Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials

TY - JOUR

T1 - Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials

AU - Savović, Jelena

AU - Jones, Hayley E

AU - Altman, Douglas G

AU - Harris, Ross J

AU - Jüni, Peter

AU - Pildal, Julie

AU - Als-Nielsen, Bodil

AU - Balk, Ethan M

AU - Gluud, Christian

AU - Gluud, Lise Lotte

AU - Ioannidis, John P A

AU - Schulz, Kenneth F

AU - Beynon, Rebecca

AU - Welton, Nicky J

AU - Wood, Lesley

AU - Moher, David

AU - Deeks, Jonathan J

AU - Sterne, Jonathan A C

PY - 2012/9/18

Y1 - 2012/9/18

N2 - Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as "mortality," "other objective," "or subjective," and Bayesian hierarchical models were used to estimate associations of trial characteristics with average bias and between-trial heterogeneity. Intervention effect estimates seemed to be exaggerated in trials with inadequate or unclear (vs. adequate) random-sequence generation (ratio of odds ratios, 0.89 [95% credible interval {CrI}, 0.82 to 0.96]) and with inadequate or unclear (vs. adequate) allocation concealment (ratio of odds ratios, 0.93 [CrI, 0.87 to 0.99]). Lack of or unclear double-blinding (vs. double-blinding) was associated with an average of 13% exaggeration of intervention effects (ratio of odds ratios, 0.87 [CrI, 0.79 to 0.96]), and between-trial heterogeneity was increased for such studies (SD increase in heterogeneity, 0.14 [CrI, 0.02 to 0.30]). For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes.

AB - Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as "mortality," "other objective," "or subjective," and Bayesian hierarchical models were used to estimate associations of trial characteristics with average bias and between-trial heterogeneity. Intervention effect estimates seemed to be exaggerated in trials with inadequate or unclear (vs. adequate) random-sequence generation (ratio of odds ratios, 0.89 [95% credible interval {CrI}, 0.82 to 0.96]) and with inadequate or unclear (vs. adequate) allocation concealment (ratio of odds ratios, 0.93 [CrI, 0.87 to 0.99]). Lack of or unclear double-blinding (vs. double-blinding) was associated with an average of 13% exaggeration of intervention effects (ratio of odds ratios, 0.87 [CrI, 0.79 to 0.96]), and between-trial heterogeneity was increased for such studies (SD increase in heterogeneity, 0.14 [CrI, 0.02 to 0.30]). For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes.

KW - Bayes Theorem

KW - Bias (Epidemiology)

KW - Double-Blind Method

KW - Humans

KW - Meta-Analysis as Topic

KW - Odds Ratio

KW - Randomized Controlled Trials as Topic

KW - Research Design

U2 - 10.7326/0003-4819-157-6-201209180-00537

DO - 10.7326/0003-4819-157-6-201209180-00537

M3 - Journal article

C2 - 22945832

SN - 0003-4819

VL - 157

SP - 429

EP - 438

JO - Annals of Internal Medicine

JF - Annals of Internal Medicine

IS - 6

ER -