The Effect of Pandemic Prevalence on the Reported Efficacy of SARS-CoV-2 Vaccine Candidates: A Systematic Review and Meta-analysis
Notice bibliographique
Résumé
Abstract Importance The efficacy of SARS-CoV-2 vaccine candidates reported in Phase 3 trials varies from ∼45% to ∼95%. It is important to explain the reasons for this heterogeneity. Objective To test the hypothesis that the efficacy of SARS-CoV-2 vaccine candidates falls with increasing prevalence of the COVID-19 pandemic. Data Sources ClinicalTrials.gov , WHO, McGill and LSHTM trackers of COVID-19 candidate vaccines, peer reviewed publications, and press releases were searched until March 31 st , 2021. Study Selection All RCTs reporting efficacy outcomes from Phase 3 trials till March 31 st , 2021 were included. Of the 11 vaccine candidates that had started their Phase 3 trials by November 1, 2020. Phase 3 efficacy outcomes were available for 8 vaccine candidates. (PROSPERO CRD42021243121). Data Extraction and Synthesis Both authors independently extracted the data required from identified sources, using PRISMA guidelines. The analysis included all RCTs reported in peer reviewed publications and publicly available sources. A random effects model with restricted maximum likelihood estimator was used to summarize the treatment effects. Cochrane Risk of Bias Assessment Tool was used to assess risk of bias. Certainty of evidence was assessed using the GRADE tool. Main Outcomes and Measures SARS-CoV-2 infections per protocol in vaccine and placebo groups, risk ratio, prevalence of the COVID-19 infection rate in the populations where the Phase 3 trials were conducted. Results 8 vaccine candidates had reported efficacy data from a total of 20 independent Phase 3 trials, representing a total of 221,968 subjects, 453 infections across the vaccinated groups and 1,554 infections across the placebo groups. The overall estimate of the risk-ratio is 0.24 (95% CI, 0.17-0.34, p < 0.01), with an I 2 statistic of 88.73%. The meta-regression analysis with pandemic prevalence as the moderator explains almost half the variance in risk ratios across trials (R 2 =49.06%, p<0.01). Conclusion and Relevance Pandemic prevalence explains almost half of the between-trial variance in reported efficacies. Efficacy of SARS-CoV-2 vaccine candidates declines as the pandemic prevalence increases. Key Points Question Does the prevalence of the COVID-19 pandemic explain the heterogeneity in efficacies reported across Phase 3 trials of SARS-CoV-2 vaccine candidates? Findings Almost 50% of the variance in efficacies reported across Phase 3 trials can be explained by differences in COVID-19 infection rate prevailing across trials. Efficacy of evaluated SARS-CoV-2 vaccine candidates falls significantly with increasing prevalence of the COVID-19 pandemic across trial sites. Meaning Efficacy of SARS-CoV-2 vaccine candidates needs to be interpreted in conjunction with the prevalence of the COVID-19 pandemic. Adjustment for location-level prevalence analysis would provide better insights into the efficacy results of Phase 3 trials.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,036 | 0,093 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,027 | 0,043 |
| Bibliométrie | 0,010 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 source (Gemma direct ou Codex distillé), 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 ».