Risk and treatment effect heterogeneity: re-analysis of individual participant data from 32 large clinical trials

Journal article

Background: Risk of the outcome is a mathematical determinant of the absolute treatment benefit of an intervention, yet this can vary substantially within a trial population, complicating interpretation of trial results.
Methods: We derived risk models using Cox or logistic regression on a set of large publically available RCTs. Risk heterogeneity was evaluated using the extreme quartile risk ratio (EQRR, the ratio of outcome rates in the lowest risk quartile to that in the highest). Skewness was evaluated with median to mean risk ratio (MMRR, the ratio of risk in the median risk patient to the average). Heterogeneity of treatment effect (HTE) across risk strata was also examined.
Results: We describe 39 analyses using data from 32 large trials, with event rates across studies ranging from 3%-63% (median=15%, interquartile range [IQR]=9%-29%). C-statistics of risk models ranged from 0.59-0.89 (median=0.70, IQR=0.65-0.71). The EQRR ranged from 1.9- 35.2 (median=4.0, IQR=3.1-5.4). The MMRR ranged from 0.4-1.0 (median=0.86, IQR=0.80-0.92). EQRRs were predictably higher and MMRRs predictably lower as the C-statistic increased or the overall outcome incidence decreased. Among 18 comparisons with a significant overall treatment effect, there was a significant interaction between treatment and baseline risk on the proportional scale in only one. The difference in the absolute risk reduction between extreme risk quartiles ranged from -3.2-28.3% (median=5.1%; IQR=0.3-10.9).
Conclusions: There is typically substantial variation in outcome risk in clinical trials, commonly leading to clinically significant differences in absolute treatment effects. Most patients have outcome risks lower than the trial average reflected in the summary result. Risk stratified trial 3 analyses are feasible and may be clinically informative, particularly when the outcome is predictable and uncommon.

Authors: Kent, D; Nelson, J; Altman, D; Hayward, R; Dahabreh, I

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: International Journal of Epidemiology
• Volume: 45
• Issue: 6
• Pages: 2075-2088
• Publication date: 2016-07-03
• Acceptance date: 2016-04-18
• DOI: 10.1093/ije/dyw118
• EISSN: 1464-3685
• ISSN: 0300-5771
• Keywords: Risk Prediction; Heterogeneity of Treatment Effect; Personalized Medicine; Subgroup Analysis; Patient-Centered Outcomes Research