The difference in local, regional and distant breast cancer recurrence between the immediate and delayed DIEP flap procedure; a retrospective cohort study

Purpose It has been hypothesized that autologous breast reconstruction can cause reactivation of dormant micro metastases by its extensive tissue trauma, influencing the risk of breast cancer recurrence. However, about the specific effect of timing on breast cancer recurrence in the deep inferior epigastric perforator (DIEP) flap reconstruction is not much known. In this study the rate of local, regional and distant recurrence between patients undergoing an immediate and delayed autologous DIEP flap breast reconstruction were evaluated. Methods In this retrospective cohort study, breast cancer patients undergoing a DIEP flap breast reconstruction between 2010 and 2018 in three hospitals in the Netherlands were evaluated. Cox proportional hazards regression analyses were performed to assess the impact of different factors on breast cancer recurrence. The primary endpoint was local breast cancer recurrence. Secondary endpoints were regional and distant recurrence. Results A total of 919 DIEP-flap reconstructions were done in 862 women of which 347 were immediate- and 572 were delayed DIEP flap reconstructions. After a median follow-up of 46 months and 86 months respectively (p < 0.001), local breast cancer recurrence occurred in 1.5% and in 1.7% of the patients resulting in an adjusted hazard ratio of 2.890 (p = 0.001, 95% CI 1.536, 5437). Conclusion This study suggests an increased risk for breast cancer recurrence in women receiving a delayed DIEP flap reconstruction as compared to women receiving an immediate DIEP flap reconstruction. However, these data should be interpreted carefully as a result of selection bias.

Automated summary

This study suggests an increased risk for breast cancer recurrence in women receiving a delayed DIEP flap reconstruction compared to women receiving an immediate DIEP flap reconstruction. However, caution is needed in interpreting these data due to potential selection bias.