Recurrence detection in patients with triple-negative breast cancer following the current standard of care: a microsimulation model.

Abstract

Breast cancer is the most common cancer among women in the USA, accounting for approximately 31% of new cases and 15% of cancer-related deaths in females. Triple-negative breast cancer (TNBC) is the most lethal subtype with 29 months median overall survival. Despite curative-intent surgery and systemic adjuvant therapy, many patients remain at risk for recurrence. We developed a comprehensive model for patients with operable stage II and III TNBC, adhering to the current standard-of-care clinical follow-up recommendations, to evaluate the effectiveness of these recommendations in detecting recurrence among patients with newly diagnosed TNBC. An individual-level state transition (microsimulation) model was built with a lifetime horizon using monthly cycles. The model integrated treatment and surveillance recommendations per current guidelines. The currently recommended treatment and surveillance modalities by the National Comprehensive Cancer Network guidelines for surveilling patients with TNBC after diagnosis. Female patients aged 49 years who were newly diagnosed with operable stage II or III TNBC. Cumulative recurrences, detected recurrences, detection rate, overall survival and recurrence-free survival in a 5-year horizon, as well as average life expectancy, were the outcome measures used. Our model estimated a 5-year overall survival rate of 81.4%±0.1% (SE) for patients with stage II or III TNBC, with a recurrence-free survival rate of 78.3%±0.1% (SE). Over the same period, 7.4%±0.1% (SE) of patients with TNBC were projected to experience recurrences (68% distant recurrence, 32% locoregional recurrence), with a detection rate of only 59.3%±0.2% (SE) among these recurrences. Our model estimated that 399 mammograms would be required to detect one locoregional recurrence and 279 other imaging tests would be needed to identify one distant recurrence. Our clinically validated model sheds light on the outcomes for patients with TNBC, revealing the limitations in recurrence detection rates associated with current guidelines. These findings underscore the need for improved strategies during the surveillance period. As novel testing methods become available, this model can be instrumental in exploring how these innovations may improve patient outcomes.