均肺剂量来预测接受调强放疗和化疗治疗的肺癌患者的放射性肺损伤
DOI：
10.18632/oncotarget.19032
复制
发表时间：
2017-10-06
期刊：
影响因子：
--
通讯作者：
Wang YY
中科院分区：
文献类型：
--
作者：
Pan WY;Bian C;Zou GL;Zhang CY;Hai P;Zhao R;Wang YY
目的是评估基线中性粒细胞与淋巴细胞比值 (NLR) 水平对肺癌患者 3 级或以上放射性肺损伤 (RILI) 发生率的预测价值。对166例肺癌患者进行回顾性分析。所有入组患者均于2014年4月至2016年5月期间在我院接受放化疗。采用Cox比例风险模型识别RILI的潜在危险因素。在该队列中，3 级或以上 RILI 的发生率为 23.8%。单变量分析显示，放射剂量、至少接受20Gy（V20）的体积、平均肺剂量和NLR与3级或以上RILI的发生率显着相关（P分别为0.012、0.008、0.012和0.039）。多变量分析显示，总剂量≥60Gy、V20≥20%、平均肺剂量≥12Gy和NLR≥2.2仍然是RILI的独立预测因素（P分别为0.010、0.043、0.028和0.015）。使用受试者工作特征曲线建立了基于已识别风险因素的 RILI 预测模型。结果表明，V20、平均肺剂量和 NLR 的组合分析优于单独使用任何一个变量。此外，我们发现 V20 和平均肺剂量的限制对于基线 NLR 水平较高的患者有意义。如果V20值和平均肺剂量低于阈值，高NLR水平患者3级或以上RILI的发生率可从63.3%降低至8.7%。我们的研究表明，辐射剂量、V20、平均肺剂量和 NLR 是 RILI 的独立预测因子。 V20、平均肺剂量和 NLR 的组合分析可能为 RILI 预测提供更准确的模型。
The purpose was to evaluate the predictive value of baseline neutrophil to lymphocyte ratio (NLR) level in the incidence of grade 3 or higher radiation induced lung injury (RILI) for lung cancer patients. A retrospectively analysis with 166 lung cancer patients was performed. All of the enrolled patients received chemoradiotherapy at our hospital between April 2014 and May 2016. The Cox proportional hazard model was used to identify the potential risk factors for RILI. In this cohort, the incidence of grade 3 or higher RILI was 23.8%. Univariate analysis showed that radiation dose, volume at least received 20Gy (V20), mean lung dose and NLR were significantly associated with the incidence of grade 3 or higher RILI (P = 0.012, 0.008, 0.012, and 0.039, respectively). Multivariate analysis revealed that total dose ≥ 60 Gy, V20 ≥ 20%, mean lung dose ≥ 12 Gy, and NLR ≥ 2.2 were still independent predictive factors for RILI (P = 0.010, 0.043, 0.028, and 0.015, respectively). A predictive model of RILI based on the identified risk factors was established using receiver operator characteristic curves. The results demonstrated that the combination analysis of V20, mean lung dose and NLR was superior to either of the variables alone. Additionally, we found that the constraint of V20 and mean lung dose were meaningful for patients with higher baseline NLR level. If the value of V20 and mean lung dose lower than the threshold value, the incidence of grade 3 or higher RILI for the high NLR level patients could be decreased from 63.3% to 8.7%. Our study showed that radiation dose, V20, mean lung dose and NLR were independent predictors for RILI. Combination analysis of V20, mean lung dose and NLR may provide a more accurate model for RILI prediction.