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药物致畸性研究中的医学数据库:方法学问题。

Medical databases in studies of drug teratogenicity: methodological issues.

机构信息

Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark;

出版信息

Clin Epidemiol. 2010 Aug 9;2:37-43. doi: 10.2147/clep.s9304.

Abstract

More than half of all pregnant women take prescription medications, raising concerns about fetal safety. Medical databases routinely collecting data from large populations are potentially valuable resources for cohort studies addressing teratogenicity of drugs. These include electronic medical records, administrative databases, population health registries, and teratogenicity information services. Medical databases allow estimation of prevalences of birth defects with enhanced precision, but systematic error remains a potentially serious problem. In this review, we first provide a brief description of types of North American and European medical databases suitable for studying teratogenicity of drugs and then discuss manifestation of systematic errors in teratogenicity studies based on such databases. Selection bias stems primarily from the inability to ascertain all reproductive outcomes. Information bias (misclassification) may be caused by paucity of recorded clinical details or incomplete documentation of medication use. Confounding, particularly confounding by indication, can rarely be ruled out. Bias that either masks teratogenicity or creates false appearance thereof, may have adverse consequences for the health of the child and the mother. Biases should be quantified and their potential impact on the study results should be assessed. Both theory and software are available for such estimation. Provided that methodological problems are understood and effectively handled, computerized medical databases are a valuable source of data for studies of teratogenicity of drugs.

摘要

超过一半的孕妇会服用处方药物,这引起了对胎儿安全的担忧。常规从大量人群中收集数据的医学数据库是研究药物致畸性的队列研究的潜在有价值资源。这些资源包括电子病历、管理数据库、人群健康登记处和致畸性信息服务。医学数据库可以更精确地估计出生缺陷的流行率,但系统误差仍然是一个潜在的严重问题。在这篇综述中,我们首先简要描述了适合研究药物致畸性的北美和欧洲医学数据库的类型,然后讨论了基于这些数据库的致畸性研究中系统误差的表现。选择偏倚主要源于无法确定所有生殖结局。信息偏倚(错误分类)可能是由于记录的临床细节不足或药物使用记录不完整引起的。混杂,特别是指示性混杂,几乎无法排除。掩盖致畸性或造成虚假表象的偏倚可能对儿童和母亲的健康产生不利影响。应量化偏倚,并评估其对研究结果的潜在影响。这些估计都有理论和软件支持。只要理解并有效处理方法学问题,计算机化的医学数据库就是药物致畸性研究的有价值的数据来源。

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