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Cross-modality applicability of rectal normal tissue complication probability models from photon- to proton-based radiotherapy.基于光子和质子放疗的直肠正常组织并发症概率模型的跨模态适用性。
Radiother Oncol. 2020 Jan;142:253-260. doi: 10.1016/j.radonc.2019.09.017. Epub 2019 Oct 17.
2
Modeling of Normal Tissue Complications Using Imaging and Biomarkers After Radiation Therapy for Hepatocellular Carcinoma.使用影像学和生物标志物对肝癌放射治疗后正常组织并发症进行建模。
Int J Radiat Oncol Biol Phys. 2018 Feb 1;100(2):335-343. doi: 10.1016/j.ijrobp.2017.10.005.
3
Impact of model and dose uncertainty on model-based selection of oropharyngeal cancer patients for proton therapy.模型和剂量不确定性对基于模型选择口咽癌患者进行质子治疗的影响。
Acta Oncol. 2017 Nov;56(11):1444-1450. doi: 10.1080/0284186X.2017.1355113. Epub 2017 Aug 22.
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A closed testing procedure to select an appropriate method for updating prediction models.一种用于选择更新预测模型合适方法的封闭测试程序。
Stat Med. 2017 Dec 10;36(28):4529-4539. doi: 10.1002/sim.7179. Epub 2016 Nov 28.
5
The Quest for Evidence for Proton Therapy: Model-Based Approach and Precision Medicine.质子治疗的循证探索:基于模型的方法与精准医学。
Int J Radiat Oncol Biol Phys. 2016 May 1;95(1):30-36. doi: 10.1016/j.ijrobp.2015.10.004. Epub 2015 Oct 9.
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Multivariable normal-tissue complication modeling of acute esophageal toxicity in advanced stage non-small cell lung cancer patients treated with intensity-modulated (chemo-)radiotherapy.晚期非小细胞肺癌患者接受调强(化疗)放疗后急性食管毒性的多变量正常组织并发症建模
Radiother Oncol. 2015 Oct;117(1):49-54. doi: 10.1016/j.radonc.2015.08.010. Epub 2015 Sep 2.
7
Selection of patients for radiotherapy with protons aiming at reduction of side effects: the model-based approach.质子放射治疗中基于模型的方法以减少副作用为目标的患者选择。
Radiother Oncol. 2013 Jun;107(3):267-73. doi: 10.1016/j.radonc.2013.05.007. Epub 2013 Jun 5.
8
Predictors of high-grade esophagitis after definitive three-dimensional conformal therapy, intensity-modulated radiation therapy, or proton beam therapy for non-small cell lung cancer.非小细胞肺癌行根治性三维适形放疗、调强放疗或质子束放疗后发生高级别食管炎的预测因素。
Int J Radiat Oncol Biol Phys. 2012 Nov 15;84(4):1010-6. doi: 10.1016/j.ijrobp.2012.01.071. Epub 2012 Aug 21.
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Med Phys. 2012 Mar;39(3):1386-409. doi: 10.1118/1.3685447.
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Cancer. 2011 Jul 1;117(13):3004-13. doi: 10.1002/cncr.25848. Epub 2011 Jan 24.

利曼-库彻-伯曼正常组织并发症概率模型在接受质子放射治疗的非小细胞肺癌患者放射性食管炎中的应用。

Lyman-Kutcher-Burman normal tissue complication probability modeling for radiation-induced esophagitis in non-small cell lung cancer patients receiving proton radiotherapy.

机构信息

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, USA.

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, USA; Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Radiother Oncol. 2020 May;146:200-204. doi: 10.1016/j.radonc.2020.03.003. Epub 2020 Apr 30.

DOI:10.1016/j.radonc.2020.03.003
PMID:32220701
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10035357/
Abstract

PURPOSE

To develop and test an Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) model to predict radiation-induced esophagitis (RE) in non-small cell lung cancer (NSCLC) patients receiving passive-scattering proton therapy (PSPT).

MATERIAL AND METHODS

We retrospectively reviewed 328 NSCLC patients receiving PSPT at our institution. Esophagitis severity was graded by physicians according to the Common Toxicity Criteria for Adverse Events version 3.0, and the primary endpoint was grade ≥2 RE within 6 months from the first treatment. LKB model parameters (n, m, and TD) were determined using maximum likelihood estimation. Overall performance of the model was quantified by Nagelkerke's R and the scaled Brier score. Discriminative ability was evaluated using the area under the receiver operating curve (AUC), and calibration was assessed with the Hosmer-Lemeshow goodness-of-fit test. Bootstrap internal validation was performed to assess the model uncertainty and generalizability.

RESULTS

Grade 2-3 RE was observed in 136 (41.5%) patients, and no grade 4-5 RE was reported. The optimal LKB parameters were: n = 0.24, m = 0.51, and TD = 44.83 Gy (relative biological effectiveness). The optimism-corrected AUC was 0.783, and the Hosmer-Lemeshow test showed significant agreement between predicted and observed morbidity. Bootstrap validation verified that the model was robust to similar future populations.

CONCLUSION

Our LKB NTCP model to predict grade ≥2 RE in NSCLC patients who received PSPT showed good predictive performance and robustness to similar future populations, and a smaller volume effect than the previously observed in photon-treated populations. External validation of the model is warranted.

摘要

目的

开发和验证一种 Lyman-Kutcher-Burman(LKB)正常组织并发症概率(NTCP)模型,以预测接受被动散射质子治疗(PSPT)的非小细胞肺癌(NSCLC)患者的放射性食管炎(RE)。

材料与方法

我们回顾性分析了在我院接受 PSPT 的 328 例 NSCLC 患者。食管炎严重程度由医师根据不良事件通用毒性标准 3.0 进行分级,主要终点为治疗后 6 个月内出现 2 级或以上 RE。采用最大似然估计法确定 LKB 模型参数(n、m 和 TD)。采用 Nagelkerke 的 R 和标准化 Brier 评分来量化模型的整体性能。采用接收者操作特征曲线下面积(AUC)评估判别能力,采用 Hosmer-Lemeshow 拟合优度检验评估校准情况。采用 Bootstrap 内部验证评估模型的不确定性和可推广性。

结果

136 例(41.5%)患者出现 2-3 级 RE,无 4-5 级 RE。最佳 LKB 参数为:n=0.24,m=0.51,TD=44.83 Gy(相对生物效应)。校正后的 AUC 为 0.783,Hosmer-Lemeshow 检验显示预测发病率与观察发病率之间存在显著一致性。Bootstrap 验证验证了该模型对类似未来人群具有稳健性。

结论

我们的 LKB NTCP 模型预测接受 PSPT 的 NSCLC 患者 2 级或以上 RE 的预测性能良好,对类似未来人群具有稳健性,且体积效应小于先前观察到的光子治疗人群。该模型需要进一步的外部验证。