验证偏差在不孕妇女子宫内膜异常的纠正被转移到罗扬研究所使用统计方法
Fatemeh Niknejad1,2, Firoozeh Ahmadi2, Masoud Roudbari1
1Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Medical journal of the Islamic Republic of Iran
|March 4, 2024
概括
诊断测试中的验证偏差可以使用Begg和Greens和后勤回归等方法来纠正,后勤回归在不孕妇女的灵敏度和特异性计算中显示出最小的偏差. 周周是一个人.
科学领域:
- 生殖医学 生殖医学
- 医学诊断 医学诊断 医学诊断
- 生物统计学 生物统计学
背景情况:
- 验证偏差是诊断准确性研究中普遍存在的问题.
- 当不是所有参与者都接受黄金标准诊断测试时,它就会出现.
- 这种偏见可能会扭曲诊断测试的真正性能指标.
研究的目的:
- 审查和比较用于纠正诊断准确性研究中的验证偏差的方法.
- 为了评估不同纠正方法在不孕妇女子宫内膜异常诊断的背景下的有效性.
主要方法:
- 进行了一项涉及567名不育妇女的横截面研究.
- 超声波被用作指数测试,而胰腺镜和病理学作为黄金标准.
- 验证偏差的校正方法包括常规,Begg和Greens,周和后勤回归.
主要成果:
- 对于透镜,Begg和Greens和后勤回归方法的灵敏度 (SEN) 和特异性 (SPEC) 估计分别为 (48%,96%) 和 (72.8%,77%).
- 对于病理学,这些方法为SEN和SPEC提供了 (66%,88%) 和 (66.9%,87.6%).
- 周的方法导致了显著偏差的估计 (例如,22%的SEN,77%的SPEC用于透镜).
结论:
- 贝格和格林斯和后勤回归方法在诊断子宫内膜异常时有效地纠正验证偏差.
- 这些方法在灵敏度和特异性计算中显示出最小的偏差,假设存在随机丢失数据机制.
- 周的方法不那么可靠,产生大大偏差的估计.
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