Analysis of radiation pneumonitis risk using a generalized Lyman model.
Analysis of radiation pneumonitis risk using a generalized Lyman model.
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DOI：
10.1016/j.ijrobp.2008.04.053
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发表时间：
2008-10-01
影响因子：
7
通讯作者：
Mohan, Radhe
中科院分区：
文献类型：
--
作者：
Tucker, Susan L.;Liu, H. Helen;Liao, Zhongxing;Wei, Xiong;Wang, Shulian;Jin, Hekun;Komaki, Ritsuko;Martel, Mary K.;Mohan, Radhe
介绍莱曼正常组织并发症概率 (NTCP) 模型的一个版本，该模型适用于合并审查的毒性时间数据和临床风险因素，并将广义模型应用于放射性肺炎 (RP) 风险分析。回顾性审查了 576 例接受放射治疗的非小细胞肺癌患者的病历和放射治疗计划。计算出现严重（≥ 3 级）RP 的时间，并在最后一次随访时对未经历此终点的患者进行事件时间审查。使用标准和广义莱曼模型分析审查后的毒性时间数据，并考虑患者吸烟状况。考虑到患者吸烟状况的广义莱曼模型产生的 NTCP 估计值与仅基于剂量体积因素的模型相差高达 27 个百分点。广义模型还预测，由于审查，8% 的严重 RP 预期病例未被观察到。肺的估计体积参数与 n = 1（对应于平均肺剂量）没有显着差异。 NTCP 模型历来仅基于剂量体积效应和二元（是/否）毒性数据。我们的结果表明，纳入非剂量风险因素和经过审查的事件时间数据可以显着影响使用 NTCP 模型做出的结果预测。
To introduce a version of the Lyman normal-tissue complication probability (NTCP) model adapted to incorporate censored time-to-toxicity data and clinical risk factors, and to apply the generalized model to analysis of radiation pneumonitis (RP) risk. Medical records and radiation treatment plans were reviewed retrospectively for 576 patients with non-small cell lung cancer treated with radiotherapy. The time to severe (grade ≥ 3) RP was computed, with event times censored at last follow-up for patients not experiencing this endpoint. The censored time-to-toxicity data were analyzed using the standard and generalized Lyman models with patient smoking status taken into account. The generalized Lyman model with patient smoking status taken into account produced NTCP estimates up to 27 percentage points different than from the model based on dose-volume factors alone. The generalized model also predicted that 8% of the expected cases of severe RP were unobserved because of censoring. The estimated volume parameter for lung was not significantly different from n = 1, corresponding to mean lung dose. NTCP models historically have been based solely on dose-volume effects and binary (yes/no) toxicity data. Our results demonstrate that inclusion of non-dosimetric risk factors and censored time-to-event data can markedly affect the predictions of outcome made using NTCP models.
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影响因子：
5.7
作者：
Kwa, SLS;Theuws, CM;Lebesque, JV
通讯作者：
Lebesque, JV
DOI：
10.1016/s0360-3016(01)01685-6
发表时间：
2001-11-01
影响因子：
7
作者：
Hernando, ML;Marks, LB;Lind, PA
通讯作者：
Lind, PA
影响因子：
2.6
作者：
BENTZEN, SM;THAMES, HD;DIXON, DO
通讯作者：
DIXON, DO
DOI：
10.1016/0360-3016(86)90331-7
发表时间：
1986-10-01
影响因子：
7
作者：
SCHULTHEISS, TE;THAMES, HD;DIXON, DO
通讯作者：
DIXON, DO
DOI：
10.1016/s0360-3016(99)00183-2
发表时间：
1999-09-01
影响因子：
7
作者：
Graham, MV;Purdy, JA;Perez, CA
通讯作者：
Perez, CA