Antibody therapies for treatment of non-severe COVID-19
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».