Journal article
Importance of nuclear morphology in breast cancer prognosis
Clinical cancer research, Vol.5(11), pp.3542-3548
11/01/1999
PMID: 10589770
Abstract
The purpose of this study is to define prognostic relationships between computer-derived nuclear morphological features, lymph node status, and tumor size in breast cancer. Computer-derived nuclear size, shape, and texture features were determined in fine-needle aspirates obtained at the time of diagnosis from 253 consecutive patients with invasive breast cancer. Tumor size and lymph node status were determined at the time of surgery. Median follow-up time was 61.5 months for patients without distant recurrence. In univariate analysis, tumor size, nuclear features, and the number of metastatic nodes were of decreasing significance for distant disease-free survival. Nuclear features, tumor size, and the number of metastatic nodes were of decreasing significance for overall survival. In multivariate analysis, the morphological size feature, largest perimeter, was more predictive of disease-free and overall survival than were either tumor size or the number of axillary lymph node metastases. This morphological feature, when combined with tumor size, identified more patients at both the good and poor ends of the prognostic spectrum than did the combination of tumor size and axillary lymph node status. Our data indicate that computer analysis of nuclear features has the potential to replace axillary lymph node status for staging of breast cancer. If confirmed by others, axillary dissection for breast cancer staging, estimating prognosis, and selecting patients for adjunctive therapy could be eliminated.
Details
- Title: Subtitle
- Importance of nuclear morphology in breast cancer prognosis
- Creators
- W. H Wolberg - University of Wisconsin–MadisonW. N Street - Management Sciences Department, University of Iowa, Iowa City, Iowa 52242, United StatesO. L Mangasarian - University of Wisconsin–Madison
- Resource Type
- Journal article
- Publication Details
- Clinical cancer research, Vol.5(11), pp.3542-3548
- Publisher
- American Association for Cancer Research
- PMID
- 10589770
- ISSN
- 1078-0432
- eISSN
- 1557-3265
- Language
- English
- Date published
- 11/01/1999
- Academic Unit
- Bus Admin College; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984380410302771
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