There is no upper limit on the maximum effect that can be detected in randomized trials.

Background And Objectives: Randomized controlled trials (RCTs) are commonly viewed as essential for detecting small treatment benefits, yet they also identify large ("dramatic") effects. Forecasting the likelihood of future large effects helps guide resource allocation for conducting clinical trials.

Methods: We included consecutive cancer RCTs from 5 cohorts identified by funders or trial registries, minimizing publication bias. Between 1955 and 2018 (and published by 2022), 716 RCTs compared 984 experimental vs standard treatments in approximately 350,000 patients. We applied a generalized Pareto distribution (GPD) under Extreme Value Theory to predict future maximum treatment effects using data spanning 65 years.

Results: The GPD's positive shape parameter implies no upper limit on maximum treatment effects. Historically, the largest observed effect had an odds ratio (OR) of 45 (95% CI: 2-1008). If current patterns hold, the largest effect over the next 50 years is projected at OR = 23 (95% CI: 13-106). We estimated 20% probability of detecting new treatments with OR >50 within the same time frame. Increasing the number of RCTs from about 20 to 40 or 60 per year would double or triple the likelihood of detecting breakthrough treatments with dramatic effects.

Conclusion: Our findings suggest there may be no absolute upper bound on discoverable treatment effects in cancer RCTs, although estimates will likely remain in the range observed between 1955 and 2022. Conducting more RCTs would boost the probability of identifying treatments with large effects, underscoring the importance of sustained or expanded trial activity to accelerate breakthrough discoveries.

Plain Language Summary: New treatments cannot be discovered without individuals volunteering to participate in clinical studies. Among all types of human clinical studies, RCTs are considered the most reliable method for evaluating new medical treatments and are especially effective at detecting small beneficial effects. This study also demonstrates that conducting more RCTs would accelerate the discovery of treatments with both small and large effects. By increasing public participation in RCTs, we can drive faster advances in therapeutics and influence policy decisions to allocate more resources toward the conduct of these trials.