Division of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, CA, USA.
Division of Epidemiology, University of California, Berkeley, School of Public Health, Berkeley, CA, USA.
Epidemics. 2022 Jun;39:100570. doi: 10.1016/j.epidem.2022.100570. Epub 2022 Apr 30.
Mathematical modeling studies are frequently conducted to guide policy in global health. However, the contribution of mathematical modeling studies to World Health Organization (WHO) guideline recommendations, and the quality of evidence contributed by these studies remains unknown. We conducted a systematic review of the WHO Guidelines Review Committee database to identify guideline recommendations that included evidence from mathematical modeling studies since inception of the Guidelines Review Committee on 1 December, 2007. We included WHO guideline recommendations citing a mathematical modeling study in the primary evidence base. We defined a mathematical model as a framework that predicted epidemiologic, health or economic impact of an intervention or decision in the clinical or public health context. The primary outcome was inclusion of evidence from mathematical modeling studies in a guideline recommendation. We evaluated each unique modeling study across multiple domains of quality. Between 1 December 2007 and 1 April 2019, the WHO Guidelines Review Committee approved 154 guidelines providing 1619 guideline recommendations. Mathematical modeling studies informed 46 WHO guidelines (29.9%) and 101 unique guideline recommendations (6.2%). Modeling evidence addressed topics related to infectious diseases in 38 guidelines (82.6%) and 81 recommendations (80.2%), most commonly for HIV and tuberculosis. Evidence from modeling studies was assessed in the GRADE evidence profile for 12 recommendations (12.9%) and GRADE evidence-to-decision framework for 45 recommendations (44.6%). Modeling-informed recommendations were more likely than other recommendations within the same guidelines to be issued with a "conditional" rather than "strong" strength of recommendation (53.5% versus 37.8%), and the evidence underlying modeling-informed recommendations was more likely to be assessed as very low quality (41.6% versus 24.1%). Upon review of individual modeling studies, we estimated that 33.8% of models performed a calibration, 29.4% of models performed a validation of results, and 20.6% of models reported a change in the study conclusion in the sensitivity analysis. While policy recommendations in WHO guidelines are informed by evidence from modeling studies, the validity of modeling studies included in guidelines development is heterogeneous. Quality assessment is needed to support the evaluation and incorporation of evidence from mathematical modeling studies in guidelines development.
数学建模研究经常被用于指导全球卫生政策。然而，数学建模研究对世界卫生组织（WHO）指南建议的贡献，以及这些研究提供的证据质量仍然未知。我们对 WHO 指南审查委员会数据库进行了系统回顾，以确定自 2007 年 12 月 1 日指南审查委员会成立以来，指南建议中包含来自数学建模研究的证据。我们纳入了在主要证据基础中引用数学建模研究的 WHO 指南建议。我们将数学模型定义为一种框架，用于预测临床或公共卫生环境中干预或决策的流行病学、健康或经济影响。主要结果是指南建议中包含来自数学建模研究的证据。我们评估了每个独特的建模研究在多个质量领域的表现。2007 年 12 月 1 日至 2019 年 4 月 1 日期间，WHO 指南审查委员会批准了 154 项指南，提供了 1619 项指南建议。数学建模研究为 46 项 WHO 指南（29.9%）和 101 项独特的指南建议（6.2%）提供了信息。建模证据涉及 38 项指南（82.6%）和 81 项建议（80.2%）中与传染病相关的主题，最常见的是艾滋病毒和结核病。在 12 项建议（12.9%）中，对来自建模研究的证据进行了 GRADE 证据概况评估，在 45 项建议（44.6%）中进行了 GRADE 证据决策框架评估。与同一指南中的其他建议相比，基于建模的建议更有可能被赋予“有条件”而不是“强烈”的推荐强度（53.5% 对 37.8%），并且基于建模的建议的证据基础更有可能被评估为极低质量（41.6% 对 24.1%）。在审查个别建模研究后，我们估计 33.8%的模型进行了校准，29.4%的模型对结果进行了验证，20.6%的模型在敏感性分析中报告了研究结论的变化。虽然 WHO 指南中的政策建议是基于来自建模研究的证据，但指南制定中纳入的建模研究的有效性是多种多样的。需要进行质量评估，以支持对指南制定中来自数学建模研究的证据进行评估和纳入。
