| Title |
Utility of Genetic Testing in Addition to Mammography for Determining Risk of Breast Cancer Depends on Patient Age.
|
|---|---|
| Published in |
AMIA Summits on Translational Science Proceedings, May 2018
|
| Pubmed ID | |
| Authors |
Shara I Feld, Jun Fan, Ming Yuan, Yirong Wu, Kaitlin M Woo, Roxana Alexandridis, Elizabeth S Burnside |
| Abstract |
While screening and treatment have sharply reduced breast cancer mortality in the past 50 years, more targeted diagnostic testing may improve the accuracy and efficiency of care. Our retrospective, age-matched, case-control study evaluated the differential value of mammography and genetic variants to predict breast cancer depending on patient age. We developed predictive models using logistic regression with group lasso comparing (1) diagnostic mammography findings, (2) selected genetic variants, and (3) a combination of both. For women older than 60, mammography features were most predictive of breast cancer risk (imaging AUC = 0.74, genetic variants AUC = 0.54, combined AUC = 0.71). For women younger than 60 there is additional benefit to obtaining genetic testing (imaging AUC = 0.69, genetic variants AUC = 0.70, combined AUC = 0.72). In summary, genetic testing supplements mammography in younger women while mammography appears sufficient in older women for breast cancer risk prediction. |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 42% |
| Student > Ph. D. Student | 3 | 25% |
| Student > Doctoral Student | 2 | 17% |
| Student > Master | 1 | 8% |
| Other | 1 | 8% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 50% |
| Biochemistry, Genetics and Molecular Biology | 2 | 17% |
| Nursing and Health Professions | 2 | 17% |
| Economics, Econometrics and Finance | 1 | 8% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 17 May 2019.
All research outputs
#4,838,109
of 25,382,440 outputs
Outputs from AMIA Summits on Translational Science Proceedings
#28
of 276 outputs
Outputs of similar age
#87,290
of 343,554 outputs
Outputs of similar age from AMIA Summits on Translational Science Proceedings
#3
of 33 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 276 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has done well, scoring higher than 86% 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 343,554 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.