Expanding Access to Immediate Lymphatic Reconstruction Through an Axillary Surgery Referral Program: A 6-Year Single-Center Experience

Annals of Surgical Oncology(2024)

引用 1|浏览0
暂无评分
摘要
Background Recent advances in breast cancer have progressed toward less aggressive axillary surgery. However, axillary lymph node dissection (ALND) remains necessary in specific cases and can increase the risk of lymphedema. Performing ALND with immediate lymphatic reconstruction (ILR) can help lower this risk. This report outlines the implementation of an Axillary Surgery Referral Program (ASRP) to broaden access to ILR, providing insights for institutions considering similar initiatives. Methods A retrospective study analyzed patients referred to the ASRP at Beth Israel Deaconess Medical Center (BIDMC) between 6 January 2017 and 10 December 2022. Patients were identified from a prospective registry, with data subsequently extracted from electronic medical records. This analysis specifically centered on patients referred from external institutions to undergo ALND with ILR. Results The program received referrals for 131 patients from institutions across five different states. Annual referrals steadily increased over time. The primary indication for referral was residual axillary disease after neoadjuvant chemotherapy (41.2%). Among the referrals, 20 patients (15.3%) no longer required ALND due to axillary pathologic complete response to neoadjuvant therapy. Care coordination played a crucial role in streamlining the patient care process for both efficiency and effectiveness. Conclusion The ASRP expands access to ILR for patients with breast cancer, the majority referred for surgical management of residual disease after chemotherapy. The program provides a model for health care institutions aiming to establish similar specialized referral services. Continued program evaluation will be instrumental in refining axillary surgery referral practices and ensuring optimal patient care.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要