Antibody therapies for treatment of non-severe COVID-19
Bibliographic record
Abstract
of the studyThis is the latest iteration of a living systematic review, published Sept 23rd, 2021, meaning that updates are integrated with each iteration of literature searches. Daily searches are made by the WHO, including over 25 "bibliographic and grey literature sources" found in the US Center for Disease Control and Prevention (CDC) COVID-19 Research Articles Downloadable Database. Study selection included preprints—primary research articles that have been released to the public before peer review. Preprints were tracked until publication, and changes were made to the guidelines if discrepancies existed between the preprint and peer-reviewed versions.Trial characteristics, patient demographics, donor characteristics and clinically important outcomes were recorded for each selected article. Outcomes for patients with severe and non-severe disease were studied separately. This severity was determined by the WHO severity scale: non-severe disease mandated that patients have O2 sats > 90% on room air, no signs of pneumonia, and no other clinical signs or symptoms of respiratory distress.Outcomes of interest were decided upon by a team of clinical experts, and included: mortality, mechanical ventilation, adverse events leading to discontinuation within 28 days, viral clearance, TRALI, TACO, infusion reactions, admission to hospital, hospital stay time, ICU length of stay, time to symptom resolution, time to viral clearance. Importantly, side effects of mABs not addressed in these outcomes may include anaphylaxis and sequelae of allergic reactions. mAB infusion may also induce bleeding, soreness, or infection at the site of administration.Fourteen different antibody or cellular treatments were evaluated for the treatment of COVID-19. This review focuses only on the evaluation of 12 studies of 5 monoclonal antibody therapies: bamlanivimab (LY-CoV555; 4 trials), casirivimab-imdevimab (REGEN-COV; 4 trials), bamlanivimab-etesevimab (2 trials), sotrovimab (1 trial), and CT-P59 monoclonal antibody (1 trial). 54.5% of these were preprints. Once preprints were published, there were no statistically significant differences in either outcomes or patient characteristics when comparing the preprint and peer-reviewed publication.There was a lower risk of hospital admission in patients with non-severe COVID-19 when treated with mAB therapy compared to standard care alone: casirivimab-imdevimab odds ratio (OR) 0.29 (95% CI 0.17–0.47); bamlanivimab OR 0.24 (95% CI 0.06–0.86), bamlanivimab-etesevimab OR 0.31 (95% CI 0.11–0.81), sotrovimab OR 0.17 (95% CI 0.04–0.57) and CT-P59 OR 0.48 (95% CI 0.14–1.60). Only casirivimab-imdevimab was shown to have moderate certainty evidence for this outcome; others were rated lower due to small numbers of events. With an assumed hospitalization rate for COVID-19 of 2.1% [2], the number needed to treat (NNT) for casirivimab-imdevimab to reduce the risk of hospital admission was 67 (Calculated separate from publication; OR = 0.29, PEER = 0.021).Only casirivimab-imdevimab (ratio of means 0.72; 95% CI 0.58–0.92, moderate certainty) was shown to reduce duration of symptoms of non-severe COVID-19. Bamlanivimab (ratio of means 0.92; 95% CI 0.64–1.32, low certainty), bamlanivimab-etesevimab (ratio of means 0.89; 95% CI 0.68–1.16, moderate certainty), and CT-P59 (ratio of means 0.66; 95% CI 0.42–1.05, moderate certainty) did not reduce symptom duration.None of the mABs studied showed a difference in mortality for non-severe COVID-19: casirivimab-imdevimab OR 0.58 (95% CI 0.26–1.22), bamlanivimab OR 0.46 (95% CI 0.01–27.79), bamlanivimab-etesevimab OR 0.05 (95% CI 0.00–1.01), sotrovimab OR 0.33 (95% CI 0.01–10.16), CT-P59 OR 0.51 (95% CI 0.01–30.40). Non-severe disease has an inherently low risk of mortality, which may have impacted these outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".