Predicting Survival Benefit of Sparing Sentinel Lymph Node Biopsy in Low-Risk Elderly Patients With Early Breast Cancer: A Population-Based Analysis

• Published in: Frontiers in oncology 2020-09, Vol.10, p.1718-1718
• Main Authors: Xu, Li, Wen, Nan, Qiu, Juanjuan, He, Tao, Tan, Qiuwen, Yang, Jiqiao, Du, Zhenggui, Lv, Qing
• Format: Article
• Language: English
• Subjects: breast cancer; elderly; nomogram; Oncology; prognosis; SEER program; sentinel lymph node biopsy
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2020.01718

Objective: The application of sentinel lymph node biopsy (SLNB) in elderly patients with early breast cancer remains somewhat controversial. This study aimed to establish individualized nomograms to predict survival outcomes of elderly patients with and without SLNB and find out which patients could avoid SLNB. Methods: A total of 39,962 ≥70-year-old patients diagnosed with T1–T2 breast cancer in 2010–2015 were included from the Surveillance, Epidemiology, and End Results (SEER) program and were divided into the training set ( n = 29,971) and the validation set ( n = 9,991). Axillary surgery was not specified in the SEER database, and we defined removing one to five lymph nodes as SLNB. Survival analysis was performed using the Kaplan–Meier plot and log-rank test. Multivariate Cox analysis was utilized to identify risk factors for overall survival (OS) and breast-cancer-specific survival (BCSS). Nomograms and a risk stratification model were constructed. Results: In the training set, patients with SLNB had better OS (adjusted HR 0.57, P < 0.001) and BCSS (adjusted HR 0.55, P < 0.001) than patients without SLNB. Multivariate COX analysis identified age, marital status, grade, subtype, T stage, and radiation as independent risk factors for OS and BCSS in both SLNB and non-SLNB groups (all P < 0.05). They were subsequently incorporated to establish nomograms to predict 3- and 5-year OS and BCSS for patients with or without SLNB. The concordance index ranged from 0.687 to 0.820, and calibration curves in the internal set and external set all demonstrated sufficient accuracies and good predictive capabilities. Further, we generated a risk stratification model which indicated that SLNB improved OS and BCSS in high-risk group (OS: HR 0.49, P < 0.001; BCSS: HR 0.54, P < 0.001), but not in the low-risk group (all P > 0.05). Conclusion: Well-validated nomograms and a risk stratification model were constructed to evaluate survival benefit from SLNB in elderly patients with early-stage breast cancer. SLNB was important for patients in the high-risk group but could be omitted in the low-risk group without sacrificing survival. This study could assist clinicians and elderly patients to weigh the risk–benefit of SLNB and make individualized decisions. We look forward to more powerful evidence from prospective trials.