The Potential Cost and Benefits of Raltegravir in Simplified Second-Line Therapy among HIV Infected Patients in Nigeria and South Africa
Bibliographic record
Abstract
BACKGROUND: There is an urgent need to improve the evidence base for provision of second-line antiretroviral therapy (ART) following first-line virological failure. This is particularly the case in Sub-Saharan Africa where 70% of all people living with HIV/AIDS (PHA) reside. The aim of this study was to simulate the potential risks and benefits of treatment simplification in second-line therapy compared to the current standard of care (SOC) in a lower-middle income and an upper-middle income country in Sub-Saharan Africa. METHODS: We developed a microsimulation model to compare outcomes associated with reducing treatment discontinuations between current SOC for second-line therapy in South Africa and Nigeria and an alternative regimen: ritonavir-boosted lopinavir (LPV/r) combined with raltegravir (RAL). We used published studies and collaborating sites to estimate efficacy, adverse effect and cost. Model outcomes were reported as incremental cost effectiveness ratios (ICERs) in 2011 USD per quality adjusted life year ($/QALY) gained. RESULTS: Reducing treatment discontinuations with LPV/r+RAL resulted in an additional 0.4 discounted QALYs and increased the undiscounted life expectancy by 0.8 years per person compared to the current SOC. The average incremental cost was $6,525 per treated patient in Nigeria and $4,409 per treated patient in South Africa. The cost-effectiveness ratios were $16,302/QALY gained and $11,085/QALY gained for Nigeria and South Africa, respectively. Our results were sensitive to the probability of ART discontinuation and the unit cost for RAL. CONCLUSIONS: The combination of raltegravir and ritonavir-boosted lopinavir was projected to be cost-effective in South Africa. However, at its current price, it is unlikely to be cost-effective in Nigeria.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".