| Title |
Can Linear Regression Modeling Help Clinicians in the Interpretation of Genotypic Resistance Data? An Application to Derive a Lopinavir-Score
|
|---|---|
| Published in |
PLOS ONE, November 2011
|
| DOI | 10.1371/journal.pone.0025665 |
| Pubmed ID | |
| Authors |
Alessandro Cozzi-Lepri, Mattia C. F. Prosperi, Jesper Kjær, David Dunn, Roger Paredes, Caroline A. Sabin, Jens D. Lundgren, Andrew N. Phillips, Deenan Pillay, for the EuroSIDA and the United Kingdom CHIC/United Kingdom HDRD Studies |
| Abstract |
The question of whether a score for a specific antiretroviral (e.g. lopinavir/r in this analysis) that improves prediction of viral load response given by existing expert-based interpretation systems (IS) could be derived from analyzing the correlation between genotypic data and virological response using statistical methods remains largely unanswered. |
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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 1 | 3% |
| Tanzania, United Republic of | 1 | 3% |
| Unknown | 27 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 5 | 17% |
| Researcher | 5 | 17% |
| Student > Master | 4 | 14% |
| Student > Ph. D. Student | 4 | 14% |
| Other | 3 | 10% |
| Other | 2 | 7% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 24% |
| Agricultural and Biological Sciences | 4 | 14% |
| Nursing and Health Professions | 4 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Social Sciences | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 6 | 21% |