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预测接受术后放疗的非小细胞肺癌患者发生严重急性放射性肺炎的风险:基于临床和剂量-体积直方图参数的列线图的开发和内部验证。

Predicting severe acute radiation pneumonitis in patients with non-small cell lung cancer receiving postoperative radiotherapy: Development and internal validation of a nomogram based on the clinical and dose-volume histogram parameters.

机构信息

Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, PR China.

Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, PR China.

出版信息

Radiother Oncol. 2019 Mar;132:197-203. doi: 10.1016/j.radonc.2018.10.016. Epub 2018 Oct 29.

Abstract

BACKGROUND AND PURPOSE

Postoperative radiotherapy (PORT) can potentially lead to radiation pneumonitis. We aim to develop a nomogram predicting the severe acute radiation pneumonitis (SARP, grade ≥3) in patients with non-small cell lung cancer (NSCLC) receiving PORT.

MATERIALS AND METHODS

Clinical and dose-volume histogram (DVH) factors were collected from 109 patients between 2006 and 2017. The endpoint was the development of SARP within 3 months after PORT. Logistic regression was used to evaluate the prognostic value of each factor in predicting SARP. Nomogram was generated based on multivariate regression coefficients. Area under the ROC curve (AUC), calibration curves, and decision curve analyses (DCA) were conducted to validate the model.

RESULTS

Univariate and multivariate analysis indicated that total lung mean dose (tlMD) (OR: 1.003, 95%CI: 1.001-1.006, p = 0.013), percentage of ipsilateral lung volume receiving ≥5 Gy (ilV) (OR: 1.084, 95%CI: 1.020-1.151, p = 0.009), and concurrent chemoradiotherapy (CCRT) (OR: 4.091, 95%CI: 1.331-12.572, p = 0.014) were independent prognosticators of SARP and were included in the nomogram. ROC curves revealed the AUC of the nomogram was 0.842, which was much higher than any factor alone (tlMD: 0.769; ilV: 0.744; CCRT: 0.661). Calibration curves showed favorable consistency between the predicted SARP and the actual observation. DCA showed satisfactory positive net benefits of the model among most of the threshold probabilities, indicating great clinical effect.

CONCLUSION

We identified that the tlMD (>10.8 Gy), ilV (>64.9%), and CCRT could predict SARP among patients with NSCLC receiving PORT. Combining clinical and DVH parameters, a nomogram was first built and validated, showing its potential value in practice.

摘要

背景与目的

术后放疗(PORT)可能导致放射性肺炎。我们旨在开发一种列线图,以预测接受 PORT 的非小细胞肺癌(NSCLC)患者发生严重急性放射性肺炎(SARP,等级≥3)的风险。

材料与方法

我们收集了 2006 年至 2017 年间 109 例患者的临床和剂量-体积直方图(DVH)因素。终点是 PORT 后 3 个月内发生 SARP。采用 logistic 回归分析评估每个因素对预测 SARP 的预后价值。基于多变量回归系数生成列线图。绘制 ROC 曲线(AUC)、校准曲线和决策曲线分析(DCA)来验证模型。

结果

单因素和多因素分析表明,全肺平均剂量(tlMD)(OR:1.003,95%CI:1.001-1.006,p=0.013)、同侧肺体积接受≥5 Gy(ilV)的百分比(OR:1.084,95%CI:1.020-1.151,p=0.009)和同期放化疗(CCRT)(OR:4.091,95%CI:1.331-12.572,p=0.014)是 SARP 的独立预后因素,并纳入了列线图。ROC 曲线显示,列线图的 AUC 为 0.842,明显高于任何单一因素(tlMD:0.769;ilV:0.744;CCRT:0.661)。校准曲线显示预测的 SARP 与实际观察结果之间具有良好的一致性。DCA 表明,在大多数阈值概率下,该模型具有令人满意的阳性净获益,表明其具有很好的临床效果。

结论

我们发现 tlMD(>10.8 Gy)、ilV(>64.9%)和 CCRT 可预测接受 PORT 的 NSCLC 患者的 SARP。结合临床和 DVH 参数,我们首次构建并验证了列线图,显示了其在实践中的潜在价值。

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