一项归算研究表明,缺少的结果数据可以在患者报告结果的系统审查中大大偏差聚合估计
Yanjiao Shen1, Zhengchi Li2, Xianlin Gu3
1Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, Innovation Institute for Integration of Medicine and Engineering, Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.
患者报告结果 (PROM) 中缺少的数据可能会影响系统性审查. 更多的缺失数据和较小的治疗效应增加了误导结果的风险,需要仔细解释.
科学领域:
- 医学研究方法论医学研究方法论.
- 生物统计学 生物统计学
- 证据综合研究
背景情况:
- 缺少结果数据是随机对照试验 (RCT) 和系统审查中的一个重大挑战.
- 虽然研究了缺失二进制结果的影响,但缺失持续患者报告结果措施 (PROMs) 对聚合估计的影响不太清楚.
- 本研究评估了PROM系统审查中缺少数据带来的偏差风险.
研究的目的:
- 评估缺失的连续患者报告结果对系统审查中聚合效应估计的影响.
- 评估PROM的元分析中不同程度的缺失数据带来的偏差风险.
主要方法:
- 分析了100个系统评论,并对统计学上显著的连续PROM进行了元分析.
- 应用了基于GRADE方法的四种归算策略和三种替代方法,用于预先计算的数据.
- 使用Firth逻辑回归来识别结果的预测因素,在归算后跨过零值.
主要成果:
- 越来越严格的归算策略显著增加了95%置信区间 (CI) 超过零的元分析的比例,达到54.2%.
- 较高的平均缺失数据 (OR 1.23每1%的增加) 和较小的治疗效应与CI越过零的可能性增加有关.
- 无论是数据库类型还是随访持续时间,都没有预测CI超过零值.
结论:
- 可信的归因方法揭示了PROM系统审查中缺少数据的偏差风险很大,通常会导致最初重要的发现超过零值.
- 缺失数据的比例和治疗效应的程度是影响审查结果可靠性的关键因素.
- 系统性审查的作者应该考虑正式的敏感性分析,以测试缺少数据对他们的结论的影响.
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