Literature DB >> 21927853

Prognostic impact of isolated tumor cells in breast cancer axillary nodes: single tumor cell(s) versus tumor cell cluster(s) and microanatomic location.

Johanna H Vestjens1, Maaike de Boer, Paul J van Diest, Carolien H van Deurzen, Jos A van Dijck, George F Borm, Eddy M Adang, Peter Bult, Vivianne C Tjan-Heijnen.   

Abstract

In breast cancer, it has been shown that pN0(i+) and pN1mi have a comparable negative impact on disease-free survival, compared with pN0. However, pN0(i+) is considered to be a heterogeneous group. We determined the effect of metastatic size and microanatomic location within the pN0(i+) group on breast cancer recurrence. We included all Dutch breast cancer patients diagnosed in 1998-2005 with favorable primary tumor characteristics and a final nodal status of pN0(i+). For this analysis, only patients without adjuvant systemic therapy were eligible (n = 513). Presence of single tumor cells versus cell clusters, metastatic size and microanatomic location were recorded. Primary endpoint was disease-free survival. Analyses were adjusted for age at diagnosis, tumor size, tumor grade, axillary treatment and hormone receptor status. The 5-year disease-free survival of patients with single tumor cell(s) (n = 93) was 78.6% and with tumor cell cluster(s) (n = 404) 77.1%. The hazard ratio for disease events was 1.05 (95% CI 0.63-1.76) for cell cluster(s) compared with single cell(s). In a Cox regression model, doubling of metastatic tumor size corresponded to a hazard ratio of 1.21 (95% CI 1.02-1.43). The adjusted hazard ratio was 0.90 (95% CI 0.54-1.50) for parenchymal (n = 112) versus sinusoidal location (n = 395). Single tumor cells bear similar prognostic information as small tumor cell clusters, even though results do suggest that within the pN0(i+) group, increasing size of nodal involvement is associated with reduced survival. Microanatomic location does not seem to have prognostic relevance.

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Year:  2011        PMID: 21927853     DOI: 10.1007/s10549-011-1771-0

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  3 in total

1.  Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images.

Authors:  Jun Xu; Lei Gong; Guanhao Wang; Cheng Lu; Hannah Gilmore; Shaoting Zhang; Anant Madabhushi
Journal:  J Med Imaging (Bellingham)       Date:  2019-02-08

2.  Occult Tumour Cells in Lymph Nodes from Gastric Cancer Patients: Should Isolated Tumour Cells Also Be Considered?

Authors:  A Tavares; X Wen; J Maciel; F Carneiro; M Dinis-Ribeiro
Journal:  Ann Surg Oncol       Date:  2020-05-04       Impact factor: 5.344

3.  Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer.

Authors:  David F Steiner; Robert MacDonald; Yun Liu; Peter Truszkowski; Jason D Hipp; Christopher Gammage; Florence Thng; Lily Peng; Martin C Stumpe
Journal:  Am J Surg Pathol       Date:  2018-12       Impact factor: 6.394

  3 in total

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