Wu Robert, Glen Peter, Ramsay Tim, Martel Guillaume
Department of Surgery and Ottawa Hospital Research Institute, University of Ottawa, 501 Smyth Rd, CCW 1667, K1H 8L6 Ottawa, ON, Canada.
Syst Rev. 2014 Jun 28;3:70. doi: 10.1186/2046-4053-3-70.
Observational studies dominate the surgical literature. Statistical adjustment is an important strategy to account for confounders in observational studies. Research has shown that published articles are often poor in statistical quality, which may jeopardize their conclusions. The Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines have been published to help establish standards for statistical reporting.This study will seek to determine whether the quality of statistical adjustment and the reporting of these methods are adequate in surgical observational studies. We hypothesize that incomplete reporting will be found in all surgical observational studies, and that the quality and reporting of these methods will be of lower quality in surgical journals when compared with medical journals. Finally, this work will seek to identify predictors of high-quality reporting.
METHODS/DESIGN: This work will examine the top five general surgical and medical journals, based on a 5-year impact factor (2007-2012). All observational studies investigating an intervention related to an essential component area of general surgery (defined by the American Board of Surgery), with an exposure, outcome, and comparator, will be included in this systematic review. Essential elements related to statistical reporting and quality were extracted from the SAMPL guidelines and include domains such as intent of analysis, primary analysis, multiple comparisons, numbers and descriptive statistics, association and correlation analyses, linear regression, logistic regression, Cox proportional hazard analysis, analysis of variance, survival analysis, propensity analysis, and independent and correlated analyses. Each article will be scored as a proportion based on fulfilling criteria in relevant analyses used in the study. A logistic regression model will be built to identify variables associated with high-quality reporting. A comparison will be made between the scores of surgical observational studies published in medical versus surgical journals. Secondary outcomes will pertain to individual domains of analysis. Sensitivity analyses will be conducted.
This study will explore the reporting and quality of statistical analyses in surgical observational studies published in the most referenced surgical and medical journals in 2013 and examine whether variables (including the type of journal) can predict high-quality reporting.
观察性研究在外科文献中占主导地位。统计调整是观察性研究中处理混杂因素的重要策略。研究表明，已发表的文章在统计质量方面往往较差，这可能会危及研究结论。《已发表文献中的统计分析与方法》（SAMPL）指南已发布，以帮助确立统计报告的标准。本研究旨在确定外科观察性研究中统计调整的质量以及这些方法的报告是否充分。我们假设在所有外科观察性研究中都会发现报告不完整的情况，并且与医学期刊相比，外科期刊中这些方法的质量和报告质量会更低。最后，这项工作将试图确定高质量报告的预测因素。
方法/设计：这项工作将基于5年影响因子（2007 - 2012年），考察排名前五的普通外科和医学期刊。所有调查与普通外科基本组成领域（由美国外科委员会定义）相关干预措施的观察性研究，若包含暴露因素、结局和对照，将纳入本系统评价。从SAMPL指南中提取与统计报告和质量相关的基本要素，包括分析意图、主要分析、多重比较、数字和描述性统计、关联和相关性分析、线性回归、逻辑回归、Cox比例风险分析、方差分析、生存分析、倾向分析以及独立和相关分析等领域。每篇文章将根据在研究中使用的相关分析满足标准的比例进行评分。将建立逻辑回归模型以识别与高质量报告相关的变量。将对医学期刊和外科期刊上发表的外科观察性研究的得分进行比较。次要结局将涉及各个分析领域。将进行敏感性分析。
本研究将探讨2013年引用率最高的外科和医学期刊上发表的外科观察性研究中统计分析的报告和质量，并研究变量（包括期刊类型）是否能够预测高质量报告。
