Estimating treatment effects from observational data: dissonant and resonant notes from the SYMPHONY trials.

CAN OBSERVATIONAL DATA SUBSTITUTE FOR RANDOMized controlled trials for developing treatment recommendations and initiating public health interventions? This question arises from the article by Newby and colleagues on the early initiation of statins in patients with acute coronary syndromes (ACS), reported in this issue of THE JOURNAL. The authors present results from an observational cohort study that indicate no difference in mortality and cardiovascular outcomes among patients with ACS who initiated statin treatment prior to hospital discharge and patients who did not receive statins. Almost 2 million patients with ACS are discharged from US hospitals each year. Since these patients are at high risk for recurrent events, secondary prevention is an important medical challenge. Randomized clinical trials (RCTs) have shown the benefits of aspirin, -blockers, and clopidogrel in these patients. Furthermore, there is evidence that administration of these agents prior to hospital discharge reduces recurrent event rates. Large RCTs have indicated that initiation of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors (statins) months to years following an ACS event is effective for secondary prevention. Recently, attention has focused on the optimal time to commence statin therapy. Several observational studies, among them 2 large studies comprising some 40000 patients, found that early statin therapy was associated with lower rates of death. In addition, the results from 2 RCTs, although not definitive, yielded consistent results. Consequently, a strong momentum is building to recommend routine, early initiation of statin therapy in post-ACS patients. Indeed, such therapy is recommended in contemporary practice guidelines. The retrospective cohort study using data from the Sibrafiban vs Aspirin to Yield Maximum Protection From Ischemic Heart Events Post-acute Coronary Syndromes (SYMPHONY) ACS trials strikes a dissonant note. In contrast to the previous studies, the report by Newby et al indicates no benefit from early initiation of statin therapy for any clinical end point, except stroke, for which statins appeared protective. How should the results from the SYMPHONY populations be interpreted and how can the differences between this and the previously reported studies be explained? One possible reason for the surprising findings is that the fractions of patients in the 2 SYMPHONY trials for whom statins were started in the hospital as well as those for whom revascularization was performed were much larger than in the other 2 observational studies. Perhaps the analysis reported by Newby and colleagues signals that statins simply do not offer a significant additional benefit in the presence of revascularization therapy in relatively low-risk patients. Other possible explanations for the different results obtained by the various studies are measurement error and confounding. Any results, whether from observational studies or RCTs can be distorted by measurement error. Measurement error may have affected the ascertainment of statin use, the diagnosis of ACS, and all clinical covariates. Furthermore, observational studies are especially vulnerable to confounding. Although analytic techniques can address the control of measured confounders, unmeasured confounders remain an omnipresent threat to the validity of nonrandomized research. Mismeasurement of a confounder, such as low-density lipoprotein cholesterol (LDL-C) level, might not create a problem if the physician decided treatment based on the mismeasured variable. Nevertheless, any discrepancy between the value of a confounder used by the physician and that used in the analysis could lead to residual confounding. To overcome the lack of randomization in their cohort, Newby et al used propensity scores to account for imbalances in baseline characteristics. In the 2 other large observational studies on this issue available to date, propensity scores were also used. Propensity scores have become a popular tool in pharmacoepidemiology. Of particular con-