Trivalent and quadrivalent seasonal influenza vaccine in adults aged 60 and older: a systematic review and network meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To compare the efficacy of influenza vaccines of any valency for adults 60 years and older. DESIGN AND SETTING: Systematic review with network meta-analysis (NMA) of randomised controlled trials (RCTs). MEDLINE, EMBASE, JBI Evidence-Based Practice (EBP) Database, PsycINFO, and Cochrane Evidence -Based Medicine database were searched from inception to 20 June 20, 2022. Two reviewers screened, abstracted, and appraised articles (Cochrane Risk of Bias (ROB) 2.0 tool) independently. We assessed certainty of findings using Confidence in Network Meta-Analysis and Grading of Recommendations, Assessment, Development and Evaluations approaches. We performed random-effects meta-analysis and network meta-analysis (NMA), and estimated odds ratios (ORs) for dichotomous outcomes and incidence rate ratios (IRRs) for count outcomes along with their corresponding 95% confidence intervals (CIs) and prediction intervals. PARTICIPANTS: Older adults (≥60 years old) receiving an influenza vaccine licensed in Canada or the USA (vs placebo, no vaccine, or any other licensed vaccine), at any dose. MAIN OUTCOME MEASURES: Laboratory-confirmed influenza (LCI) and influenza-like illness (ILI). Secondary outcomes were the number of vascular adverse events, hospitalisation for acute respiratory infection (ARI) and ILI, inpatient hospitalisation, emergency room (ER) visit for ILI, outpatient visit, and mortality, among others. RESULTS: We included 41 RCTs and 15 companion reports comprising 8 vaccine types and 206 032 participants. Vaccines may prevent LCI compared with placebo, with high-dose trivalent inactivated influenza vaccine (IIV3-HD) (NMA: 9 RCTs, 52 202 participants, OR 0.23, 95% confidence interval (CI) (0.11 to 0.51), low certainty of evidence) and recombinant influenza vaccine (RIV) (OR 0.25, 95%CI (0.08 to 0.73), low certainty of evidence) among the most efficacious vaccines. Standard dose trivalent IIV3 (IIV3-SD) may prevent ILI compared with placebo, but the result was imprecise (meta-analysis: 2 RCTs, 854 participants, OR 0.39, 95%CI (0.15 to 1.02), low certainty of evidence). Any HD was associated with prevention of ILI compared with placebo (NMA: 9 RCTs, 65 658 participants, OR 0.38, 95%CI (0.15 to 0.93)). Adjuvanted quadrivalent IIV (IIV4-Adj) may be associated with the least vascular adverse events, but the results were very uncertain (NMA: eight 8 RCTs, 57 677 participants, IRR 0.18, 95%CI (0.07 to 0.43), very low certainty of evidence). RIV on all-cause mortality may be comparable to placebo (NMA: 20 RCTs, 140 577 participants, OR 1.01, 95%CI (0.23 to 4.49), low certainty of evidence). CONCLUSIONS: This systematic review demonstrated efficacy associated with IIV3-HD and RIV vaccines in protecting older persons against LCI. RIV vaccine may reduce all-cause mortality when compared with other vaccines, but the evidence is uncertain. Differences in efficacy between influenza vaccines remain uncertain with very low to moderate certainty of evidence. PROSPERO REGISTRATION NUMBER: CRD42020177357.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: yes | Meta-analysis | high |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.026 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.043 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".