Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Julie Dudášová"'
Publikováno v:
npj Vaccines, Vol 9, Iss 1, Pp 1-11 (2024)
Abstract Understanding potential differences in vaccine-induced protection between demographic subgroups is key for vaccine development. Vaccine efficacy evaluation across these subgroups in phase 2b or 3 clinical trials presents challenges due to la
Externí odkaz:
https://doaj.org/article/61632a4fc2954cfe86bdfc29ff38b87d
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Background Vaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other subject-specific characteristics evaluated as baseline covariates. Understanding the effect of covariates
Externí odkaz:
https://doaj.org/article/02fd0993cd9e481f9c476bec0b21cf57
Autor:
Julie Dudášová, Regina Laube, Chandni Valiathan, Matthew C. Wiener, Ferdous Gheyas, Pavel Fišer, Justina Ivanauskaite, Frank Liu, Jeffrey R. Sachs
Publikováno v:
npj Vaccines, Vol 6, Iss 1, Pp 1-14 (2021)
Abstract Vaccine efficacy is often assessed by counting disease cases in a clinical trial. A new quantitative framework proposed here (“PoDBAY,” Probability of Disease Bayesian Analysis), estimates vaccine efficacy (and confidence interval) using
Externí odkaz:
https://doaj.org/article/415ecc810f6745a2bf96f13f021d869a
Autor:
Daniel I. S. Rosenbloom, Julie Dudášová, Casey Davis, Radha A. Railkar, Nitin Mehrotra, Jeffrey R. Sachs
Publikováno v:
Vaccines, Vol 11, Iss 9, p 1501 (2023)
In vaccine efficacy trials, inaccurate counting of infection cases leads to systematic under-estimation—or “dilution”—of vaccine efficacy. In particular, if a sufficient fraction of observed cases are false positives, apparent efficacy will b
Externí odkaz:
https://doaj.org/article/9338473b398c4b5fa038fff778f3ca24