Sanderson Simon, Tatt Iain D, Higgins Julian P T
Primary Care Genetics, General Practice and Primary Care Research Unit, University of Cambridge and Public Health Genetics Unit, Strangeways Research Labs, Worts Causeway, Cambridge, UK.
Int J Epidemiol. 2007 Jun;36(3):666-76. doi: 10.1093/ije/dym018. Epub 2007 Apr 30.
Assessing quality and susceptibility to bias is essential when interpreting primary research and conducting systematic reviews and meta-analyses. Tools for assessing quality in clinical trials are well-described but much less attention has been given to similar tools for observational epidemiological studies.
Tools were identified from a search of three electronic databases, bibliographies and an Internet search using Google. Two reviewers extracted data using a pre-piloted extraction form and strict inclusion criteria. Tool content was evaluated for domains potentially related to bias and was informed by the STROBE guidelines for reporting observational epidemiological studies.
A total of 86 tools were reviewed, comprising 41 simple checklists, 12 checklists with additional summary judgements and 33 scales. The number of items ranged from 3 to 36 (mean 13.7). One-third of tools were designed for single use in a specific review and one-third for critical appraisal. Half of the tools provided development details, although most were proposed for future use in other contexts. Most tools included items for selection methods (92%), measurement of study variables (86%), design-specific sources of bias (86%), control of confounding (78%) and use of statistics (78%); only 4% addressed conflict of interest. The distribution and weighting of domains across tools was variable and inconsistent.
A number of useful assessment tools have been identified by this report. Tools should be rigorously developed, evidence-based, valid, reliable and easy to use. There is a need to agree on critical elements for assessing susceptibility to bias in observational epidemiology and to develop appropriate evaluation tools.
在解释原始研究以及进行系统评价和荟萃分析时,评估质量和偏倚易感性至关重要。评估临床试验质量的工具已有详尽描述,但对于观察性流行病学研究的类似工具关注较少。
通过检索三个电子数据库、参考文献以及使用谷歌进行互联网搜索来识别工具。两名评审员使用预先试点的提取表格和严格的纳入标准提取数据。根据与偏倚潜在相关的领域对工具内容进行评估,并参考加强观察性流行病学研究报告(STROBE)指南。
共审查了86种工具,包括41种简单清单、12种带有额外总结判断的清单和33种量表。条目数量从3到36不等(平均13.7)。三分之一的工具设计用于特定综述中的单次使用,三分之一用于批判性评价。一半的工具提供了开发细节,尽管大多数是提议供未来在其他背景下使用。大多数工具包括选择方法(92%)、研究变量测量(86%)、特定设计的偏倚来源(86%)、混杂因素控制(78%)和统计方法使用(78%)的条目;只有4%涉及利益冲突。各领域在工具中的分布和权重各不相同且不一致。
本报告识别出了一些有用的评估工具。工具应经过严格开发、基于证据、有效、可靠且易于使用。有必要就观察性流行病学中评估偏倚易感性的关键要素达成一致,并开发适当的评估工具。