Breast Cancer ctDNA Surveillance Landscape

Dr. Teplinsky discusses the evolving breast cancer surveillance paradigm, noting historical data showing routine imaging surveillance doesn't impact outcomes, though this data predates modern imaging technology.

The central question remains whether earlier detection through ctDNA can change disease trajectory rather than simply representing lead-time bias.

The SURVIVE trial, still recruiting, compares standard surveillance after primary therapy completion against intensive surveillance incorporating ctDNA testing every 3 months alongside circulating tumor cells and conventional tumor markers used in metastatic disease monitoring.

The iSPY trial has demonstrated that ctDNA clearance during treatment indicates better prognosis, whereas persistent positivity predicts relapse, confirming prognostic value while leaving intervention questions unanswered.

Multiple ongoing studies are testing whether escalating treatment for persistently positive ctDNA can delay or prevent recurrence.

Dr. Teplinsky notes the strongest current data exists in triple-negative and HER2-positive populations, which experience earlier recurrences enabling more feasible follow-up, compared to HR-positive disease where recurrences may occur 10 to 20 years later.

She discusses the negative ZEST trial, which tested PARP inhibitor addition for patients with triple-negative breast cancer with positive ctDNA but enrolled an overly broad population rather than focusing on higher-risk subgroups, potentially explaining the negative result.

For patients with persistent ctDNA positivity despite clear imaging, Dr. Teplinsky acknowledges this represents "the million-dollar question" with no established optimal therapy or monitoring frequency.

Lead time estimates range from 8 months to 3 years depending on the study.

She emphasizes needing trials demonstrating ability to convert positive results to negative, or delaying metastatic disease development, even before overall survival data matures, with baseline recurrence risk by subtype informing individualized approaches rather than broad subtype-based rules.