Importance: Many large adjuvant clinical trials end up underpowered because of fewer than expected events in the control arm. Ensuring a minimum number of events would result in more informative trials.
Objective: To calculate individualized residual risk estimates using residual risk prediction software and assess whether defining eligibility based on a minimum residual risk threshold could increase the reliability of clinical trial power calculations compared with eligibility criteria based on tumor size and nodal status.
Design, setting, and participants: We estimated residual risk in 443 consecutive patients with early-stage breast cancer and assessed clinical trial power as a function of residual risk distribution among the accrued patients. We defined residual risk as the risk of recurrence that remains despite receipt of standard-of-care therapy; this risk is determined by baseline prognostic risk and by the improvement from adjuvant therapy. We performed trial simulations to examine how the power of a 2-arm, 1:1 randomized clinical trial would change as the residual risk distribution of the trial population that met eligibility criteria based on tumor size and nodal status changes. We also simulated trials that use a minimum residual risk value as eligibility criterion.
Main outcomes and measures: Residual risk; clinical trial power as a function of residual risk distribution among the patients.
Results: In the 443 patients (mean [SD] age, 56.1 [12.3] years; range, 23-89 years), baseline prognostic and residual risks differed substantially: 328 (74%) patients had more than 20% baseline risk of recurrence; however, after adjustment for treatment effect only 12 (27%) had more than 20% residual risk. We assessed residual risk distribution in patient cohorts that met tumor size- and nodal status-based eligibility criteria for 3 currently accruing randomized adjuvant trials; the median residual risks were 28% (interquartile range [IQR], 25%-31%), 22% (IQR, 15%-28%), and 22% (IQR, 15%-28%), respectively, indicating that the power of these trials could vary unpredictably. Simulations showed that trials that use anatomical risk-based eligibility criteria can become underpowered if they accrue patients with low residual risk despite all participants meeting eligibility requirements. Using a minimum required residual risk threshold as eligibility criterion produced more reliable power calculations.
Conclusions and relevance: When tumor size and nodal status are used to determine trial eligibility, the residual risk of recurrence can vary broadly, leading to unstable power estimates. The success of future adjuvant trials could be improved by defining patient eligibility based on a minimal residual risk of recurrence, and these trials can achieve a prespecified power with smaller sample sizes.