Passive immunotherapy for adults hospitalized with COVID-19: An individual participant data meta-analysis of six randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Anti-SARS-CoV-2 monoclonal antibodies (mAb) reduce the risk of hospitalization in outpatients with mild-to-moderate COVID-19. However, the efficacy of treatment with mAbs and other passive immunotherapies in patients hospitalized with severe COVID-19 is not clear. The objective of this study was to assess the clinical effect of passive immunotherapy and its heterogeneity according to baseline endogenous neutralizing antibody status and SARS-CoV-2 antigen level, in adults hospitalized with SARS-CoV-2 infection and severe COVID-19. METHODS AND FINDINGS: We carried out a two-stage individual participant data meta-analysis of six double-blind, randomized, placebo-controlled trials conducted under the Therapeutics for Inpatients with COVID-19 (TICO) and the similarly designed Inpatient Treatment with Anti-Coronavirus Immunoglobulin (ITAC) master protocols. Within each trial, three major outcomes (sustained recovery, mortality, and a composite safety outcome) were compared between treatment and placebo using Fine-Gray and Cox proportional hazards models. Trial-specific treatment differences for each of the three outcomes were pooled using a common effect meta-analysis. A total of 3,079 patients hospitalized for COVID-19 were enrolled in the six trials. Only 18% had received at least one dose of an anti-SARS-CoV-2 vaccine. Overall, the median plasma SARS-CoV-2 antigen level was 1,421 (IQR: 231-4,568) pg/mL, and 51% of patients were endogenous neutralizing antibody positive at study entry. The overall summary estimate of sustained recovery rate ratio (RRR) of the treatment versus placebo group was 1.06 (95% CI [0.99,1.14]), but this varied significantly by antibody serostatus. The RRR was 1.16 (95% CI [1.04,1.29]) among seronegative patients and 0.97 (95% CI [0.88,1.07]) in seropositive patients [p = 0.02 for interaction (the difference in RRR between seropositive and seronegative patients)]. The summary hazard ratio (HR) for mortality comparing treatment to placebo was 0.81 (95% CI [0.64,1.03]) overall, 0.69 (95% CI [0.50,0.95]) in seronegative patients, and 0.96 (95% CI [0.66,1.39]) in seropositive patients (interaction p = 0.18). There was no evidence that the treatment effect on any outcome differed according to antigen level, whether overall or within serostatus subgroups. In regards to the composite safety outcome, the overall summary HR comparing treatment group to placebo was 0.89 (95% CI [0.66,1.21]; Q = 3.47 [p = 0.63], I2 = 0.0%), and it was 0.83 (95% CI [0.70,0.99]) and 1.04 (95% CI [0.86,1.26]) in seronegative and seropositive patients, respectively. The main limitation of the methodology is that these results are limited to the analysis of the six trials in ACTIV-3/TICO and ITAC and are not intended to be a complete summary of all trials of passive immunotherapy. CONCLUSIONS: Passive immunotherapy might be a useful treatment option for hospitalized patients with COVID-19 if administered before the appearance of endogenous antibodies. Development of similar passive immunotherapy could also be especially important during the early stages of a viral pandemic, or as novel viral variants emerge.
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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 | 0.023 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.050 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".