Imaging and pathology features to predict axillary tumor load in breast cancer

Nicolau, Pau; Gamero García, Rocío; Rodríguez Arana, Ana Maria; Plancarte Zapata, Francisco; Alcantara Souza, Rodrigo; Carreras Collado, Ramón; Sabadell Marcadal, Maria Dolores; Vernet-Tomás, Maria

doi:http://dx.doi.org/10.1111/jog.13490

Imaging and pathology features to predict axillary tumor load in breast cancer

Citació

Nicolau P, Gamero R, Rodríguez-Arana A, Plancarte F, Alcántara R, Carreras R. et al. Imaging and pathology features to predict axillary tumor load in breast cancer. J Obstet Gynaecol Res. 2018 Feb;44(2):331-336. DOI: 10.1111/jog.13490

Resum

AIM: We investigated if imaging and pathology features could help to identify a high axillary tumor burden (ATB) in breast cancer patients, in order to individualize decisions on axillary lymph node (ALN) dissection (ALND). METHODS: We retrospectively analyzed patients primarily treated with surgery in our unit between 2011 and 2014. We divided the patients in two groups: low ATB (LATB) if ≤ 2 ALN were infiltrated and high ATB (HATB) if > 2 ALN were infiltrated. RESULTS: Data of 105 patients was included in the study. Axillary ultrasound (AUS) features associated with HATB were any sign of ALN infiltration (76 vs 24%, P = 0.027) and > 2 suspicious ALNs (73% vs 27%, P = 0.018); however, when AUS revealed ≤ 2 suspicious ALNs, 39% of these patients had HATB. Any sign of ALN infiltration on magnetic resonance imaging was associated with HATB (48% vs 52%, P = 0.031). Positive preoperative ALN cytology or biopsy was associated with HATB (53% vs 47%, P = 0.008), while p53 positivity (80% vs 20%) and high histological grade (68% vs. 32%) correlated with LATB (P = 0.05 and P = 0.02, respectively). In multivariate analysis, only positive preoperative ALN cytology or biopsy was associated with HATB (P = 0.038). CONCLUSIONS: AUS was useful for detecting HATB but was not as effective in patients with LATB. Proving axillary infiltration with AUS-directed cytology or biopsy is the most effective method to predict HATB.