Healthy Skepticism Library item: 8003

Warning: This library includes all items relevant to health product marketing that we are aware of regardless of quality. Often we do not agree with all or part of the contents.

Publication type: Journal Article

D’agostino RB, D’agostino RB.
Estimating Treatment Effects Using Observational Data
JAMA 2007 Jan 17; 297:(3):314-316
http://jama.ama-assn.org/cgi/content/full/297/3/314

Abstract:

The randomized clinical trial (RCT) is the ideal method for measuring treatment effects. Participants in clinical trials are randomly assigned to a treatment or control group. Randomization reduces biases by making treatment and control groups “equal with respect to all features,” except the treatment assignment. When randomization is performed correctly, differences in efficacy found by statistical comparisons can be attributed to the difference between the treatment and control.1

However, the RCT does not necessarily provide the final answer to treatment effectiveness, as there are many restrictions that limit generalizability. For example, RCTs are often restricted to patients with limited disease, comorbidity, and concomitant medications. Thus, RCTs generally demonstrate efficacy rather than effectiveness, where efficacy is the treatment effect under the restricted conditions of the RCT and effectiveness is the treatment effect under the conditions of usual practice.1

Observational, . . .