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Evolution of heterogeneity (I2) estimates and their 95% confidence intervals in large meta-analyses

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@article{8175fdb68319428ba55443ef718601e5,
title = "Evolution of heterogeneity (I2) estimates and their 95{\%} confidence intervals in large meta-analyses",
abstract = "Assessment of heterogeneity is essential in systematic reviews and meta-analyses of clinical trials. The most commonly used heterogeneity measure, I(2), provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error. Recent studies have raised concerns about the reliability of I(2) estimates, due to their dependence on the precision of included trials and time-dependent biases. Authors have also advocated use of 95{\%} confidence intervals (CIs) to express the uncertainty associated with I(2) estimates. However, no previous studies have explored how many trials and events are required to ensure stable and reliable I(2) estimates, or how 95{\%} CIs perform as evidence accumulates.",
author = "Kristian Thorlund and Georgina Imberger and Johnston, {Bradley C} and Michael Walsh and Tahany Awad and Lehana Thabane and Christian Gluud and Devereaux, {P J} and J{\o}rn Wetterslev",
year = "2012",
doi = "10.1371/journal.pone.0039471",
language = "English",
volume = "7",
pages = "e39471",
journal = "P L o S One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "7",

}

RIS

TY - JOUR

T1 - Evolution of heterogeneity (I2) estimates and their 95% confidence intervals in large meta-analyses

AU - Thorlund, Kristian

AU - Imberger, Georgina

AU - Johnston, Bradley C

AU - Walsh, Michael

AU - Awad, Tahany

AU - Thabane, Lehana

AU - Gluud, Christian

AU - Devereaux, P J

AU - Wetterslev, Jørn

PY - 2012

Y1 - 2012

N2 - Assessment of heterogeneity is essential in systematic reviews and meta-analyses of clinical trials. The most commonly used heterogeneity measure, I(2), provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error. Recent studies have raised concerns about the reliability of I(2) estimates, due to their dependence on the precision of included trials and time-dependent biases. Authors have also advocated use of 95% confidence intervals (CIs) to express the uncertainty associated with I(2) estimates. However, no previous studies have explored how many trials and events are required to ensure stable and reliable I(2) estimates, or how 95% CIs perform as evidence accumulates.

AB - Assessment of heterogeneity is essential in systematic reviews and meta-analyses of clinical trials. The most commonly used heterogeneity measure, I(2), provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error. Recent studies have raised concerns about the reliability of I(2) estimates, due to their dependence on the precision of included trials and time-dependent biases. Authors have also advocated use of 95% confidence intervals (CIs) to express the uncertainty associated with I(2) estimates. However, no previous studies have explored how many trials and events are required to ensure stable and reliable I(2) estimates, or how 95% CIs perform as evidence accumulates.

U2 - 10.1371/journal.pone.0039471

DO - 10.1371/journal.pone.0039471

M3 - Journal article

VL - 7

SP - e39471

JO - P L o S One

JF - P L o S One

SN - 1932-6203

IS - 7

ER -

ID: 36623744