Neoadjuvant as Future for Drug Development in Breast Cancer--Letter

Re-Evaluation of Pathologic Complete Response as a Surrogate for Event-Free and Overall Survival in Human Epidermal Growth Factor Receptor 2-Positive, Early Breast Cancer Treated With Neoadjuvant Therapy Including Anti-Human Epidermal Growth Factor Receptor 2 Therapy

PURPOSE

Pathologic complete response (pCR) has prognostic importance and is frequently used as a primary end point, but doubts remain about its validity as a surrogate for event-free survival (EFS) and overall survival (OS) in human epidermal growth factor receptor 2 (HER2)-positive, early breast cancer.

METHODS

We obtained individual-patient data from randomized trials of neoadjuvant anti-HER2 therapy that enrolled at least 100 patients, had data for pCR, EFS, and OS, and a median follow-up of at least 3 years. We quantified the patient-level association between pCR (defined as ypT0/Tis ypN0) and both EFS and OS using odds ratios (ORs, with ORs >1.00 indicating a benefit from achieving a pCR). We quantified the trial-level association between treatment effects on pCR and on EFS and OS using R2 (with values above 0.75 considered as indicating strong associations).

RESULTS

Eleven of 15 eligible trials had data for analysis (3,980 patients, with a median follow-up of 62 months). Considering all trials, we found strong patient-level associations, with ORs of 2.64 (95% CI, 2.20 to 3.07) for EFS and 3.15 (95% CI, 2.38 to 3.91) for OS; however, trial-level associations were weak, with an unadjusted R2 of 0.23 (95% CI, 0 to 0.66) for EFS and 0.02 (95% CI, 0 to 0.17) for OS. We found qualitatively similar results when grouping trials according to different clinical questions, when analyzing only patients with hormone receptor-negative disease, and when using a more stringent definition of pCR (ypT0 ypN0).

CONCLUSION

Although pCR may be useful for patient management, it cannot be considered as a surrogate for EFS or OS in neoadjuvant trials of HER2-positive, operable breast cancer.

Assessment of effect size and power for survival analysis through a binary surrogate endpoint in clinical trials

A strategy for early-stage breast cancer trials in recent years consists of a neoadjuvant trial with pathological complete response (pCR) at time of surgery as the efficacy endpoint, followed by the collection of long-term data to show efficacy in survival. To calculate an appropriate sample size to detect a survival difference based upon pCR data, it is necessary to relate the effect size in pCR with the effect size in survival. Here, we propose an exponential mixture model for survival time with parameters for the neoadjuvant pCR rates and an estimated benefit of achieving pCR to determine the treatment effect size. Through simulation studies, we demonstrated how to estimate the empirical power for detecting the survival efficacy under a parameter setting. We also showed a more efficient way to estimate the power for detecting the survival efficacy through estimated average hazard ratios and the Schoenfeld formula. Our method can be used to power future confirmatory adjuvant trials based on the preliminary data obtained from the neoadjuvant component.