Guan Wenqiang, Xie Kang, Fan Yixin, Lin Stefan, Huang Rui, Tang Qianlong, Chen Ailin, Song Yanqiong, Lang Jinyi, Zhang Peng
Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China.
Department of Oncology, The Second People's Hospital of Yibin, Yibin, China.
Front Oncol. 2020 Dec 11;10:594494. doi: 10.3389/fonc.2020.594494. eCollection 2020.
The purpose was to develop and validate a nomogram for prediction on radiation-induced temporal lobe injury (TLI) in patients with nasopharyngeal carcinoma (NPC).
The prediction model was developed based on a primary cohort that consisted of 194 patients. The data was gathered from January 2008 to December 2010. Clinical factors associated with TLI and dose-volume histograms for 388 evaluable temporal lobes were analyzed. Multivariable logistic regression analysis was used to develop the predicting model, which was conducted by R software. The performance of the nomogram was assessed with calibration and discrimination. An external validation cohort contained 197 patients from January 2011 to December 2013.
Among the 391 patients, 77 patients had TLI. Prognostic factors contained in the nomogram were Dmax (the maximum point dose) of temporal lobe, D1cc (the maximum dose delivered to a volume of 1 ml), T stage, and neutrophil-to-lymphocyte ratios (NLRs). The Internal validation showed good discrimination, with a C-index of 0.847 [95%CI 0.800 to 0.893], and good calibration. Application of the nomogram in the external validation cohort still obtained good discrimination (C-index, 0.811 [95% CI, 0.751 to 0.870]) and acceptable calibration.
This study developed and validated a nomogram, which may be conveniently applied for the individualized prediction of TLI.
目的是开发并验证一种用于预测鼻咽癌（NPC）患者放射性颞叶损伤（TLI）的列线图。
基于一个由194例患者组成的初级队列开发预测模型。数据收集于2008年1月至2010年12月。分析了与TLI相关的临床因素以及388个可评估颞叶的剂量体积直方图。使用多变量逻辑回归分析开发预测模型，该分析由R软件进行。通过校准和鉴别评估列线图的性能。一个外部验证队列包含2011年1月至2013年12月的197例患者。
在391例患者中，77例发生了TLI。列线图中包含的预后因素有颞叶的Dmax（最大点剂量）、D1cc（给予1 ml体积的最大剂量）、T分期和中性粒细胞与淋巴细胞比值（NLR）。内部验证显示出良好的鉴别能力，C指数为0.847 [95%CI 0.800至0.893]，且校准良好。在外部验证队列中应用列线图仍获得了良好的鉴别能力（C指数，0.811 [95%CI，0.751至0.870]）和可接受的校准。
本研究开发并验证了一种列线图，可方便地用于TLI的个体化预测。
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