PMID- 36798386
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231130
DP  - 2023 Feb 9
TI  - Incorporating data from multiple endpoints in the analysis of clinical trials: 
      example from RSV vaccines.
LID - 2023.02.07.23285596 [pii]
LID - 10.1101/2023.02.07.23285596 [doi]
AB  - BACKGROUND: To achieve licensure, interventions typically must demonstrate 
      efficacy against a primary outcome in a randomized clinical trial. However, 
      selecting a single primary outcome a priori is challenging. Incorporating data 
      from multiple and related outcomes might help to increase statistical power in 
      clinical trials. Inspired by real-world clinical trials of interventions against 
      respiratory syncytial virus (RSV), we examined methods for analyzing data on 
      multiple endpoints. METHOD: We simulated data from three different populations in 
      which the efficacy of the intervention and the correlation among outcomes varied. 
      We developed a novel permutation-based approach that represents a weighted 
      average of individual outcome test statistics ( varP ) to evaluate intervention 
      efficacy in a multiple endpoint analysis. We compared the power and type I error 
      rate of this approach to two alternative methods: the Bonferroni correction ( 
      bonfT ) and another permutation-based approach that uses the minimum P-value 
      across all test statistics ( minP ). RESULTS: When the vaccine efficacy against 
      different outcomes was similar, VarP yielded higher power than bonfT and minP; in 
      some scenarios the improvement in power was substantial. In settings where 
      vaccine efficacy was notably larger against one endpoint compared to the others, 
      all three methods had similar power. CONCLUSIONS: Analyzing multiple endpoints 
      using a weighted permutation method can increase power while controlling the type 
      I error rate in settings where outcomes share similar characteristics, like RSV 
      outcomes. We developed an R package, PERMEATE , to guide selection of the most 
      appropriate method for analyzing multiple endpoints in clinical trials.
FAU - Prunas, Ottavia
AU  - Prunas O
AD  - Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, 
      Yale School of Public Health, Yale University; New Haven, CT USA.
FAU - Willemsen, Joukje E
AU  - Willemsen JE
AD  - Centre for Translational Immunology, University Medical Center Utrecht; Utrecht, 
      The Netherlands.
AD  - Division of Infectious Diseases, Department of Pediatrics, University Medical 
      Center Utrecht, Utrecht, The Netherlands.
FAU - Bont, Louis
AU  - Bont L
AD  - Division of Infectious Diseases, Department of Pediatrics, University Medical 
      Center Utrecht, Utrecht, The Netherlands.
FAU - Pitzer, Virginia E
AU  - Pitzer VE
AD  - Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, 
      Yale School of Public Health, Yale University; New Haven, CT USA.
FAU - Warren, Joshua L
AU  - Warren JL
AD  - Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, 
      Yale School of Public Health, Yale University; New Haven, CT USA.
AD  - Department of Biostatistics, Yale School of Public Health, Yale University; New 
      Haven, CT USA.
FAU - Weinberger, Daniel M
AU  - Weinberger DM
AD  - Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, 
      Yale School of Public Health, Yale University; New Haven, CT USA.
LA  - eng
GR  - INV-017940/GATES/Bill & Melinda Gates Foundation/United States
GR  - R01 AI137093/AI/NIAID NIH HHS/United States
GR  - UL1 TR001863/TR/NCATS NIH HHS/United States
PT  - Preprint
DEP - 20230209
PL  - United States
TA  - medRxiv
JT  - medRxiv : the preprint server for health sciences
JID - 101767986
UIN - Epidemiology. 2023 Oct 02;:. PMID: 37793120
PMC - PMC9934779
EDAT- 2023/02/18 06:00
MHDA- 2023/02/18 06:01
PMCR- 2023/02/16
CRDT- 2023/02/17 02:06
PHST- 2023/02/17 02:06 [entrez]
PHST- 2023/02/18 06:00 [pubmed]
PHST- 2023/02/18 06:01 [medline]
PHST- 2023/02/16 00:00 [pmc-release]
AID - 2023.02.07.23285596 [pii]
AID - 10.1101/2023.02.07.23285596 [doi]
PST - epublish
SO  - medRxiv [Preprint]. 2023 Feb 9:2023.02.07.23285596. doi: 
      10.1101/2023.02.07.23285596.