Treatment outcomes of patients on second-line antiretroviral therapy in resource-limited settings
Bibliographic record
Abstract
BACKGROUND: A growing proportion of patients on antiretroviral therapy in resource-limited settings have switched to second-line regimens. We carried out a systematic review in order to summarize reported rates and reasons for virological failure among people on second-line therapy in resource-limited settings. METHODS: Two reviewers independently searched four databases and three conference websites. Full text articles were screened and data extracted using a standardized data extraction form. RESULTS: We retrieved 5812 citations, of which 19 studies reporting second-line failure rates in 2035 patients across low-income and middle-income countries were eligible for inclusion. The cumulative pooled proportion of adult patients failing virologically was 21.8, 23.1, 26.7 and 38.0% at 6, 12, 24 and 36 months, respectively. Most studies did not report adequate information to allow discrimination between drug resistance and poor adherence as reasons for virological failure, but for those that did poor adherence appeared to be the main driver of virological failure. Mortality on second-line was low across all time points. CONCLUSION: Rates of virological failure on second-line therapy are high in resource-limited settings and associated with duration of exposure to previous drug regimens and poor adherence. The main concern appears to be poor adherence, rather than drug resistance, from the limited number of studies accessing both factors. Access to treatment options beyond second-line remains limited and, therefore, a cause for a concern for those patients in whom drug resistance is the identified cause of virological failure.
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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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".