Immune recovery markers in a double blind clinical trial comparing dolutegravir and raltegravir based regimens as initial therapy (SPRING-2)
Bibliographic record
Abstract
BACKGROUND: Multiple T-cell marker recovery (MTMR: CD4+ T-cells >500 cel/mm3 plus CD4+% >29% plus CD4+/CD8+ ratio >1) has been proposed as the most complete level of immune reconstitution. In this study we quantified differences in the CD4+/CD8+ ratio, CD4+% recovery and MTMR after starting HIV-1 treatment with dolutegravir (DTG) vs. raltegravir (RAL) plus a NRTI backbone. METHODS: Exploratory post-hoc analysis of the SPRING-2 study, a randomized double-blind clinical trial comparing DTG and RAL as third agents in naive HIV-infected patients at 100 sites in Canada, USA, Australia, and Europe. Percentage differences and corresponding precision based on 95% confidence intervals (CI) and p-values were calculated for i) CD4+/CD8+ ratio normalization, ii) CD4+% normalization, and iii) the achievement of MTMR. RESULTS: A total of 822 participants were analyzed (411 in each group). No statistically significant differences in the proportion of patients who reached a CD4+/CD8+ ratio ≥0.5 & ≥1 at w48 & w96 were observed. At w96, the proportion of patients with a CD4+/CD8+ ratio ≥1 was similar (30.43% DTG vs. 29.57% RAL). No differences were observed in the mean increase in CD4+/CD8+ ratio from baseline at both w48 & w96. Similarly, no significant differences in the CD4+/CD8+>29% were observed at w96 (72.95% DTG vs 69.28% RAL). The proportion of patients attaining MTMR criteria was also similar in the DTG group and the RAL group at w48 (20.33% vs. 18.26%; difference 2.07 (95%CI (-3.67;7.81) P = 0.481 and w96 (28.70% vs. 27.13; difference 1.56 (95%CI -5.22;8.34) P = 0.652). CONCLUSION: After comparing DTG and RAL, no differences on immune recovery markers were observed.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".