A systematic literature review and network meta-analysis feasibility study to assess the comparative efficacy and comparative effectiveness of pneumococcal conjugate vaccines
Bibliographic record
Abstract
Background: No head-to-head studies are currently available comparing pneumococcal non-typeable Haemophilus influenzae protein D conjugate vaccine (PHiD-CV) with 13-valent pneumococcal conjugate vaccine (PCV-13). This study explored the feasibility of using network meta-analysis (NMA) to conduct an indirect comparison of the relative efficacy or effectiveness of the two vaccines.Methods: A systematic literature search was conducted for published randomized controlled trials (RCTs) and non-RCT studies reporting data on vaccine efficacy or effectiveness against invasive pneumococcal disease in children aged <5 years receiving 7-valent pneumococcal conjugate vaccine (PCV-7), PHiD-CV or PCV-13. Study quality was evaluated using published scales. NMA feasibility was assessed by considering whether a connected network could be constructed by examining published studies for differences in study or patient characteristics that could act as potential treatment effect modifiers or confounding variables.Results: A total of 26 publications were included; 2 RCTs (4 publications), 7 indirect cohort studies, and 14 case-control studies (15 publications). Study quality was generally good. The RCTs could not be connected in a network as there was no common comparator. The studies differed considerably in design, dose number, administration schedules, and subgroups analyzed. Reporting of exposure status and subject characteristics was inconsistent.Conclusion: NMA to compare the relative efficacy or effectiveness of PHiD-CV and PCV-13 is not feasible on the current evidence base, due to the absence of a connected network across the two RCTs and major heterogeneity between studies. NMA may be possible in future if sufficient RCTs become available to construct a connected network.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.072 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".