Rosiglitazone and Myocardial Infarction in Patients Previously Prescribed Metformin

Objective: Rosiglitazone was found associated with approximately a 43% increase in risk of acute myocardial infarction (AMI) in a two meta-analyses of clinical trials. Our objective is to estimate the magnitude of the association in real-world patients previously treated with metformin. Research Design and Methods: We conducted a nested case control study in British Columbia using health care databases on 4.3 million people. Our cohort consisted of 158,578 patients with Type 2 diabetes who used metformin as first-line drug treatment. We matched 2,244 cases of myocardial infarction (AMI) with up to 4 controls. Conditional logistic regression models were used to estimate matched odds ratios for AMI associated with treatment with rosiglitazone, pioglitazone and sulfonylureas. Results: In our cohort of prior metformin users, adding rosiglitazone for up to 6 months was not associated with an increased risk of AMI compared to adding a sulfonylurea (odds ratio [OR] 1.38; 95% confidence interval [CI], 0.91–2.10), or compared to adding pioglitazone (OR for rosi versus pio 1.41; 95% CI, 0.74–2.66). There were also no significant differences between rosiglitazone, pioglitazone and sulfonylureas for longer durations of treatment. Though not significantly different from sulfonylureas, there was a transient increase in AMI risk associated with the first 6 months of treatment with a glitazone compared to not using the treatment (OR 1.53; 95% CI, 1.13–2.07) Conclusions: In our British Columbia cohort of patients who received metformin as first-line pharmacotherapy for Type 2 diabetes mellitus, further treatment with rosiglitazone did not increase the risk of AMI compared to patients who were treated with pioglitazone or a sulfonylurea. Though not statistically significantly different compared from each other, an increased risk of AMI observed after starting rosiglitazone or sulfonylureas is a matter of concern that requires more research

How the weather affects the pain of citizen scientists using a smartphone app.

Patients with chronic pain commonly believe their pain is related to the weather. Scientific evidence to support their beliefs is inconclusive, in part due to difficulties in getting a large dataset of patients frequently recording their pain symptoms during a variety of weather conditions. Smartphones allow the opportunity to collect data to overcome these difficulties. Our study Cloudy with a Chance of Pain analysed daily data from 2658 patients collected over a 15-month period. The analysis demonstrated significant yet modest relationships between pain and relative humidity, pressure and wind speed, with correlations remaining even when accounting for mood and physical activity. This research highlights how citizen-science experiments can collect large datasets on real-world populations to address long-standing health questions. These results will act as a starting point for a future system for patients to better manage their health through pain forecasts

To what extent do mass media health messages trigger patients' contacts with their GPs?

BACKGROUND: A recent Cochrane review concluded that mass media intervention may play an important role in influencing the use of health services, but little is known about the effects of unplanned untargeted information in the media. AIM: To investigate the influence of messages in mass media about health issues on patients' contacts with their GPs. DESIGN OF STUDY: A case crossover design study comparing the frequency of receiving mass media health messages in a period before contact with a GP versus the frequency in matching control time periods for the same individuals. The outcome measure was the odds of patients having received health messages in the period before they contacted their GP, compared to the odds in the control periods. SETTING: The practices of 21 single-handed Danish GPs. METHOD: Three hundred and twenty-two patients between 18 and 91 years of age were interviewed by telephone after an unscheduled contact with a GP, and 148 patients were interviewed again 3–6 months later. Health media messages were only recorded if patients could remember the topics. RESULT: More than a third (35%) of the patients remembered receiving health media messages in the week before contact. No significant relationship (odds ratio = 1.2, 95% confidence interval = 0.5 to 2.6) between health messages and contact with GPs could be observed. CONCLUSION: In the absence of health campaigns and drug advertisements, mass media health messages seldom directly trigger patients to consult their GPs

On the Evaluation of Drug Benefits Policy Changes with Longitudinal Claims Data: Concepts of Income-Based Deductibles and Issues Related to Causal Inference

Cost containment in pharmaceutical benefits plans is often controversial because of its potential for unintended effects on health and overall expenditures. Thorough evaluations are needed to support benefits plans in developing evidence-based policies. Evaluations of income-based deductibles for prescription drugs using non-experimental data are challenging because the time until patients' expenses exceed their annual deductible varies with the number of drugs used, which depends on their health status and income. We sought to clarify conceptual and methodological issues in longitudinal designs to evaluate income-based deductibles for prescription drugs, and provide a framework for the evaluation of such policies using longitudinal claims data. One of the main challenges is the violation of the Exclusion Restriction Assumption, which is a standard assumption when using instrumental variables such as the start date of a new policy. This assumption requires the instrumental variable to be independent of subject characteristics, such as income and health status. The validity of an evaluation therefore depends on the ability to measure and adjust for these characteristics. Given the lack of such data, randomization of the policy may be a more valid study design.Cost containment, Pharmacoeconomics, Reimbursement