Department of Radiation Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 Qingchun East Road, Shangcheng District, Hangzhou, 310016, Zhejiang, China.
Jpn J Radiol. 2024 Jan;42(1):102-108. doi: 10.1007/s11604-023-01482-3. Epub 2023 Sep 9.
To investigate the effect of inflammation-based indexes in predicting radiation pneumonitis (RP) and prognosis in lung tumor patients treated with stereotactic body radiation therapy (SBRT).
The data of one hundred and seventy-two patients with 272 lung lesions from November 2015 to December 2020 were retrospectively analyzed. Pretreatment hematological indexes including platelet count, neutrophil count, and lymphocyte count were collected before treatment. Systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were calculated. The receiver operating characteristic (ROC) curve was established to predict the RP and overall survival of patients, and the Youden index was calculated to determine the cutoff values of SII, NLR, and PLR before radiotherapy.
Pretreatment SII, NLR, and PLR could predict RP in lung tumor patients treated with SBRT, the optimal cutoff values of SII, NLR, and PLR were 355.38, 2.04, and 141.09, respectively. Pretreatment PLR could predict survival and the optimal cutoff value of PLR was 166.83, patients with a PLR > 166.83 predict worse overall survival (OS) (P < 0.001). The 1-year and 2-year OS for patients with a PLR ≤ 166.83 were 96.3% and 82.4%, while for those with a PLR > 166.83 were 82.0% and 58.5%, respectively.
In lung tumor patients treated with SBRT, pretreatment SII, NLR, and PLR can effectively predict RP and a higher PLR predicts poor OS. These inflammation-based indexes could serve as reliable and convenient predictors to guide treatment for physicians in clinical practice.
探讨炎症指标在预测立体定向体部放疗（SBRT）治疗肺肿瘤患者放射性肺炎（RP）及预后中的作用。
回顾性分析 2015 年 11 月至 2020 年 12 月 172 例 272 个肺部病变患者的资料。治疗前采集血小板计数、中性粒细胞计数和淋巴细胞计数等预处理血液学指标。计算全身免疫炎症指数（SII）、中性粒细胞与淋巴细胞比值（NLR）和血小板与淋巴细胞比值（PLR）。绘制受试者工作特征（ROC）曲线预测患者的 RP 和总生存率，并计算 ROC 曲线下面积（AUC）的 Youden 指数，以确定放疗前 SII、NLR 和 PLR 的最佳截断值。
治疗 SBRT 的肺肿瘤患者的预处理 SII、NLR 和 PLR 可预测 RP，SII、NLR 和 PLR 的最佳截断值分别为 355.38、2.04 和 141.09。PLR 可预测生存，PLR 的最佳截断值为 166.83，PLR>166.83 的患者总生存（OS）较差（P<0.001）。PLR≤166.83 的患者 1 年和 2 年 OS 分别为 96.3%和 82.4%，而 PLR>166.83 的患者分别为 82.0%和 58.5%。
SBRT 治疗的肺肿瘤患者，预处理 SII、NLR 和 PLR 可有效预测 RP，较高的 PLR 预示着较差的 OS。这些炎症指标可作为可靠、方便的预测指标，为临床医生提供指导。
