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Optimizing flow cytometric DNA ploidy and S-phase fraction as independent prognostic markers for node-negative breast cancer specimens

Bagwell, C B ; Clark, G M ; Spyratos, F ; Chassevent, A ; Bendahl, Pär-Ola LU ; Stal, O ; Killander, D ; Jourdan, M L ; Romain, S and Hunsberger, B , et al. (2001) In Cytometry 46(3). p.121-135
Abstract
Developing a reliable and quantitative assessment of the potential virulence of a malignancy has been a long-standing goal in clinical cytometry. DNA histogram analysis provides valuable information on the cycling activity of a tumor population through S-phase estimates; it also identifies nondiploid populations, a possible indicator of genetic instability and subsequent predisposition to metastasis. Because of conflicting studies in the literature, the clinical relevance of both of these potential prognostic markers has been questioned for the management of breast cancer patients. The purposes of this study are to present a set of 10 adjustments derived from a single large study that optimizes the prognostic strength of both DNA ploidy... (More)
Developing a reliable and quantitative assessment of the potential virulence of a malignancy has been a long-standing goal in clinical cytometry. DNA histogram analysis provides valuable information on the cycling activity of a tumor population through S-phase estimates; it also identifies nondiploid populations, a possible indicator of genetic instability and subsequent predisposition to metastasis. Because of conflicting studies in the literature, the clinical relevance of both of these potential prognostic markers has been questioned for the management of breast cancer patients. The purposes of this study are to present a set of 10 adjustments derived from a single large study that optimizes the prognostic strength of both DNA ploidy and S-phase and to test the validity of this approach on two other large multicenter studies. Ten adjustments to both DNA ploidy and S-phase were developed from a single node-negative breast cancer database from Baylor College (n = 961 cases). Seven of the adjustments were used to reclassify histograms into low-risk and high-risk ploidy patterns based on aneuploid fraction and DNA index optimum thresholds resulting in prognostic P values changing from little (P < 0.02) or no significance to P < 0.000005. Other databases from Sweden (n = 210 cases) and France (n = 220 cases) demonstrated similar improvement of DNA ploidy prognostic significance, P < 0.02 to P < 0.0009 and P < 0.12 to P < 0.002, respectively. Three other adjustments were applied to diploid and aneuploid S-phases. These adjustments eliminated a spurious correlation between DNA ploidy and S-phase and enabled them to combine independently into a powerful prognostic model capable of stratifying patients into low, intermediate, and high-risk groups (P < 0.000005). When the Baylor prognostic model was applied to the Sweden and French databases, similar significant patient stratifications were observed (P < 0.0003 and P < 0.00001, respectively). The successful transference of the Baylor prognostic model to other studies suggests that the proposed adjustments may play an important role in standardizing this test and provide valuable prognostic information to those involved in the management of breast cancer patients. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
breast cancer, flow cytometry, DNA index, DNA ploidy, S-phase, prognosis
in
Cytometry
volume
46
issue
3
pages
121 - 135
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:11449403
  • scopus:0035875052
ISSN
0196-4763
DOI
10.1002/cyto.1097
language
English
LU publication?
yes
id
7acbff09-8de5-4600-8da8-d322f0d3ab8c (old id 1123141)
date added to LUP
2016-04-01 16:08:51
date last changed
2022-01-28 17:39:05
@article{7acbff09-8de5-4600-8da8-d322f0d3ab8c,
  abstract     = {{Developing a reliable and quantitative assessment of the potential virulence of a malignancy has been a long-standing goal in clinical cytometry. DNA histogram analysis provides valuable information on the cycling activity of a tumor population through S-phase estimates; it also identifies nondiploid populations, a possible indicator of genetic instability and subsequent predisposition to metastasis. Because of conflicting studies in the literature, the clinical relevance of both of these potential prognostic markers has been questioned for the management of breast cancer patients. The purposes of this study are to present a set of 10 adjustments derived from a single large study that optimizes the prognostic strength of both DNA ploidy and S-phase and to test the validity of this approach on two other large multicenter studies. Ten adjustments to both DNA ploidy and S-phase were developed from a single node-negative breast cancer database from Baylor College (n = 961 cases). Seven of the adjustments were used to reclassify histograms into low-risk and high-risk ploidy patterns based on aneuploid fraction and DNA index optimum thresholds resulting in prognostic P values changing from little (P &lt; 0.02) or no significance to P &lt; 0.000005. Other databases from Sweden (n = 210 cases) and France (n = 220 cases) demonstrated similar improvement of DNA ploidy prognostic significance, P &lt; 0.02 to P &lt; 0.0009 and P &lt; 0.12 to P &lt; 0.002, respectively. Three other adjustments were applied to diploid and aneuploid S-phases. These adjustments eliminated a spurious correlation between DNA ploidy and S-phase and enabled them to combine independently into a powerful prognostic model capable of stratifying patients into low, intermediate, and high-risk groups (P &lt; 0.000005). When the Baylor prognostic model was applied to the Sweden and French databases, similar significant patient stratifications were observed (P &lt; 0.0003 and P &lt; 0.00001, respectively). The successful transference of the Baylor prognostic model to other studies suggests that the proposed adjustments may play an important role in standardizing this test and provide valuable prognostic information to those involved in the management of breast cancer patients.}},
  author       = {{Bagwell, C B and Clark, G M and Spyratos, F and Chassevent, A and Bendahl, Pär-Ola and Stal, O and Killander, D and Jourdan, M L and Romain, S and Hunsberger, B and Baldetorp, Bo}},
  issn         = {{0196-4763}},
  keywords     = {{breast cancer; flow cytometry; DNA index; DNA ploidy; S-phase; prognosis}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{121--135}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Cytometry}},
  title        = {{Optimizing flow cytometric DNA ploidy and S-phase fraction as independent prognostic markers for node-negative breast cancer specimens}},
  url          = {{http://dx.doi.org/10.1002/cyto.1097}},
  doi          = {{10.1002/cyto.1097}},
  volume       = {{46}},
  year         = {{2001}},
}