Context Although factorial trials have become common, standards for the analysis
and reporting of such trials have not been established and, despite concerns
about the possibility of unrecognized interactions between therapies in factorial
trials, the magnitude of this potential problem is unknown.
Objective To examine the rationale, methods, and analysis of randomized factorial
Data Sources and Study Selection We searched MEDLINE, EMBASE, and the Cochrane Controlled Trials Register
using the terms factorial, interaction, 2 × 2, 2 by 2,
and incremental to identify factorial randomized
trials published from January 2000 to July 2002. To identify trials missed
by the electronic search, we performed a hand search of English-language trials
in a defined topic area (using the term myocardial ischemia
[exp]) listed in MEDLINE (1966-2002), EMBASE (1980-2002), and the Cochrane
Controlled Trials Register, as well as all trials in any topic area published
in December 2000, excluding trials reporting only continuous surrogate end
points. The final set of 33 eligible publications described 29 unique trials.
Data Extraction Two investigators independently identified factorial trials, generated
a list of items affecting validity of results, and abstracted these items
from each trial.
Data Synthesis The sensitivity of electronic searching for identifying factorial trials
was 76%. Our 3-pronged search strategy identified 44 factorial trials with
clinically important binary outcomes: 36 (82%) were done for reasons of efficiency
(testing 2 interventions in the same patient population), and 8 (18%) were
done to assess the incremental benefits of combining the 2 treatments. All
but 1 of the trials reported treatment effects by comparing all patients who
received treatment A (ie, those receiving either A alone or both A and B)
vs all those not receiving treatment A (ie, those receiving either B alone
or neither A nor B). Twenty-nine of the 44 trials (66%) reported the data
from each of the treatment groups separately; 26 trials (59%) reported testing
for interactions between the treatments. Only 2 of 31 (6%) comparisons demonstrated
a statistically significant interaction between the 2 treatments.
Conclusions Accurate interpretation of factorial trials depends on the transparent
reporting of data for each treatment cell. Despite concerns about unrecognized
interactions, our findings suggest that investigators are appropriately restricting
their use of the factorial design to those situations in which 2 (or more)
treatments do not have the potential for substantive interaction.