Do observational studies using propensity score methods agree with randomized trials? A systematic comparison of studies on acute coronary syndromes.

AIMS: Randomized controlled trials (RCTs) are the gold standard for assessing the efficacy of therapeutic interventions because randomization protects from biases inherent in observational studies. Propensity score (PS) methods, proposed as a potential solution to confounding of the treatment-outcome association, are widely used in observational studies of therapeutic interventions for acute coronary syndromes (ACS). We aimed to systematically assess agreement between observational studies using PS methods and RCTs on therapeutic interventions for ACS. METHODS AND RESULTS: We searched for observational studies of interventions for ACS that used PS methods to estimate treatment effects on short- or long-term mortality. Using a standardized algorithm, we matched observational studies to RCTs based on patients' characteristics, interventions, and outcomes ('topics'), and we compared estimates of treatment effect between the two designs. When multiple observational studies or RCTs were identified for the same topic, we performed a meta-analysis and used the summary relative risk for comparisons. We matched 21 observational studies investigating 17 distinct clinical topics to 63 RCTs (median = 3 RCTs per observational study) for short-term (7 topics) and long-term (10 topics) mortality. Estimates from PS analyses differed statistically significantly from randomized evidence in two instances; however, observational studies reported more extreme beneficial treatment effects compared with RCTs in 13 of 17 instances (P = 0.049). Sensitivity analyses limited to large RCTs, and using alternative meta-analysis models yielded similar results. CONCLUSION: For the treatment of ACS, observational studies using PS methods produce treatment effect estimates that are of more extreme magnitude compared with those from RCTs, although the differences are rarely statistically significant.

Meta-analysis: statin therapy does not alter the association between low levels of high-density lipoprotein cholesterol and increased cardiovascular risk.

BACKGROUND: Low levels of high-density lipoprotein cholesterol (HDL-C) are associated with an increased risk for myocardial infarction (MI). Although statins reduce the risk for MI, most cardiovascular events still occur despite statin treatment. PURPOSE: Using meta-analysis of large randomized, controlled trials (RCTs) of statins to determine whether statins alter the relationship between HDL-C level and MI. DATA SOURCES: MEDLINE search to February 2010, ClinicalTrials.gov, and reference lists from eligible studies. STUDY SELECTION: English-language RCTs of statin-treated patients versus control participants with 1000 or more person-years of follow-up and reported HDL-C levels and MI. DATA EXTRACTION: Two independent investigators extracted data from eligible RCTs. DATA SYNTHESIS: Twenty eligible RCTs were identified (543,210 person-years of follow-up and 7838 MIs). After adjustment for on-treatment LDL-C levels, age, hypertension, diabetes, and tobacco use, there was a significant inverse association between HDL-C levels and risk for MI in statin-treated patients and control participants. In Poisson meta-regressions, every 0.26-mmol/L (10-mg/dL) decrease in HDL-C was associated with 7.1 (95% CI, 6.8 to 7.3) and 8.3 (CI, 8.1 to 8.5) more MIs per 1000 person-years in statin-treated patients and control participants, respectively. The inverse association between HDL-C levels and MI did not differ between statin-treated patients and control participants (P= 0.57). LIMITATION: The observed associations may be explained by unmeasured confounding and do not imply causality in the relationship between HDL-C level and cardiovascular risk. CONCLUSION: Statins do not alter the relationship between HDL-C level and cardiovascular risk, such that low levels of HDL-C remain significantly and independently associated with increased risk despite statin treatment. The remaining risk seen in statin-treated patients may be partly explained by low HDL-C levels or other factors associated with low levels of HDL-C. PRIMARY FUNDING SOURCE: None.

Baseline and on-treatment high-density lipoprotein cholesterol and the risk of cancer in randomized controlled trials of lipid-altering therapy.

OBJECTIVES: We sought to examine the relationship between high-density lipoprotein cholesterol (HDL-C) levels and the risk of the development of cancer in large randomized controlled trials (RCTs) of lipid-altering interventions. BACKGROUND: Epidemiologic data demonstrate an inverse relationship between serum total cholesterol levels and incident cancer. We recently reported that lower levels of low-density lipoprotein cholesterol are associated with a significantly higher risk of incident cancer in a meta-analysis of large RCTs of statin therapy. However, little is known about the relationship between HDL-C levels and cancer risk. METHODS: A systematic MEDLINE search identified lipid intervention RCTs with >or=1,000 person-years of follow-up, providing baseline HDL-C levels and rates of incident cancer. Using random-effects meta-regressions, we evaluated the relationship between baseline HDL-C and incident cancer in each RCT arm. RESULTS: A total of 24 eligible RCTs were identified (28 pharmacologic intervention arms and 23 control arms), with 625,477 person-years of follow-up and 8,185 incident cancers. There was a significant inverse association between baseline HDL-C levels and the rate of incident cancer (p = 0.018). The inverse association persisted after adjusting for baseline low-density lipoprotein cholesterol, age, body mass index (BMI), diabetes, sex, and smoking status, such that for every 10-mg/dl increment in HDL-C, there was a 36% (95% confidence interval: 24% to 47%) relatively lower rate of the development of cancer (p < 0.001). CONCLUSIONS: There is a significant inverse association between HDL-C and the risk of incident cancer that is independent of LDL-C, age, BMI, diabetes, sex, and smoking.

Peripheral arterial tonometry for risk stratification in men with coronary artery disease.

BACKGROUND: Coronary artery disease (CAD) risk is not fully revealed by traditional risk factors. Identification of a simple, noninvasive tool that allows for detection of high-risk CAD patients and can be applied in large populations and clinical settings would prove valuable. HYPOTHESIS: We sought to test the hypothesis that peripheral arterial tonometry (PAT) would be associated with residual risk in men with CAD. METHODS: In this study, finger PAT was used to measure pulse wave amplitude (PWA) during reactive hyperemia (RH) and taken as a measure of microvascular endothelial function in 42 men with stable CAD and well controlled low-density lipoprotein cholesterol (LDL-C) levels. Plasma levels of high-sensitivity C-reactive protein (hs-CRP) and lipoprotein-associated phospholipase A2 (Lp-PLA(2)) were measured and used to reclassify men into high-risk (elevated hs-CRP and Lp-PLA(2)), moderate-risk (either elevated hs-CRP or Lp-PLA(2)), or low-risk (low hs-CRP and Lp-PLA(2)) groups. RESULTS: PWA-RH was significantly lower in the high-risk group (1.3 +/- 0.04) compared to the moderate-risk (1.6 +/- 0.07, P < 0.05) and low-risk (2.0 +/- 0.1, P < 0.05) groups. According to binary logistic regression, PWA-RH was a significant predictor of high-risk status among men with CAD (P < 0.05). CONCLUSION: Measurement of peripheral microvascular endothelial function with PAT may be able to distinguish high-risk men from moderate- and low-risk men with stable CAD and well-controlled LDL-C levels and thus aid in residual risk stratification in this at risk cohort.

Extended-release niacin reduces LDL particle number without changing total LDL cholesterol in patients with stable CAD.

BACKGROUND: The importance of the number of circulating low-density lipoprotein (LDL) cholesterol particles, in addition to total LDL level, has been increasingly recognized. The effects of extended-release niacin (ERN) on LDL particle numbers have not been studied. OBJECTIVE: To evaluate ERN's effects on LDL particle numbers. METHODS: Fifty-four patients with stable coronary artery disease (CAD) and well-controlled LDL levels were randomly assigned to 3 months of ERN (1 g/day) or placebo in addition to their baseline medications. Lipoprotein particle number was analyzed by proton nuclear magnetic resonance spectroscopy at baseline and after 3 months. RESULTS: Compared to baseline, the addition of ERN had no significant effect on total LDL cholesterol levels; however, ERN decreased the number of medium and small LDL particles (P < .005). After 3 months, ERN decreased the number of medium and small LDL particles compared to placebo-treated patients (P < .05). ERN raised HDL cholesterol levels by 2.7%, significantly increased the number of large HDL particles (P < .001), and decreased the number of small HDL particles (P = .027) compared to placebo. There were no significant changes in lipid values or particle numbers in the placebo-treated patients. In patients with stable coronary artery disease and well-controlled LDL cholesterol levels, ERN reduced the number of circulating particles of the more atherogenic subtypes of LDL, despite having no effect on total LDL cholesterol levels. ERN also favorably altered the number of HDL particles. CONCLUSION: ERN-induced alterations in lipoprotein particle numbers may contribute to its anti-atherosclerotic effects, and these effects may not be evident from the standard lipid profile.