A compromise strategy for patients with multiple drug failure
Bibliographic record
Abstract
Overall, we agree with Deeks and Martin [1] regarding the need to evaluate critically the role of various strategies in the treatment of heavily pretreated HIV-infected patients. Our work has demonstrated that a substantial number of such individuals will be able to achieve an undetectable viral load if treated with a multiple drug rescue therapy (MDRT) regimen [2]. Until the results of controlled studies comparing various treatment modalities are available, we believe that we face a true equipoise. Therefore, we propose a compromise strategy that could be offered to these patients. In brief, patients who have failed multiple conventional triple drug regimens and who demonstrate extensive resistance to most of the available drugs would be considered candidates for a trial of MDRT. Patients who are able to tolerate the regimen and who achieve an undetectable viral load may choose to continue this approach. Otherwise, a simplified partly suppressive regimen as proposed by Deeks and Martin [1] may be pursued. We propose that this is a worthwhile strategy to pursue, given that it will prevent further evolution of drug-resistant variants among successfully treated patients. The fact that no statistically significant CD4 cell response was observed in patients receiving MDRT in our recently published results [2] does not detract from the fact that such patients maintained the CD4 cell gains that had been achieved as a result of previous therapies, and have prevented further resistance evolution of the virus. Several groups, including Deeks and colleagues and ourselves have previously demonstrated that partial suppression of viral replication is ultimately associated with CD4 cell decline, which contrasts with the stable CD4 cell count seen in patients who achieve an undetectable plasma viral load. Julio S. G. Montaner Marianne Harris Richard Harrigan Robert Hogg Evan Wood
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".