Trikalinos T A, Ioannidis J P
Clinical Trials and Evidence-Based Medicine Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
J Clin Epidemiol. 2001 Mar;54(3):245-52. doi: 10.1016/s0895-4356(00)00311-5.
We developed and evaluated methods for the analysis and interpretation of the baseline risk heterogeneity in meta-analysis of individual patient data (MIPD) based on information on predictive factors. We used data from a typical MIPD of eight clinical trials (1792 patients, 2947 years of follow-up) on the efficacy of high-dose acyclovir in human immunodeficiency virus infection. Cox models with four predictive factors (age, disease state, CD4 cell count and hemoglobin levels) were used to estimate predicted individual hazards both for single trials and for various MIPD modeling methods (simple pooling, adjusted for study, stratified per study, fixed and random effects for predictors). For each study and for each method of MIPD synthesis, we estimated the odds ratio for death in the upper versus the lower quartile of predicted risk (Extreme Quartile Odds Ratio, EQuOR) and the respective rate ratio (Extreme Quartile Rate Ratio, EQuRR). Only the CD4 cell count showed a significantly heterogeneous predictive effect across the eight studies (P =.024). The EQuOR of single studies ranged from 3.5 (little heterogeneity) to 24 (intermediate heterogeneity), substantially lower than the EQuOR of the MIPD (167 to 275, depending on the model used). The EQuRR values ranged from 3.5 to 77 for single studies and from 77 to 116 for the various MIPD models. Predictive modeling can be a major strength of MIPD, when performed and interpreted with standardized approaches. All models consistently show that MIPD may be a study design with extreme heterogeneity of patient baseline risk.
我们基于预测因素的信息，开发并评估了个体患者数据荟萃分析（MIPD）中基线风险异质性的分析和解释方法。我们使用了一项典型的MIPD数据，该数据来自八项关于高剂量阿昔洛韦治疗人类免疫缺陷病毒感染疗效的临床试验（1792例患者，2947人年的随访）。使用包含四个预测因素（年龄、疾病状态、CD4细胞计数和血红蛋白水平）的Cox模型来估计单个试验以及各种MIPD建模方法（简单合并、按研究调整、按研究分层、预测因素的固定效应和随机效应）下的个体预测风险。对于每项研究以及MIPD综合分析的每种方法，我们估计了预测风险上四分位数与下四分位数中死亡的比值比（极端四分位数比值比，EQuOR）和相应的率比（极端四分位数率比，EQuRR）。在八项研究中，只有CD4细胞计数显示出显著的异质性预测效应（P = 0.024）。单个研究的EQuOR范围为3.5（异质性小）至24（中等异质性），远低于MIPD的EQuOR（167至275，取决于所使用的模型）。单个研究的EQuRR值范围为3.5至77，各种MIPD模型的EQuRR值范围为77至116。当采用标准化方法进行和解释时，预测建模可能是MIPD的一个主要优势。所有模型一致表明，MIPD可能是一种患者基线风险存在极端异质性的研究设计。
