TY  - JOUR
T1  - COnfounding of subgroup analyses in randomized data
AU  - Groenwold RH, Donders AT, van der Heijden GG, Hoes AW, Rovers MM
Y1  - 2009/09/12
N1  - 10.1001/archinternmed.2009.250
JO  - Archives of Internal Medicine
SP  - 1532
EP  - 1534
VL  - 169
IS  - 16
N2  - 
Randomized controlled trials (RCTs) are considered the paradigm to study effects of medical interventions because randomization (theoretically) results in comparability of study groups.1- 2 Confounding is therefore considered a nonissue in RCTs. Nevertheless, effects that are estimated within subgroups of RCTs can be confounded. This argument might seem rather obvious because the issue is just elementary epidemiology, but it has not received adequate attention (ie, minimal or no discussion on this issue is found in various standard texts on clinical trials). Confounding of subgroup effects has mainly been described in relation to individual patient data (IPD) meta-analyses.3- 4 However, proposed methods to control for such confounding (ie, the so-called 2-stage approach) fail, as illustrated by the example described herein, which exemplifies confounding of subgroup effects and demonstrates how to adjust for it.

SN  - 0003-9926
M3  - doi: 10.1001/archinternmed.2009.250
UR  - http://dx.doi.org/10.1001/archinternmed.2009.250
ER  -