Effect of smoking on comparative efficacy of antiplatelet agents: systematic review, meta-analysis, and indirect comparison

Objective: To evaluate whether smoking status is associated with the efficacy of antiplatelet treatment in the prevention of cardiovascular events. Design: Systematic review, meta-analysis, and indirect comparisons. Data sources Medline (1966 to present) and Embase (1974 to present), with supplementary searches in databases of abstracts from major cardiology conferences, the Cumulative Index to Nursing and Allied Health (CINAHL) and the CAB Abstracts databases, and Google Scholar. Study selection Randomized trials of clopidogrel, prasugrel, or ticagrelor that examined clinical outcomes among subgroups of smokers and nonsmokers. Data extraction Two authors independently extracted all data, including information on the patient populations included in the trials, treatment types and doses, definitions of clinical outcomes and duration of follow-up, definitions of smoking subgroups and number of patients in each group, and effect estimates and 95% confidence intervals for each smoking status subgroup. Results: Of nine eligible randomized trials, one investigated clopidogrel compared with aspirin, four investigated clopidogrel plus aspirin compared with aspirin alone, and one investigated double dose compared with standard dose clopidogrel; these trials include 74 489 patients, of whom 21 717 (29%) were smokers. Among smokers, patients randomized to clopidogrel experienced a 25% reduction in the primary composite clinical outcome of cardiovascular death, myocardial infarction, and stroke compared with patients in the control groups (relative risk 0.75, 95% confidence interval 0.67 to 0.83). In nonsmokers, however, clopidogrel produced just an 8% reduction in the composite outcome (0.92, 0.87 to 0.98). Two studies investigated prasugrel plus aspirin compared with clopidogrel plus aspirin, and one study investigated ticagrelor plus aspirin compared with clopidogrel plus aspirin. In smokers, the relative risk was 0.71 (0.61 to 0.82) for prasugrel compared with clopidogrel and 0.83 (0.68 to 1.00) for ticagrelor compared with clopidogrel. Corresponding relative risks were 0.92 (0.83 to 1.01) and 0.89 (0.79 to 1.00) among nonsmokers. Conclusions: In randomized clinical trials of antiplatelet drugs, the reported clinical benefit of clopidogrel in reducing cardiovascular death, myocardial infarction, and stroke was seen primarily in smokers, with little benefit in nonsmokers

Differential risk of death in older residents in nursing homes prescribed specific antipsychotic drugs: population based cohort study

Objective To assess risks of mortality associated with use of individual antipsychotic drugs in elderly residents in nursing homes

Treatment Effects in the Presence of Unmeasured Confounding: Dealing With Observations in the Tails of the Propensity Score Distribution--A Simulation Study

Frailty, a poorly measured confounder in older patients, can promote treatment in some situations and discourage it in others. This can create unmeasured confounding and lead to nonuniform treatment effects over the propensity score (PS). The authors compared bias and mean squared error for various PS implementations under PS trimming, thereby excluding persons treated contrary to prediction. Cohort studies were simulated with a binary treatment T as a function of 8 covariates X. Two of the covariates were assumed to be unmeasured strong risk factors for the outcome and present in persons treated contrary to prediction. The outcome Y was simulated as a Poisson function of T and all X’s. In analyses based on measured covariates only, the range of PS's was trimmed asymmetrically according to the percentile of PS in treated patients at the lower end and in untreated patients at the upper end. PS trimming reduced bias due to unmeasured confounders and mean squared error in most scenarios assessed. Treatment effect estimates based on PS range restrictions do not correspond to a causal parameter but may be less biased by such unmeasured confounding. Increasing validity based on PS trimming may be a unique advantage of PS's over conventional outcome models

Applying System Engineering to Pharmaceutical Safety

While engineering techniques are used in the development of medical devices and have been applied to individual healthcare processes, such as the use of checklists in surgery and ICUs, the application of system engineering techniques to larger healthcare systems is less common. System safety is the part of system engineering that uses modeling and analysis to identify hazards and to design the system to eliminate or control them. In this paper, we demonstrate how to apply a new, safety engineering static and dynamic modeling and analysis approach to healthcare systems. Pharmaceutical safety is used as the example in the paper, but the same approach is potentially applicable to other complex healthcare systems. System engineering techniques can be used in re-engineering the system as a whole to achieve the system goals, including both enhancing the safety of current drugs while, at the same time, encouraging the development of new drugs

Performance of propensity score calibration - A simulation study

Confounding can be a major source of bias in nonexperimental research. The authors recently introduced propensity score calibration (PSC), which combines propensity scores and regression calibration to address confounding by variables unobserved in the main study by using variables observed in a validation study. Here, the authors assess the performance of PSC using simulations in settings with and without violation of the key assumption of PSC: that the error-prone propensity score estimated in the main study is a surrogate for the gold-standard propensity score (i.e., it contains no additional information on the outcome). The assumption can be assessed if data on the outcome are available in the validation study. If data are simulated allowing for surrogacy to be violated, results depend largely on the extent of violation. If surrogacy holds, PSC leads to bias reduction between 32% and 106% (>100% representing overcorrection). If surrogacy is violated, PSC can lead to an increase in bias. Surrogacy is violated when the direction of confounding of the exposure-disease association caused by the unobserved variable(s) differs from that of the confounding due to observed variables. When surrogacy holds, PSC is a useful approach to adjust for unmeasured confounding using validation data

Risk of Ischemic Cerebrovascular and Coronary Events in Adult Users of Anticonvulsant Medications in Routine Care Settings

Background: Older‐generation anticonvulsants that highly induce cytochrome P450 enzyme system activity produce metabolic abnormalities that may increase cardiovascular risk. The objective of this study was to evaluate the risk of ischemic cerebrovascular and coronary events in adult new users of anticonvulsants that highly induce cytochrome P450 activity compared with other anticonvulsant agents, as observed in a routine care setting. Methods and Results: This was a cohort study of patients 40 to 64 years old from the HealthCore Integrated Research Database who had initiated an anticonvulsant medication between 2001 and 2006 and had no recorded major coronary or cerebrovascular condition in the 6 months before treatment initiation. Propensity score (PS) matching was used to evaluate ischemic cerebrovascular and coronary risk among anticonvulsant new users. High‐dimensional propensity score (hdPS)–matched analyses were used to confirm adjusted findings. The study identified 913 events in 166 031 unmatched new treatment episodes with anticonvulsant drugs. In a PS‐matched population of 22 864 treatment episodes, the rate ratio (RR) for ischemic coronary or cerebrovascular events associated with highly inducing agents versus other agents was 1.22 (95% CI, 0.90‐1.65). The RR moved to 0.99 (95% CI, 0.73‐1.33) with adjustment for hdPS matching (RR, 1.47; 95% CI, 0.95‐2.28 for cerebrovascular events; RR, 0.70; 95% CI, 0.47‐1.05 for coronary events). Conclusions: In this exploratory analysis, there was no evidence of a consistent and statistically significant effect of initiating anticonvulsants that highly induce cytochrome P450 activity on ischemic coronary or cerebrovascular outcomes compared with other agents, given routine care utilization patterns

Propensity Score Calibration in the Absence of Surrogacy

Propensity score calibration (PSC) can be used to adjust for unmeasured confounders using a cross-sectional validation study that lacks information on the disease outcome (Y), under a strong surrogacy assumption. Using directed acyclic graphs and path analysis, the authors developed a formula to predict the presence and magnitude of the bias of PSC in the simplest setting of a binary exposure (T) and 1 confounder (X) that are observed in the main study and 1 confounder (C) that is observed in the validation study only. PSC bias is predicted on the basis of parameters that can be estimated from the data and a single unidentifiable parameter, the relative risk (RR) associated with C (RRCY). The authors simulated 1,000 cohort studies each with a Poisson-distributed outcome Y, varying parameter values over a wide range. When using the true parameter for RRCY, the formula predicts PSC bias almost perfectly in this simple setting (correlation with observed bias over 24 scenarios assessed: r = 0.998). The authors conclude that the bias from PSC observed in certain scenarios can be estimated from the imbalance in C between treated and untreated persons, after adjustment for X, in the validation study and assuming a range of plausible values for the unidentifiable RRCY

A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods

Objective: Propensity score (PS) analyses attempt to control for confounding in nonexperimental studies by adjusting for the likelihood that a given patient is exposed. Such analyses have been proposed to address confounding by indication, but there is little empirical evidence that they achieve better control than conventional multivariate outcome modeling. Study Design and Methods: Using PubMed and Science Citation Index, we assessed the use of propensity scores over time and critically evaluated studies published through 2003. Results: Use of propensity scores increased from a total of 8 reports before 1998 to 71 in 2003. Most of the 177 published studies abstracted assessed medications (N = 60) or surgical interventions (N = 51), mainly in cardiology and cardiac surgery (N = 90). Whether PS methods or conventional outcome models were used to control for confounding had little effect on results in those studies in which such comparison was possible. Only 9 of 69 studies (13%) had an effect estimate that differed by more than 20% from that obtained with a conventional outcome model in all PS analyses presented. Conclusions: Publication of results based on propensity score methods has increased dramatically, but there is little evidence that these methods yield substantially different estimates compared with conventional multivariable methods

Analytic strategies to adjust confounding using exposure propensity scores and disease risk scores: Nonsteroidal antiinflammatory drugs and short-term mortality in the elderly

Little is known about optimal application and behavior of exposure propensity scores (EPS) in small studies. In a cohort of 103,133 elderly Medicaid beneficiaries in New Jersey, the effect of nonsteroidal antiinflammatory drug use on 1-year all-cause mortality was assessed (1995-1997) based on the assumption that there is no protective effect and that the preponderance of any observed effect would be confounded. To study the comparative behavior of EPS, disease risk scores, and "conventional" disease models, the authors randomly resampled 1,000 subcohorts of 10,000, 1,000, and 500 persons. The number of variables was limited in disease models, but not EPS and disease risk scores. Estimated EPS were used to adjust for confounding by matching, inverse probability of treatment weighting, stratification, and modeling. The crude rate ratio of death was 0.68 for users of nonsteroidal antiinflammatory drugs. "Conventional" adjustment resulted in a rate ratio of 0.80 (95% confidence interval: 0.77, 0.84). The rate ratio closest to 1 (0.85) was achieved by inverse probability of treatment weighting (95% confidence interval: 0.82, 0.88). With decreasing study size, estimates remained further from the null value, which was most pronounced for inverse probability of treatment weighting (n = 500: rate ratio = 0.72, 95% confidence interval: 0.26, 1.68). In this setting, analytic strategies using EPS or disease risk scores were not generally superior to "conventional" models. Various ways to use EPS and disease risk scores behaved differently with smaller study size

Systematic review of economic evaluations and cost analyses of guideline implementation strategies

Objectives To appraise the quality of economic studies undertaken as part of evaluations of guideline implementation strategies; determine their resources use; and recommend methods to improve future studies. Methods Systematic review of economic studies undertaken alongside robust study designs of clinical guideline implementation strategies published (1966-1998). Studies assessed against the BMJ economic evaluations guidelines for each stage of the guideline process (guideline development, implementation and treatment). Results 235 studies were identified, 63 reported some information on cost. Only 3 studies provided evidence that their guideline was effective and efficient. 38 reported the treatment costs only, 12 implementation and treatment costs, 11 implementation costs alone, and two guideline development, implementation and treatment costs. No study gave reasonably complete information on costs. Conclusions Very few satisfactory economic evaluations of guideline implementation strategies have been performed. Current evaluations have numerous methodological defects and rarely consider all relevant costs and benefits. Future evaluations should focus on evaluating the implementation of evidence based guidelines. Keywords: Cost-effectiveness analysis, physician (or health care professional) behaviour, practice guidelines, quality improvement, systematic review.Peer reviewedAuthor versio