Dolutegravir Dual Therapy as Maintenance Treatment in HIV-Infected Patients: A Review
Bibliographic record
Abstract
OBJECTIVE: To review available evidence for dolutegravir-based dual therapy as maintenance treatment in HIV-1 infected patients. DATA SOURCES: A literature search was conducted using PubMed, MEDLINE, and Google Scholar to the end of January 2018. Conference abstracts and article bibliographies were also reviewed. STUDY SELECTION AND DATA EXTRACTION: All English-language, randomized, and observational studies were included. DATA SYNTHESIS: In all, 12 studies were identified: 10 were observational, and 2 were randomized trials. Rilpivirine or lamivudine were the most common second agent used in combination with dolutegravir. Virological suppression seen in observational studies appear promising; however, the most compelling evidence to date is the 48-week results from 2 large open-label randomized trials (SWORD 1 and 2). These studies found that dual therapy with rilpivirine and dolutegravir was noninferior to 3- or 4-drug combination antiretroviral therapy (cART). The long-term efficacy, safety, and tolerability of dual therapy, as compared with usual cART, are less clear and require further data. CONCLUSIONS: Regimen switching in virally suppressed HIV-1-infected patients may be considered to reduce pill burden or dosing frequency, decrease short- or long-term toxicity, prevent or manage drug-drug interactions, and/or decrease cost. Based on available evidence, a switch to dual therapy with dolutegravir and rilpivirine appears viable for virologically suppressed patients without prior resistance mutations to these agents. Randomized studies of other dual-therapy regimens that include dolutegravir and longer-term follow-up as well as cost-effectiveness analyses are needed to provide confirmation that this strategy offers advantages to traditional cART regimens.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".