目标试验模拟评估流行病学策略和医学经济学转移性乳腺癌队列中的真实世界疗效。
Target trial emulation to assess real-world efficacy in the Epidemiological Strategy and Medical Economics metastatic breast cancer cohort.
机构信息
Clinical Research and Biostatistics Department, Centre Léon Bérard, Lyon, France.
UMR CNRS 5558 LBBE, Claude Bernard Lyon 1 University, Villeurbanne, France.
出版信息
J Natl Cancer Inst. 2023 Aug 8;115(8):971-980. doi: 10.1093/jnci/djad092.
BACKGROUND
Real-world data studies usually consider biases related to measured confounders. We emulate a target trial implementing study design principles of randomized trials to observational studies; controlling biases related to selection, especially immortal time; and measured confounders.
METHODS
This comprehensive analysis emulating a randomized clinical trial compared overall survival in patients with HER2-negative metastatic breast cancer (MBC), receiving as first-line treatment, either paclitaxel alone or combined to bevacizumab. We used data from 5538 patients extracted from the Epidemiological Strategy and Medical Economics-MBC cohort to emulate a target trial using advanced statistical adjustment techniques including stabilized inverse-probability weighting and G-computation, dealing with missing data with multiple imputation, and performing a quantitative bias analysis for residual bias due to unmeasured confounders.
RESULTS
Emulation led to 3211 eligible patients, and overall survival estimates achieved with advanced statistical methods favored the combination therapy. Real-world effect sizes were close to that assessed in the existing E2100 randomized clinical trial (hazard ratio = 0.88, P = .16), but the increased sample size allowed to achieve a higher level of precision in real-world estimates (ie, reduced confidence intervals). Quantitative bias analysis confirmed the robustness of the results with respect to potential unmeasured confounding.
CONCLUSION
Target trial emulation with advanced statistical adjustment techniques is a promising approach to investigate long-term impact of innovative therapies in the French Epidemiological Strategy and Medical Economics-MBC cohort while minimizing biases and provides opportunities for comparative efficacy through the synthetic control arms provided.
DATABASE REGISTRATION
clinicaltrials.gov Identifier NCT03275311.
背景
真实世界研究通常考虑与测量混杂因素相关的偏倚。我们模拟了一项目标试验，实施了随机临床试验向观察性研究的设计原则；控制与选择相关的偏倚，特别是无事件时间；以及测量混杂因素。
方法
这项综合分析模拟了一项随机临床试验，比较了接受一线治疗的 HER2 阴性转移性乳腺癌（MBC）患者的总生存期，一线治疗分别为紫杉醇单药或联合贝伐珠单抗。我们使用了从 5538 名患者中提取的来自流行病学策略和医学经济学-MBC 队列的数据，使用先进的统计调整技术模拟目标试验，包括稳定的逆概率加权和 G 计算，处理缺失数据的多重插补，并进行残留偏倚的定量偏差分析由于未测量的混杂因素。
结果
模拟得出 3211 名合格患者，使用先进的统计方法得出的总生存期估计值有利于联合治疗。真实世界的效果大小与现有的 E2100 随机临床试验评估的结果相近（风险比=0.88，P=0.16），但增加的样本量使得在真实世界的估计中达到了更高的精度水平（即缩小了置信区间）。定量偏差分析证实了结果对于潜在未测量混杂的稳健性。
结论
使用先进的统计调整技术进行目标试验模拟是一种很有前途的方法，可以在法国流行病学策略和医学经济学-MBC 队列中研究创新疗法的长期影响，同时最大限度地减少偏倚，并通过提供合成对照臂提供比较疗效的机会。
数据库注册
clinicaltrials.gov 标识符 NCT03275311。
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