Literature DB >> 17983402

A decision tool for predicting sentinel node accuracy from breast tumor size and grade.

Nathan Coombs1, Wanqing Chen, Richard Taylor, John Boyages.   

Abstract

The ability to predict axillary lymph node involvement in breast cancer patients in the preoperative setting is invaluable. This study provides a simple set of formulae to enable clinicians to make informed decisions in the management of screen-detected breast cancer. The tumor pathology reports were obtained of all 4,585 women identified between 1996 and 1999 in New South Wales (NSW) with T1 or T2 breast cancer by the statewide co-ordinated breast screening service (BreastScreen NSW). Equations predicting node positivity were calculated by linear regression analysis and, from published sentinel node false-negative rates, the probability of retrieval of a false-negative axillary lymph node by sentinel node biopsy was calculated for tumors of different size and grade. Node involvement was identified in 1,089 (23.8%) of women. A linear relationship for tumor size, grade, and nodal involvement was predicted by: frequency (%) = 1.5 x tumor size (mm) + 2 (or 6 or 10) for grade I (or II or III) tumors. Assuming a 7.5% false-negative rate, the probability of retrieving a false-negative sentinel node ranged from 0.8% for a patient with a 5 mm, grade I carcinoma to 6.0% for a 50 mm, grade III tumor. These simple formulae are easy to use in a clinical setting. The reference table enables breast surgeons to inform a patient about the absolute probability of false-negative sentinel biopsy rates for patients with screen-detected carcinomas when size can be estimated from preoperative imaging and when tumor grade is often available from preoperative core biopsy. Patients with large, T2 breast tumors may be best treated with axillary dissection rather than sentinel node biopsy alone due to the risk of under-staging the woman's disease and also the high probability of finding a positive sentinel node.

Entities:  

Mesh:

Year:  2007        PMID: 17983402     DOI: 10.1111/j.1524-4741.2007.00507.x

Source DB:  PubMed          Journal:  Breast J        ISSN: 1075-122X            Impact factor:   2.431


  3 in total

1.  Prediction of axillary lymph node metastases in breast cancer patients based on pathologic information of the primary tumor.

Authors:  Jia-Long Wu; Hsin-Shun Tseng; Li-Heng Yang; Hwa-Koon Wu; Shou-Jen Kuo; Shou-Tung Chen; Dar-Ren Chen
Journal:  Med Sci Monit       Date:  2014-04-08

2.  A negative binomial regression model for risk estimation of 0-2 axillary lymph node metastases in breast cancer patients.

Authors:  Hao-Yu Lin; Yu-Ling Zhang; Jun-Dong Wu; Kun Lin; Ya Xu; Chun-Fa Chen
Journal:  Sci Rep       Date:  2020-12-14       Impact factor: 4.379

3.  Tumor characteristics of breast cancer in predicting axillary lymph node metastasis.

Authors:  Hsin-Shun Tseng; Li-Sheng Chen; Shou-Jen Kuo; Shou-Tung Chen; Yu-Fen Wang; Dar-Ren Chen
Journal:  Med Sci Monit       Date:  2014-07-07
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.