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Risk and treatment effect heterogeneity: re-analysis of individual participant data from 32 large clinical trials.
Pubmed ID: 27375287
Pubmed Central ID: PMC5841614
Journal: International journal of epidemiology
Publication Date: Dec. 1, 2016
MeSH Terms: Humans, Risk Factors, Logistic Models, Randomized Controlled Trials as Topic, Data Interpretation, Statistical, Risk Assessment, Proportional Hazards Models, Therapeutics
Grants: U01 NS086294, UL1 TR001064
Authors: Kent DM, Hayward RA, Altman DG, Nelson J, Dahabreh IJ, Rothwell PM
Cite As: Kent DM, Nelson J, Dahabreh IJ, Rothwell PM, Altman DG, Hayward RA. Risk and treatment effect heterogeneity: re-analysis of individual participant data from 32 large clinical trials. Int J Epidemiol 2016 Dec 1;45(6):2075-2088.
Studies:
- Action to Control Cardiovascular Risk in Diabetes (ACCORD)
- Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT)
- Aspirin-Myocardial Infarction Study (AMIS)
- Atrial Fibrillation Follow-Up Investigation of Rhythm Management (AFFIRM)
- Beta-Blocker Evaluation in Survival Trial (BEST)
- Bypass Angioplasty Revascularization Investigation (BARI)
- Cardiac Arrhythmia Suppression Trial (CAST)
- Digitalis Investigation Group (DIG)
- Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD)
- Hypertension Detection and Follow-Up Program (HDFP)
- Lipid Research Clinics (LRC) Coronary Primary Prevention Trial (CPPT)
- Magnesium in Coronaries (MAGIC)
- Multiple Risk Factor Intervention Trial for the Prevention of Coronary Heart Disease (MRFIT)
- Occluded Artery Trial (OAT)
- Prevention of Events With Angiotensin-Converting Enzyme Inhibitor Therapy (PEACE)
- Resuscitation Outcomes Consortium (ROC) Hypertonic Saline Trial Shock Study (HS) and Traumatic Brain Injury Study (TBI)
- Studies of Left Ventricular Dysfunction (SOLVD)
- Systolic Hypertension in the Elderly Program (SHEP)
- Thrombolysis in Myocardial Ischemia Trial II (TIMI II)
Abstract
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 the interpretation of trial results. METHODS: We developed risk models using Cox or logistic regression on a set of large publicly available randomized controlled trials (RCTs). We evaluated risk heterogeneity using the extreme quartile risk ratio (EQRR, the ratio of outcome rates in the lowest risk quartile to that in the highest) and skewness using the median to mean risk ratio (MMRR, the ratio of risk in the median risk patient to the average). We also examined heterogeneity of treatment effects (HTE) across risk strata. RESULTS: We describe 39 analyses using data from 32 large trials, with event rates across studies ranging from 3% to 63% (median = 15%, 25th-75th percentile = 9-29%). C-statistics of risk models ranged from 0.59 to 0.89 (median = 0.70, 25th-75th percentile = 0.65-0.71). The EQRR ranged from 1.8 to 50.7 (median = 4.3, 25th-75th percentile = 3.0-6.1). The MMRR ranged from 0.4 to 1.0 (median = 0.86, 25th-75th percentile = 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 to 28.3% (median = 5.1%; 25th-75th percentile = 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 analyses are feasible and may be clinically informative, particularly when the outcome is predictable and uncommon.