Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada.
Department of Radiation Oncology, London Health Sciences Centre, London, ON N6A 5W9, Canada.
J Comp Eff Res. 2021 Aug;10(11):939-951. doi: 10.2217/cer-2021-0069. Epub 2021 Jun 1.
We compared propensity score matching (PSM) and coarsened exact matching (CEM) in balancing baseline characteristics between treatment groups using observational data obtained from a pan-Canadian prostate cancer radiotherapy database. Changes in effect estimates were evaluated as a function of improvements in balance, using results from randomized clinical trials to guide interpretation. CEM and PSM improved balance between groups in both comparisons, while retaining the majority of original data. Improvements in balance were associated with effect estimates closer to those obtained in randomized clinical trials. CEM and PSM led to substantial improvements in balance between comparison groups, while retaining a considerable proportion of original data. This could lead to improved accuracy in effect estimates obtained using observational data in a variety of clinical situations.
我们比较了倾向评分匹配（PSM）和粗化精确匹配（CEM）在使用来自全加前列腺癌放疗数据库的观察性数据平衡治疗组之间的基线特征方面的效果。我们根据随机临床试验的结果来指导解释，评估了平衡改善对效应估计值的影响。在这两种比较中，CEM 和 PSM 都改善了组间的平衡，同时保留了大部分原始数据。平衡的改善与更接近随机临床试验中获得的效应估计值相关。CEM 和 PSM 使比较组之间的平衡得到了实质性的改善，同时保留了相当一部分原始数据。这可能会提高在各种临床情况下使用观察性数据获得的效应估计值的准确性。
