Institut für Biometrie (OE 8410), Medizinische Hochschule Hannover, Carl-Neuberg-Straße 1, 30625, Hannover, Germany.
Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main St. West, Hamilton, ON, L8S 4K1, Canada.
BMC Med Res Methodol. 2018 Oct 24;18(1):115. doi: 10.1186/s12874-018-0576-9.
BACKGROUND: To provide empirical evidence about prevalence, reporting and handling of missing outcome data in systematic reviews with network meta-analysis and acknowledgement of their impact on the conclusions. METHODS: We conducted a systematic survey including all published systematic reviews of randomized controlled trials comparing at least three interventions from January 1, 2009 until March 31, 2017. RESULTS: We retrieved 387 systematic reviews with network meta-analysis. Description of missing outcome data was available in 63 reviews. Intention-to-treat analysis was the most prevalent method (71%), followed by missing outcome data investigated as secondary outcome (e.g., acceptability) (40%). Bias due to missing outcome data was evaluated in half the reviews with explicit judgments in 18 (10%) reviews. Only 88 reviews interpreted their results acknowledging the implications of missing outcome data and mostly using the network meta-analysis results on missing outcome data as secondary outcome. We were unable to judge the actual strategy applied to deal with missing outcome data in 65% of the reviews due to insufficient information. Six percent of network meta-analyses were re-analyzed in sensitivity analysis considering missing outcome data, while 4% explicitly justified the strategy for dealing with missing outcome data. CONCLUSIONS: The description and handling of missing outcome data as well as the acknowledgment of their implications for the conclusions from network meta-analysis are deemed underreported.
背景:为了提供关于系统综述中网络荟萃分析中缺失结局数据的流行程度、报告和处理的经验证据,并承认其对结论的影响。 方法:我们进行了一项系统调查,包括所有发表的比较至少三种干预措施的随机对照试验的系统综述,这些干预措施来自 2009 年 1 月 1 日至 2017 年 3 月 31 日。 结果:我们检索到 387 篇具有网络荟萃分析的系统综述。63 篇综述描述了缺失结局数据。意向治疗分析是最常见的方法(71%),其次是将缺失结局数据作为次要结局进行调查(例如可接受性)(40%)。一半的综述评估了因缺失结局数据而产生的偏倚,并在 18 篇(10%)综述中明确做出了判断。只有 88 篇综述承认了缺失结局数据的结果,并承认其对结论的影响,主要是将缺失结局数据的网络荟萃分析结果作为次要结局。由于信息不足,我们无法判断 65%的综述中实际应用的缺失结局数据处理策略。6%的网络荟萃分析在考虑缺失结局数据的敏感性分析中重新进行了分析,而 4%的网络荟萃分析明确说明了处理缺失结局数据的策略。 结论:对缺失结局数据的描述和处理,以及对网络荟萃分析结论的影响的承认,被认为报告不足。
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