| Title |
An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients
|
|---|---|
| Published in |
Breast Cancer Research and Treatment, December 2009
|
| DOI | 10.1007/s10549-009-0674-9 |
| Pubmed ID | |
| Authors |
Balazs Györffy, Andras Lanczky, Aron C. Eklund, Carsten Denkert, Jan Budczies, Qiyuan Li, Zoltan Szallasi |
| Abstract |
Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained (n = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com . We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B, MKI67, CCND2, CCND3, CCNDE2, as well as CDKN1A, and TK2. We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources. |
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 % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 729 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 5 | <1% |
| United States | 4 | <1% |
| Mexico | 2 | <1% |
| India | 2 | <1% |
| United Kingdom | 2 | <1% |
| Canada | 2 | <1% |
| Hungary | 1 | <1% |
| Germany | 1 | <1% |
| Norway | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 707 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 168 | 23% |
| Researcher | 124 | 17% |
| Student > Master | 65 | 9% |
| Student > Bachelor | 55 | 8% |
| Student > Doctoral Student | 43 | 6% |
| Other | 124 | 17% |
| Unknown | 150 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 220 | 30% |
| Agricultural and Biological Sciences | 155 | 21% |
| Medicine and Dentistry | 89 | 12% |
| Engineering | 18 | 2% |
| Computer Science | 17 | 2% |
| Other | 56 | 8% |
| Unknown | 174 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 12 December 2023.
All research outputs
#1,691,351
of 26,017,215 outputs
Outputs from Breast Cancer Research and Treatment
#202
of 5,117 outputs
Outputs of similar age
#7,212
of 178,221 outputs
Outputs of similar age from Breast Cancer Research and Treatment
#4
of 52 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,117 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 178,221 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.