Donald Berry1, J Kyle Wathen, Margaret Newell. 1. Department of Biostatistics, University of Texas, MD Anderson Cancer Center, Houston, TX, USA. dberry@mdanderson.org.
Abstract
CONTEXT: The strength and relevance of a meta-analysis depends on the validity of the statistical methods used. Of special importance is appropriately assessing different sources of variability. Many studies including meta-analyses have evaluated the efficacy and safety of vitamin E and have yielded varying results. Illuminating and resolving these disparities requires addressing study variability and model uncertainty. OBJECTIVE: To describe Bayesian meta-analysis methods for combining data from clinical trials, using recent studies that analyzed the relationship between vitamin E dose and all-cause mortality. DATA SOURCES: Studies used in a previously published meta-analysis appended by studies identified by a search of MEDLINE from August 2004 to December 2005 using the MeSH terms vitamin e and alpha tocopherol. INCLUSION CRITERIA: men and nonpregnant women; use of vitamin E alone or in combination with other vitamins or minerals; random allocation of participants to either vitamin E or a placebo or other control group; intervention and follow-up duration greater than 1 year; 10 or more deaths. DATA EXTRACTION: Independent data extraction by one author was reviewed and confirmed by a second author. Corresponding authors of the original publications were contacted when questions arose. DATA SYNTHESIS: Data collection included the number of patients and deaths, percent men, use of other vitamins or minerals, mean age, and length of follow-up. We combined study results using Bayesian hierarchical model averaging. Analyses used Markov chain Monte Carlo computational techniques. CONCLUSIONS: Vitamin E intake is unlikely to affect mortality regardless of dose. The Bayesian meta-analyses presented here are ideal for incorporating disparate sources of variability, including trial effect and model uncertainty.
CONTEXT: The strength and relevance of a meta-analysis depends on the validity of the statistical methods used. Of special importance is appropriately assessing different sources of variability. Many studies including meta-analyses have evaluated the efficacy and safety of vitamin E and have yielded varying results. Illuminating and resolving these disparities requires addressing study variability and model uncertainty. OBJECTIVE: To describe Bayesian meta-analysis methods for combining data from clinical trials, using recent studies that analyzed the relationship between vitamin E dose and all-cause mortality. DATA SOURCES: Studies used in a previously published meta-analysis appended by studies identified by a search of MEDLINE from August 2004 to December 2005 using the MeSH terms vitamin e and alpha tocopherol. INCLUSION CRITERIA: men and nonpregnant women; use of vitamin E alone or in combination with other vitamins or minerals; random allocation of participants to either vitamin E or a placebo or other control group; intervention and follow-up duration greater than 1 year; 10 or more deaths. DATA EXTRACTION: Independent data extraction by one author was reviewed and confirmed by a second author. Corresponding authors of the original publications were contacted when questions arose. DATA SYNTHESIS: Data collection included the number of patients and deaths, percent men, use of other vitamins or minerals, mean age, and length of follow-up. We combined study results using Bayesian hierarchical model averaging. Analyses used Markov chain Monte Carlo computational techniques. CONCLUSIONS:Vitamin E intake is unlikely to affect mortality regardless of dose. The Bayesian meta-analyses presented here are ideal for incorporating disparate sources of variability, including trial effect and model uncertainty.
Authors: R J Kryscio; E L Abner; F A Schmitt; P J Goodman; M Mendiondo; A Caban-Holt; B C Dennis; M Mathews; E A Klein; J J Crowley Journal: J Nutr Health Aging Date: 2013-01 Impact factor: 4.075
Authors: Juan L Navia; Tim Byers; Darinka Djordjevic; Eric Hentges; Janet King; David Klurfeld; Craig Llewellyn; John Milner; Daniel Skrypec; Douglas Weed Journal: Crit Rev Food Sci Nutr Date: 2010 Impact factor: 11.176
Authors: Mary E Rinella; Zurabi Lominadze; Rohit Loomba; Michael Charlton; Brent A Neuschwander-Tetri; Stephen H Caldwell; Kris Kowdley; Stephen A Harrison Journal: Therap Adv Gastroenterol Date: 2016-01 Impact factor: 4.409