SynthesisFrontiers in immunology2026
Immunogenicity, efficacy, and safety of different dose schedules of human papillomavirus vaccines: a Bayesian network meta-analysis of randomized controlled trials.
Synthesis in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: To enhance global vaccine coverage and reduce costs, Human papillomavirus (HPV) immunization schedules are shifting from the standard three-dose (3D) regimen toward reduced-dose (1D or 2D) schedules. We aimed to evaluate the comparative immunogenicity, efficacy, and safety of diverse dose schedules and vaccine types using a Bayesian network meta-analysis. Methods: Two reviewers independently searched PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), CNKI, and Wanfang Data from inception to February 15, 2026, for randomized controlled trials (RCTs) evaluating different dose schedules of HPV vaccines in females aged 9-26 years. Primary outcomes were HPV-16/18 Seroconversion rates (SCR) and 6-month Persistent infection (PI). A Bayesian random-effects model was constructed using the multinma package in R, and treatments were ranked using the Surface Under the Cumulative Ranking (SUCRA) values. Results: For immunogenicity, the 9v-3D regimen demonstrated the highest SCR compared with placebo (OR 62.45, 95% CrI 15.20-158.30; SUCRA 0.96). However, these large effect estimates are largely driven by near-zero events in placebo arms. Regarding protective efficacy against PI, while 3-dose regimens ranked highest (9v-3D SUCRA 0.95; 2v-3D SUCRA 0.89), single-dose schedules (1D) maintained clinically significant protection (e.g., 2v-1D vs. placebo: OR 0.32, 95% CrI 0.07-0.96; SUCRA 0.61). Safety rankings identified 1D schedules as having the lowest risk of injection-site pain (SUCRA: 2v-1D 88.0%, 9v-1D 82.0%). Subgroup analysis suggested comparable efficacy of 2-dose regimens in adolescents aged 9-14 years compared to the standard 3D regimen (P-interaction = 0.04). Conclusions: Although reduced-dose schedules induce lower antibody titers than the standard 3-dose regimen, they provide robust protective efficacy against persistent HPV infection with a superior safety profile. Our findings support the widespread adoption of 2-dose schedules in adolescents and suggest that a single-dose strategy is a viable alternative in resource-constrained settings to accelerate the elimination of cervical cancer. However, given the surrogate nature of the study endpoints and the limitations of network meta-analysis for establishing non-inferiority, cautious interpretation of these results is warranted, and further long-term clinical endpoint data are needed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.