Trial reportNature communications2018
Refined efficacy estimates of the Sanofi Pasteur dengue vaccine CYD-TDV using machine learning.
Trial report in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- Antibody-Dependent Enhancement in Flavivirus Infections: From Fc Receptor Signaling to Vaccine and Therapeutic Design.Viruses · 2026Review
- Assessing the impact of intervention strategies on dengue dynamics in Shenzhen, China.PLoS neglected tropical diseases · 2026Article
- Efficacy, public health impact and optimal use of the Takeda dengue vaccine.Nature medicine · 2025Article
- A scoping review of artificial intelligence applications in clinical trial risk assessment.NPJ digital medicine · 2025Article
- Facing the escalating burden of dengue: Challenges and perspectives.PLOS global public health · 2023Review
- Hit-to-Lead Short Peptides against Dengue Type 2 Envelope Protein: Computational and Experimental Investigations.Molecules (Basel, Switzerland) · 2022Article
- The Importance of Nanocarrier Design and Composition for an Efficient Nanoparticle-Mediated Transdermal Vaccination.Vaccines · 2021Review
- Article
- Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.PloS one · 2021Article
- Functional Profiling of Antibody Immune Repertoires in Convalescent Zika Virus Disease Patients.Frontiers in immunology · 2021Article
- Case Fatality Ratio Estimates for the 2013-2016 West African Ebola Epidemic: Application of Boosted Regression Trees for Imputation.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2020Article
- Cross-serotype interactions and disease outcome prediction of dengue infections in Vietnam.Scientific reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
CYD-TDV is the first licensed dengue vaccine for individuals 9-45 (or 60) years of age. Using 12% of the subjects enroled in phase-2b and phase-3 trials for which baseline serostatus was measured, the vaccine-induced protection against virologically confirmed dengue during active surveillance (0-25 months) was found to vary with prior exposure to dengue. Because age and dengue exposure are highly correlated in endemic settings, refined insight into how efficacy varies by serostatus and age is essential to understand the increased risk of hospitalisation observed among vaccinated individuals during the long-term follow-up and to develop safe and effective vaccination strategies. Here we apply machine learning to impute the baseline serostatus for subjects with post-dose 3 titres but missing baseline serostatus. We find evidence for age dependence in efficacy independent of serostatus and estimate that among 9-16 year olds, CYD-TDV is protective against serotypes 1, 3 and 4 regardless of baseline serostatus.
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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.