| Title |
Early prediction of resistance to tyrosine kinase inhibitors by plasma monitoring of EGFR mutations in NSCLC: a new algorithm for patient selection and personalized treatment
|
|---|---|
| Published in |
Oncotarget, March 2020
|
| DOI | 10.18632/oncotarget.27517 |
| Pubmed ID | |
| Authors |
Fiamma Buttitta, Lara Felicioni, Alessia Di Lorito, Alessio Cortellini, Luciana Irtelli, Davide Brocco, Pietro Di Marino, Donatella Traisci, Nicola D’Ostilio, Alessandra Di Paolo, Francesco Malorgio, Pasquale Assalone, Sonia Di Felice, Francesca Fabbri, Giovanni Cianci, Michele De Tursi, Antonio Marchetti |
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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 3 | 13% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Bachelor | 2 | 8% |
| Student > Doctoral Student | 1 | 4% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 13 | 54% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 13% |
| Medicine and Dentistry | 3 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 8% |
| Nursing and Health Professions | 1 | 4% |
| Social Sciences | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 11 | 46% |
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 28 March 2020.
All research outputs
#1,430,740
of 23,312,088 outputs
Outputs from Oncotarget
#651
of 14,402 outputs
Outputs of similar age
#38,537
of 394,729 outputs
Outputs of similar age from Oncotarget
#13
of 58 outputs
Altmetric has tracked 23,312,088 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 14,402 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 95% 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 394,729 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 90% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.