BACKGROUND

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.

METHODS AND FINDINGS

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.

CONCLUSIONS

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.