Feirman Shari P, Donaldson Elisabeth, Glasser Allison M, Pearson Jennifer L, Niaura Ray, Rose Shyanika W, Abrams David B, Villanti Andrea C
The Schroeder Institute for Tobacco Research and Policy Studies, Legacy, Washington, DC; Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD;
The Schroeder Institute for Tobacco Research and Policy Studies, Legacy, Washington, DC;
Nicotine Tob Res. 2016 Mar;18(3):229-42. doi: 10.1093/ntr/ntv104. Epub 2015 May 14.
The US Food and Drug Administration has expressed interest in using mathematical models to evaluate potential tobacco policies. The goal of this systematic review was to synthesize data from tobacco control studies that employ mathematical models.
We searched five electronic databases on July 1, 2013 to identify published studies that used a mathematical model to project a tobacco-related outcome and developed a data extraction form based on the ISPOR-SMDM Modeling Good Research Practices. We developed an organizational framework to categorize these studies and identify models employed across multiple papers. We synthesized results qualitatively, providing a descriptive synthesis of included studies.
The 263 studies in this review were heterogeneous with regard to their methodologies and aims. We used the organizational framework to categorize each study according to its objective and map the objective to a model outcome. We identified two types of study objectives (trend and policy/intervention) and three types of model outcomes (change in tobacco use behavior, change in tobacco-related morbidity or mortality, and economic impact). Eighteen models were used across 118 studies.
This paper extends conventional systematic review methods to characterize a body of literature on mathematical modeling in tobacco control. The findings of this synthesis can inform the development of new models and the improvement of existing models, strengthening the ability of researchers to accurately project future tobacco-related trends and evaluate potential tobacco control policies and interventions. These findings can also help decision-makers to identify and become oriented with models relevant to their work.
美国食品药品监督管理局已表示有兴趣利用数学模型来评估潜在的烟草政策。本系统评价的目的是综合利用数学模型的烟草控制研究的数据。
2013年7月1日，我们检索了五个电子数据库，以识别使用数学模型预测烟草相关结果的已发表研究，并根据国际药物经济学与结果研究协会-药物经济学与结果研究协会建模良好研究实践制定了数据提取表。我们开发了一个组织框架，对这些研究进行分类，并识别多篇论文中使用的模型。我们对结果进行了定性综合，对纳入研究进行了描述性综合。
本评价中的263项研究在方法和目的上存在异质性。我们使用组织框架根据每项研究的目标对其进行分类，并将目标映射到模型结果。我们确定了两种研究目标（趋势和政策/干预）和三种模型结果（烟草使用行为的变化、烟草相关发病率或死亡率的变化以及经济影响）。118项研究使用了18种模型。
本文扩展了传统的系统评价方法，以描述烟草控制中数学建模的文献。本综合研究的结果可为新模型的开发和现有模型的改进提供参考，增强研究人员准确预测未来烟草相关趋势以及评估潜在烟草控制政策和干预措施的能力。这些结果还可以帮助决策者识别与其工作相关的模型并熟悉这些模型。
