Voelskow Vanessa, Garcia-Albeniz Xabier, Berglund Anita, Feychting Maria, Kurth Tobias, Matthews Anthony A
Institute of Public Health, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
PLoS Med. 2025 Jul 21;22(7):e1004661. doi: 10.1371/journal.pmed.1004661. eCollection 2025 Jul.
Benchmarking an observational analysis against a randomized trial can increase confidence in the use of observational data to complement inferences made in trials. Until now, few examples of benchmarking have been within oncology. However, benchmarking trials of a cancer treatment poses a unique set of challenges, such as defining composite outcomes like disease-free survival.
We designed a target trial with a protocol as similar as possible to the B-31 and N9831 randomized trials, which estimated the effect of adjuvant trastuzumab plus chemotherapy compared with chemotherapy alone in individuals with early human epidermal growth factor receptor 2-positive breast cancer. We then carried out an observational analysis by emulating the target trial using routinely collected data from Swedish registries to understand if we can estimate a similar effect of trastuzumab as the trial. The primary endpoint was the composite of disease-free survival consisting of the earliest of (1) local or regional recurrences, (2) distant recurrences, (3) contralateral breast cancer, (4) other second primary cancer, or (5) death from any cause. Individuals who had data compatible with both treatment strategies at baseline were cloned and one copy was assigned to each arm. We applied inverse probability weights to adjust for baseline and time-varying confounding (e.g., age and hematological events like neutropenia). Our observational analysis included 1,578 women, with a median age of 59 years, and who were diagnosed between 2008 and 2015. We estimated a similar effect after five years of follow-up (RR: 0.54, 95% CI [0.44, 0.67]) for the composite endpoint of disease-free survival as the two jointly analyzed B-31 and N9831 trials (HR: 0.48, 95% CI [0.39, 0.59]). While the comparability of results increases confidence in our estimates, there remains a risk of residual and unmeasured confounding, as is the case with all observational analyses.
We successfully benchmarked an observational analysis against the B-31 and N9831 trials. By aligning protocols and using appropriate methodological approaches, we show that observational data can be used to estimate similar results as randomized trials of cancer treatments, like trastuzumab. This opens the door to using observational data to complement results from randomized trials of cancer treatments which can provide quick, cheap, and robust evidence to support decision-making where trials leave evidence gaps.
将观察性分析与随机试验进行对比，可以增强对利用观察性数据补充试验推断结果的信心。到目前为止，肿瘤学领域中对比的例子还很少。然而，对癌症治疗进行对比试验存在一系列独特的挑战，比如定义无病生存等复合结局。
我们设计了一项目标试验，其方案尽可能类似于B-31和N9831随机试验，这两项试验评估了在早期人表皮生长因子受体2阳性乳腺癌患者中，辅助性曲妥珠单抗联合化疗与单纯化疗相比的效果。然后，我们通过使用瑞典登记处常规收集的数据模拟目标试验进行观察性分析，以了解我们是否能够估计出与试验中曲妥珠单抗类似的效果。主要终点是无病生存的复合指标，包括以下最早发生的情况：（1）局部或区域复发；（2）远处复发；（3）对侧乳腺癌；（4）其他第二原发性癌症；或（5）任何原因导致的死亡。对基线时具有与两种治疗策略都兼容数据的个体进行克隆，并将一份副本分配到每个治疗组。我们应用逆概率权重来调整基线和随时间变化的混杂因素（如年龄和中性粒细胞减少等血液学事件）。我们的观察性分析纳入了1578名女性，她们的中位年龄为59岁，于2008年至2015年期间被诊断。对于无病生存的复合终点，我们在随访五年后估计出的效果（风险比：0.54，95%置信区间[0.44, 0.67]）与联合分析的B-31和N9831试验（风险比：0.48，95%置信区间[0.39, 0.59]）相似。虽然结果的可比性增强了我们对估计值的信心，但与所有观察性分析一样，仍存在残留和未测量混杂因素的风险。
我们成功地将一项观察性分析与B-31和N9831试验进行了对比。通过使方案一致并采用适当的方法学方法，我们表明观察性数据可用于估计与癌症治疗随机试验（如曲妥珠单抗试验）相似的结果。这为利用观察性数据补充癌症治疗随机试验的结果打开了大门，这些观察性数据能够提供快速、廉价且有力的证据，以支持在试验存在证据空白时的决策制定。
