| Title |
4-IHC classification of breast cancer subtypes in a large cohort of a clinical cancer registry: use in clinical routine for therapeutic decisions and its effect on survival
|
|---|---|
| Published in |
Breast Cancer Research and Treatment, September 2015
|
| DOI | 10.1007/s10549-015-3572-3 |
| Pubmed ID | |
| Authors |
Elisabeth Christine Inwald, M. Koller, M. Klinkhammer-Schalke, F. Zeman, F. Hofstädter, M. Gerstenhauer, G. Brockhoff, O. Ortmann |
| Abstract |
The aim of the present study was to evaluate to what extent the combination of standard histopathological parameters determines the biology of breast cancer and the effect on therapy and prognosis. The Clinical Cancer Registry Regensburg (Bavaria, Germany) included n = 4,480 female patients with primary, non-metastatic (M0) invasive breast cancer diagnosed between 2000 and 2012. Immuno-histochemical analyses, i.e., estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 (4-IHC), defined the tumor biological subtypes Luminal A, Luminal B, HER2-like, and Basal-like. Subtype-related differences in therapies and overall survival (OS) were analyzed using multivariable statistical methods. 4344 patients (97.0 %) could be classified into the four common tumor biological subtypes. The two most frequent entities were Luminal A (48.4 %), Luminal B (24.8 %), HER2-like (17.8 %), and Basal-like subtype (9.0 %). A multivariable Cox regression model showed that the best 7-year OS was seen in Luminal A patients and that OS of Luminal B and HER2-like patients was comparable (HR = 1.59, P < 0.001 versus HR = 1.51, P = 0.03). Lowest OS was seen in patients with Basal-like tumors (HR = 2.18, P < 0.001). In conclusion, the classification of tumor biological subtypes by the ER, PR, HER2, and Ki-67 biomarkers is practical in routine clinical work. Providing that quality assurance of these markers is ensured, this classification is useful for making therapy decisions in the routine clinical management of breast cancer patients. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 115 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 17% |
| Student > Ph. D. Student | 16 | 14% |
| Student > Master | 14 | 12% |
| Student > Bachelor | 9 | 8% |
| Other | 7 | 6% |
| Other | 17 | 15% |
| Unknown | 33 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 27% |
| Biochemistry, Genetics and Molecular Biology | 21 | 18% |
| Agricultural and Biological Sciences | 10 | 9% |
| Nursing and Health Professions | 6 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 3% |
| Other | 7 | 6% |
| Unknown | 37 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 September 2015.
All research outputs
#20,291,881
of 22,828,180 outputs
Outputs from Breast Cancer Research and Treatment
#4,109
of 4,659 outputs
Outputs of similar age
#225,531
of 268,597 outputs
Outputs of similar age from Breast Cancer Research and Treatment
#59
of 87 outputs
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