Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Quebec.
Institute for Health and Social Policy, McGill University, Montreal, Quebec.
Am J Epidemiol. 2019 May 1;188(5):840-845. doi: 10.1093/aje/kwy280.
Observational studies are ambiguous, difficult, and necessary for epidemiology. Presently, there are concerns that the evidence produced by most observational studies in epidemiology is not credible and contributes to research waste. I argue that observational epidemiology could be improved by focusing greater attention on 1) defining questions that make clear whether the inferential goal is descriptive or causal; 2) greater utilization of quantitative bias analysis and alternative research designs that aim to decrease the strength of assumptions needed to estimate causal effects; and 3) promoting, experimenting with, and perhaps institutionalizing both reproducible research standards and replication studies to evaluate the fragility of study findings in epidemiology. Greater clarity, credibility, and transparency in observational epidemiology will help to provide reliable evidence that can serve as a basis for making decisions about clinical or population-health interventions.
观察性研究在流行病学中具有重要意义,但也存在诸多问题和挑战。目前,人们普遍担心,大多数流行病学观察性研究产生的证据并不可靠,造成了研究资源的浪费。我认为,通过更加关注以下三个方面,观察性流行病学可以得到改善:1)明确提出问题,以阐明推理目标是描述性的还是因果性的;2)更广泛地利用定量偏差分析和其他研究设计,以降低估计因果效应所需的假设强度;3)推广、尝试并可能将可重复性研究标准和复制研究制度化,以评估流行病学研究结果的脆弱性。提高观察性流行病学的清晰度、可信度和透明度,将有助于提供可靠的证据,为临床或人群健康干预措施提供决策依据。