Heterogeneity of patients in clinical trials: Subgroup analysis and covariate adjustment in cardiovascular and neurosurgical trials

Randomized clinical trials (RCTs) are essential to evaluate the usefulness of treatments and interventions, and clearly influence clinical practice. Trials are often performed in heterogeneous populations, such as patients with traumatic brain injury (TBI), acute coronary syndromes (ACS), stroke and cancer. Patients are heterogeneous regarding to their characteristics, such as age, gender, or disease severity. Heterogeneity may produce imbalance in randomized groups with respect to prognosis, and may dilute the beneficial effect of treatments in some subgroups of patients. However, heterogeneity of patients offers some solutions to deal with these problems. Covariate adjustment and subgroup analysis are two methods used in the analysis phase of the trials. Covariate adjustment leads to adjusted estimates of treatment effects that relate to the “average” patient with a certain risk profile. It corrects for imbalance, and increases the statistical power to detect significant treatment effects. Subgroup analysis assesses differences in treatment effect across different subpopulations of patients.

• View at Worldcat

Free Full Text ( Final Version , 1mb )