Plasma Cytokine Predictors of Tuberculosis Recurrence in Antiretroviral-Treated Human Immunodeficiency Virus-infected Individuals from Durban, South Africa
Bibliographic record
Abstract
BACKGROUND: Immune correlates of tuberculosis (TB) risk in populations infected with human immunodeficiency virus (HIV) remain understudied, despite HIV being associated with a high burden of TB disease. Here we describe plasma cytokine correlates of TB recurrence in a well-characterized cohort of HIV-infected individuals on antiretroviral therapy (ART) with a history of prior TB cure. METHODS: Study participants were drawn from a prospective cohort study initiated at the conclusion of a randomized clinical trial in which individuals presented with untreated HIV infection and active pulmonary TB. At baseline, ART was initiated, and TB successfully cured. Participants were screened for TB recurrence quarterly for up to 4 years. TB recurrent cases (n = 63) were matched to controls (n = 123) on sex, study arm assignment in the original trial, and month of enrollment with a subset of cases sampled longitudinally at several time-points. RESULTS: Three cytokines were associated with increased rates of TB recurrence in univariate models: interleukin 6 (IL6) (odds ratio [OR] 2.66, 95% confidence interval [CI] 1.34-5.28, P = .005), IP10 (OR 4.62, 95% CI 1.69-12.65, P = .003), monokine induced by IFN-γ (MIG) (OR 3.11, 95% CI 1.10-8.82, P = .034). Conversely, interferon β (IFNβ) was associated with decreased TB risk (OR 0.34, 95% CI 0.13-0.87, P = .025). Following multivariate analyses adjusting for covariates IL6, interleukin 1β (IL1β), and interleukin 1Rα (IL1Rα) were associated with increased risk and IFNβ with decreased TB risk. Longitudinal analysis showed that levels of many TB-associated markers, including IL6, IP10, sCD14, and interferon γ (IFNγ) are reduced following TB treatment. CONCLUSION: These data show that TB recurrence, in HIV-infected individuals on ART is predicted by biomarkers of systemic inflammation, many of which are implicated in more rapid HIV disease progression. CLINICAL TRIALS REGISTRATION: NCT 01539005.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".