Development and validation of a web-based calculator to predict individualized conditional risk of site-specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases.
Development and validation of a web-based calculator to predict individualized conditional risk of site-specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases.
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开发和验证基于网络的计算器来预测鼻咽癌部位特异性复发的个体化条件风险：对 10,058 个地方性病例的分析
DOI：
10.1002/cac2.12113
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发表时间：
2021-01
期刊：
影响因子：
--
通讯作者：
Sun Y
中科院分区：
文献类型：
--
作者：
Wu CF;Lv JW;Lin L;Mao YP;Deng B;Zheng WH;Wen DW;Chen Y;Kou J;Chen FP;Yang XL;Zheng ZQ;Li ZX;Xu SS;Ma J;Sun Y
条件生存期（CS）通过考虑患者现有的生存时间提供动态预后估计。由于缺乏地方性鼻咽癌（NPC）的CS，我们的目的是评估地方性NPC的CS，并建立一个基于网络的计算器来预测个体化的、有条件的部位特异性复发风险。使用带有大数据智能平台的NPC特定数据库，调查了2009年4月至2015年12月期间接受调强放疗（伴或不伴化疗）的10，058名非转移性I-IVA期NPC地方病患者。计算条件总生存期（COS）、条件无病生存期（CDFS）、条件局部无复发生存期（CLRRFS）、条件无远处转移生存期（CDMFS）和条件NPC特异性生存期（CNPC-SS）的粗CS估计值。使用逆概率加权生成协变量校正的CS估计值。使用竞争风险模型建立预测模型，并在另一家机构使用接受调强放疗伴或不伴化疗的独立非转移性I-IVA期NPC队列（n = 601）进行外部验证。主要队列的中位随访时间为67.2个月。5年COS、CDFS、CLRRFS、CDMFS和CNPC-SS分别从诊断时的86.2%、78.1%、89.8%、87.3%和87.6%增加至87.3%、87.7%、94.4%、96.0%和90.1%，自诊断以来的现有生存时间为3年。每个终点的预后因素亚组之间的CS估计值差异在诊断时明显，但随着时间的推移而减少，而随着时间的推移，观察到不同年龄亚组之间的CS差异不断增加。值得注意的是，随着患者存活时间的延长，诊断不佳的患者的病情大大改善。对于个体化CS预测，我们开发了一个基于网络的模型来估计局部（C指数，0.656）、区域（0.667）、骨（0.742）、肺（0.681）和肝（0.711）复发的条件风险，其显著优于当前分期系统（P < 0.001）。使用外部验证队列（中位随访时间为61.3个月）进一步验证了该网络模型的性能，C指数分别为0.672、0.736、0.754、0.663和0.721。我们在迄今为止最大的队列中描述了地方性NPC的CS。此外，我们建立了一个基于网络的计算器来预测特定部位复发的CS，这可能有助于定制个性化，基于风险，适应时间的随访策略。
Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, conditional site‐specific recurrence risk. Using an NPC‐specific database with a big‐data intelligence platform, 10,058 endemic patients with non‐metastatic stage I–IVA NPC receiving intensity‐modulated radiotherapy with or without chemotherapy between April 2009 and December 2015 were investigated. Crude CS estimates of conditional overall survival (COS), conditional disease‐free survival (CDFS), conditional locoregional relapse‐free survival (CLRRFS), conditional distant metastasis‐free survival (CDMFS), and conditional NPC‐specific survival (CNPC‐SS) were calculated. Covariate‐adjusted CS estimates were generated using inverse probability weighting. A prediction model was established using competing risk models and was externally validated with an independent, non‐metastatic stage I–IVA NPC cohort undergoing intensity‐modulated radiotherapy with or without chemotherapy (n = 601) at another institution. The median follow‐up of the primary cohort was 67.2 months. The 5‐year COS, CDFS, CLRRFS, CDMFS, and CNPC‐SS increased from 86.2%, 78.1%, 89.8%, 87.3%, and 87.6% at diagnosis to 87.3%, 87.7%, 94.4%, 96.0%, and 90.1%, respectively, for an existing survival time of 3 years since diagnosis. Differences in CS estimates between prognostic factor subgroups of each endpoint were noticeable at diagnosis but diminished with time, whereas an ever‐increasing disparity in CS between different age subgroups was observed over time. Notably, the prognoses of patients that were poor at diagnosis improved greatly as patients survived longer. For individualized CS predictions, we developed a web‐based model to estimate the conditional risk of local (C‐index, 0.656), regional (0.667), bone (0.742), lung (0.681), and liver (0.711) recurrence, which significantly outperformed the current staging system (P < 0.001). The performance of this web‐based model was further validated using an external validation cohort (median follow‐up, 61.3 months), with C‐indices of 0.672, 0.736, 0.754, 0.663, and 0.721, respectively. We characterized the CS of endemic NPC in the largest cohort to date. Moreover, we established a web‐based calculator to predict the CS of site‐specific recurrence, which may help to tailor individualized, risk‐based, time‐adapted follow‐up strategies.
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影响因子：
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DOI：
10.1016/s1470-2045(14)71116-7
发表时间：
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期刊：
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影响因子：
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