Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials.
Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials.
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DOI：
10.1002/cncr.28623
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发表时间：
2014-06-01
期刊：
影响因子：
6.2
通讯作者：
Plevritis, Sylvia K.
中科院分区：
文献类型：
--
作者：
Meza, Rafael;ten Haaf, Kevin;Kong, Chung Yin;Erdogan, Ayca;Black, William C.;Tammemagi, Martin C.;Choi, Sung Eun;Jeon, Jihyoun;Han, Summer S.;Munshi, Vidit;van Rosmalen, Joost;Pinsky, Paul;McMahon, Pamela M.;de Koning, Harry J.;Feuer, Eric J.;Hazelton, William D.;Plevritis, Sylvia K.
关键词：
国家肺筛查试验（NLST）表明，低剂量CT筛查是降低肺癌（LC）死亡率的有效方法。然而，最佳的筛查策略尚未确定，也不确定是否比NLST中的吸烟者更轻的吸烟者也可能从筛查中受益。为了解决这些问题，有必要首先开发LC自然史模型，可以重现NLST的结果，并在人群水平上模拟筛选程序。使用来自NLST和前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验（PLCO）的常见输入和校准靶标开发了五个独立的LC筛查模型。在两项试验中，对一小部分个体和诊断的LC缺失的吸烟、组织学和分期信息进行了插补。模型根据LC发病率、死亡率或两种结局同时进行校准。最初，所有模型都校准到NLST，并根据PLCO进行验证。模型验证良好，对PLCO个人谁将有资格NLST。然而，所有模型都需要进一步校准PLCO，以充分捕获PLCO从不吸烟者和轻度吸烟者的LC结果。所有模型的最终版本在存在和不存在筛查的情况下产生的发病率和死亡率结果与两项试验一致。我们根据NLST和PLCO中的证据开发了五种不同的LC筛选模拟模型。我们的分析表明，NLST和PLCO产生了一致的结果。由此产生的模型可以成为重要的工具，以产生额外的证据，以确定低剂量CT肺癌筛查策略的有效性。
The National Lung Screening Trial (NLST) demonstrated that low-dose CT screening is an effective way of reducing lung cancer (LC) mortality. However, optimal screening strategies have not been determined yet and it is uncertain whether lighter smokers than those in NLST may also benefit from screening. To address these questions, it is necessary to first develop LC natural history models that can reproduce NLST outcomes and simulate screening programs at the population level. Five independent LC screening models were developed using common inputs and calibration targets derived from NLST and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). Imputation of missing smoking, histology and stage information for a small fraction of individuals and diagnosed LCs in both trials was performed. Models were calibrated to LC incidence, mortality or both outcomes simultaneously. Initially, all models were calibrated to NLST and validated against PLCO. Models validated well against PLCO individuals who would have been eligible to NLST. However, all models required further calibration to PLCO to adequately capture LC outcomes in PLCO never and light smokers. Final versions of all models produced incidence and mortality outcomes in the presence and absence of screening consistent with both trials. We developed five distinct LC screening simulation models based on the evidence in NLST and PLCO. Our analyses demonstrate that NLST and PLCO have produced consistent results. The resulting models can be important tools to generate additional evidence to determine the effectiveness of low-dose CT lung cancer screening strategies.
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DOI：
10.1177/0272989x10369005
发表时间：
2011-01
期刊：
Medical decision making : an international journal of the Society for Medical Decision Making
影响因子：
--
作者：
Rutter CM;Zaslavsky AM;Feuer EJ
通讯作者：
Feuer EJ
影响因子：
3.6
作者：
Siebert, Uwe;Alagoz, Oguzhan;Kuntz, Karen M.
通讯作者：
Kuntz, Karen M.
DOI：
10.1093/jnci/djs136
发表时间：
2012-04-04
期刊：
Journal of the National Cancer Institute
影响因子：
--
作者：
Moolgavkar SH;Holford TR;Levy DT;Kong CY;Foy M;Clarke L;Jeon J;Hazelton WD;Meza R;Schultz F;McCarthy W;Boer R;Gorlova O;Gazelle GS;Kimmel M;McMahon PM;de Koning HJ;Feuer EJ
通讯作者：
Feuer EJ
影响因子：
10.3
作者：
Spitz, Margaret R.;Hong, Waun Ki;Etzel, Carol J.
通讯作者：
Etzel, Carol J.
影响因子：
2.3
作者：
Feuer, EJ;Etzioni, R;Mariotto, A
通讯作者：
Mariotto, A