Institute of Medical Biometry and Medical Informatics, University Medical Center, 79104 Freiburg, Germany.
Pharmacoepidemiol Drug Saf. 2010 Jan;19(1):10-8. doi: 10.1002/pds.1863.
To investigate whether propensity score (ps) methods could reasonably be applied to estimate the treatment effect on mortality, based on a comparatively small sample of patients with severe cutaneous adverse reactions (SCAR) and who come from different countries where physicians prefer different treatment schemes.
Ps methods were applied to cope with confounding due to non-randomized treatment assignment for the analysis of the treatment data obtained in the case-control study EuroSCAR. For the study's purpose, the analysis focused on the comparison of the treatments: corticosteroids (STER) and supportive care only (SUPP).
206 French and German patients were treated either with SUPP or STER. Imbalances between treatment groups as well as between the countries were recognized. Concerning the balance between the treatment groups no ps model for the full cohort was satisfying. In addition, the inclusion of a variable for patient's country led to a separation of the patients by country. Thus, we developed ps models for each country separately and estimated the treatment effects (France: odds ratio (OR) 0.52, 95% confidence interval (CI) 0.09-3.10, Germany: OR 0.23, CI 0.06-0.92, Overall: OR 0.33 CI 0.11-1.04).
The application of the ps methods was successful and provided valuable information. We could confirm the findings of the original analysis which was based on standard logistic regression, especially concerning the necessity of a country-specific analysis. The observed country differences in the estimated treatment effects were less pronounced and thus seemed to be more reasonable than those of the past analysis.
探讨在严重皮肤不良反应（SCAR）患者样本较小且来自不同国家、医生倾向于不同治疗方案的情况下，是否可以合理地应用倾向评分（ps）方法来估计死亡率的治疗效果。
应用 ps 方法处理因非随机治疗分配导致的混杂因素，对病例对照研究 EuroSCAR 中获得的治疗数据进行分析。为研究目的，分析重点比较了两种治疗方法：皮质类固醇（STER）和仅支持治疗（SUPP）。
206 名法国和德国患者分别接受 SUPP 或 STER 治疗。发现治疗组之间以及国家之间存在不平衡。对于治疗组之间的平衡，没有一个完整队列的 ps 模型是令人满意的。此外，纳入患者所在国家的变量会导致患者按国家分组。因此，我们分别为每个国家开发了 ps 模型，并估计了治疗效果（法国：比值比（OR）0.52，95%置信区间（CI）0.09-3.10，德国：OR 0.23，CI 0.06-0.92，总体：OR 0.33，CI 0.11-1.04）。
应用 ps 方法是成功的，并提供了有价值的信息。我们可以证实基于标准逻辑回归的原始分析的发现，特别是关于进行特定国家分析的必要性。估计的治疗效果的观察到的国家差异不太明显，因此似乎比过去的分析更合理。
