Nissen and his colleagues perform a meta–analsysis on published clinical trial data on the diabetes drug Avandia and conclude that it may be associated with a 43% increase in heart attack risk for some patients.

We conducted searches of the published literature, the Web site of the Food and Drug Administration, and a clinical–trials registry maintained by the drug manufacturer (GlaxoSmithKline). Criteria for inclusion in our meta–analysis included a study duration of more than 24 weeks, the use of a randomized control group not receiving rosiglitazone, and the availability of outcome data for myocardial infarction and death from cardiovascular causes. Of 116 potentially relevant studies, 42 trials met the inclusion criteria. We tabulated all occurrences of myocardial infarction and death from cardiovascular causes.

Data were combined by means of a fixed–effects model. In the 42 trials, the mean age of the subjects was approximately 56 years, and the mean baseline glycated hemoglobin level was approximately 8.2%. In the rosiglitazone group, as compared with the control group, the odds ratio for myocardial infarction was 1.43 (95% confidence interval [CI], 1.03 to 1.98; P=0.03), and the odds ratio for death from cardiovascular causes was 1.64 (95% CI, 0.98 to 2.74; P=0.06).

[We conclude that] Rosiglitazone was associated with a significant increase in the risk of myocardial infarction and with an increase in the risk of death from cardiovascular causes that had borderline significance. Our study was limited by a lack of access to original source data, which would have enabled time–to–event analysis. Despite these limitations, patients and providers should consider the potential for serious adverse cardiovascular effects of treatment with rosiglitazone for type 2 diabetes.

As Congress debates the renewal of the State Children's Health Insurance Program (SCHIP) the Congressional Budget Office has released a paper summarizing the history and design of SCHIP, and discussing key issues that are likely to emerge as the debate moves forward. One problem that policymakers should pay careful attention to is how SCHIP has "crowded out" private insurance coverage for some parents and their children.

Although SCHIP has significantly reduced the number of uninsured children in low–income families, the net effect on the extent of coverage is smaller than the number of children who have been enrolled in public coverage as a result of SCHIP because the increase in public coverage has been partially offset by a reduction in private coverage.

SCHIP provides an alternative source of coverage that is less expensive and that often provides a broader range of benefits than private insurance. As a result, some parents who otherwise would have enrolled their children in private coverage may prefer instead to switch their coverage to SCHIP. In addition, to the extent that SCHIP makes private coverage less important for some low income families, parents might be more inclined to take jobs that offer higher cash wages rather than health insurance.

Moreover, if employers of low–wage workers believe that SCHIP reduces the value of private health insurance in attracting employees, some might reduce their contribution to the premiums for family coverage, reduce the benefits offered, stop offering family coverage, or stop offering insurance altogether. Considerable potential thus exists for increases in SCHIP coverage to be partially offset by a reduction in private coverage.

For example, about 60 percent of the children who were eligible for the program were covered by private insurance in the year before the program was enacted. But measuring the extent to which enrollment in SCHIP has actually been offset by a reduction in private coverage is difficult. Estimates vary depending on the measure that is used. Moreover, studies have obtained widely varying estimates depending on the data sources and methods

On the basis of a review of the research literature, CBO concludes that the most reliable estimates currently available suggest that the reduction in private coverage among children is between a quarter and a half of the increase in public coverage resulting from SCHIP. In other words, for every 100 children who enroll as a result of SCHIP, there is a corresponding reduction in private coverage of between 25 and 50 children.

The available evidence, which is quite limited, suggests that the bulk of the reduction in private coverage occurs because parents choose to forgo private coverage and enroll their children in SCHIP (because of better benefits, lower costs, or some combination thereof), rather than employers deciding to drop coverage for such children. No studies have estimated the extent to which SCHIP reduces private coverage among parents, so the available estimates probably understate the total reduction in private coverage associated with the introduction of SCHIP.

Cutler and his colleagues consider how past trends in health behaviors (like the long term decline in U.S. smoking rates) have affected longevity, and what current trends (like rising obesity rates) portend for future health.

In this paper, we consider what has happened to the population's health behaviors over time, and consider various scenarios for trends in the future.

Past trends in behavioral risk factors have not been in a common direction. Some measures of population risk have improved markedly, while others have deteriorated. Smoking rates have fallen by more than a third since 1960 (Anonymous, 1999) and alcohol consumption has declined by 20 percent since 1980 (Lakins, Williams, and Yi, 2006), both leading to better health.

Demographically, the population is better educated, and better educated people live longer than less educated people (Elo and Preston, 1996). On the other hand, obesity rates have doubled in the past two decades (Flegal et al., 2002) and diabetes has increased as a result (Gregg et al., 2005). Further, the population has a higher share of minority groups, for whom life expectancy is lower. The net impact of these risk factor trends on population health expectations is uncertain (Preston, 2005).

Our analysis has two parts. We start by aggregating these different health trends into a single measure of population risk. We focus on the most common risk factors: smoking, drinking, obesity, hypertension, high cholesterol, and diabetes. We weight the different risk factors by their impact on predicted 10 year mortality, as determined through multiple regression analysis. We show that overall health trends in the past three decades have improved markedly. For the entire population aged 25 and older, the age adjusted probability of dying in 10 years, conditional on the same level of medical care, fell from 9.8 percent in the early 1970s to 8.4 percent around 2000, a 14 percent reduction. The largest contributors to this trend were reductions in smoking and improved blood pressure control.

The second part of our analysis considers the impact of a continuation of future trends. Our conclusions here are not as rosy. We show that if current obesity trends continue, the population mortality risk could increase, even with continued reductions in smoking. We estimate that about a third of the past gains would be reversed within 20 years. The increase in obesity is the proximate cause of this. But even given the increase in obesity, the health impact would be substantially blunted if more people took medication to control blood pressure, cholesterol, and diabetes.

Researchers in the New England Journal of Medicine warn that health gains from pay–for–performance incentives will be limited because our fragmented health care system makes it difficult to measure the respective contributions of the several different physicians who may find themselves caring for a single patient.

We analyzed Medicare claims from 2000 through 2002 for 1.79 million fee–for–service beneficiaries treated by 8604 respondents to the Community Tracking Study Physician Survey in 2000 and 2001. In separate analyses, we assigned each patient to the physician or primary care physician with whom the patient had had the most visits. We determined the number of physicians and practices seen annually, the percentage of care received from the assigned physician or practice, the stability of assignments over time, and the percentage of physicians' Medicare patients who were their assigned patients.

...Beneficiaries saw a median of two primary care physicians and five specialists working in four different practices. A median of 35% of beneficiaries' visits each year were with their assigned physicians; for 33% of beneficiaries, the assigned physician changed from one year to another. On the basis of all visits to any physician, a primary care physician's assigned patients accounted for a median of 39% of the physician's Medicare patients and 62% of Medicare visits. For medical specialists, the respective percentages were 6% and 10%. On the basis of visits to primary care physicians only, 79% of beneficiaries could be assigned to a physician, and a median of 31% of beneficiaries' visits were with that assigned primary care physician.

The researchers concluded that

In fee–for–service Medicare, the dispersion of patients' care among multiple physicians will limit the effectiveness of pay–for–performance initiatives that rely on a single retrospective method of assigning responsibility for patient care.

Academy Health finds that the nascent science of pharmacogenomics (PGx), i.e. how drugs interact with genetics, faces several formidable challenges before it can become widespread in the marketplace—particularly because our reimbursement system is badly aligned with the concept of personalized medicine.

Not only do PGx products and services stand to reduce adverse drug reactions, they have the potential to: 1) speed the approval process for drugs, reducing the cost of clinical trials (by using genetic tests to target a defined patient population); 2) reduce the length of time patients are on medication; 3) reduce the number of medications patients must take in order to find an effective therapy; and 4) reduce of the effects of disease in the body through early detection...

This study finds that the existing U.S. payment system is not designed for, and is therefore inadequate for, PGx products and services to reach their maximum treatment potential. The researchers encourage policymakers to discuss and consider reforms to the current financing and payment systems in light of the potential for positive health outcomes. "With the widespread adoption of PGx, a simple genetic test may prevent countless adverse drug events, hospitalizations, disability, and death," says Rossiter. The results of this study indicate that more funding should be directed toward PGx cost–effectiveness research. Only with additional funding directed toward health services research, can society truly experience the greatest value offered by PGx.

Cutler and his colleagues estimate the economic and health impacts of antihypertensive therapy in the U.S. over the past 40 years.

Using national survey data and risk equations from the Framingham Heart Study, we quantify the impact of antihypertensive therapy changes on blood pressures and the number and cost of heart attacks, strokes, and deaths. Antihypertensive therapy has had a major impact on health. Without it, 1999–2000 average blood pressures (at age 40+) would have been 10–13 percent higher, and 86,000 excess premature deaths from cardiovascular disease would have occurred in 2001. Treatment has generated a benefit–to–cost ratio of at least 6:1, but much more can be achieved. More effective use of antihypertensive medication would have an impact on mortality akin to eliminating all deaths from medical errors or accidents.

They also speculate that "life expectancy would increase an additional 0.3 years (men) and 0.1 years (women) if therapy were extended to all with State I or Stage II hypertension not currently treated with medication."

Goldman and Philipson argue that insofar as prescription drugs are substitutes for other forms of health care, like doctor's offices and emergency room visits, optimal insurance benefit design (at least for certain chronic disease categories) should have very low or even negative co–pays for prescription drugs.

The classic theory of moral hazard concerns the insurance of a single good and predicts that co–insurance is larger when the elasticity of demand is higher and when small risks are insured. We extend this analysis to the insurance of multiple goods; for example, the simultaneous insurance of medical services and prescription drugs. We show that when multiple goods are either complements or substitutes—so that a change in co–insurance for one service affects the demand of others—the classic moral hazard results do not hold.

For example, the single good model would predict high co–payments for prescription drugs since drug demand is elastic and of modest financial risk. However, a model of multi–good insurance suggests such drug coverage may optimally involve zero or even negative co–insurance when it is a substitute to other services insured such as hospital care or physician services. We summarize some of the empirical evidence in support of markets adopting optimal integrated pricing structures rather than individually optimal pricing structures.

The authors note that:

In sum, the preponderance of evidence suggests strong negative cross–price elasticities between drugs and other medical spending, at least for patients with chronic disease. The behavioral mechanism is almost surely compliance (John A.Rizzo and W. Robert Simons, 1997; L. Wei et al, 2002). For example, Dana P. Goldman et al (2006) investigated the relationship between compliance and subsequent outcomes for patients who had initiated statin therapy in the previous two to five years. They found that full compliance with cholesterol–lowering therapy reduces use of hospital services by 25% among high risk patients, demonstrating a substantial cross–price elasticity between drugs and hospital services among certain chronically–ill populations and for certain drugs. Other studies find similar effects for asthma and diabetes.

This article finds that using biomarkers (like C-reactive protein and homosyteine) to help predict the risks of patients developing life-threatening cardiovascular disease have only marginal advantages over traditional risk factor analysis.

Few investigations have evaluated the incremental usefulness of multiple biomarkers from distinct biologic pathways for predicting the risk of cardiovascular events.

We measured 10 biomarkers in 3209 participants attending a routine examination cycle of the Framingham Heart Study: the levels of C-reactive protein, B-type natriuretic peptide, N-terminal pro–atrial natriuretic peptide, aldosterone, renin, fibrinogen, D-dimer, plasminogen-activator inhibitor type 1, and homocysteine; and the urinary albumin-to-creatinine ratio.

During follow-up (median, 7.4 years), 207 participants died and 169 had a first major cardiovascular event. In Cox proportional-hazards models adjusting for conventional risk factors, the following biomarkers most strongly predicted the risk of death (each biomarker is followed by the adjusted hazard ratio per 1 SD increment in the log values): B-type natriuretic peptide level (1.40), C-reactive protein level (1.39), the urinary albumin-to-creatinine ratio (1.22), homocysteine level (1.20), and renin level (1.17). The biomarkers that most strongly predicted major cardiovascular events were B-type natriuretic peptide level (adjusted hazard ratio, 1.25 per 1 SD increment in the log values) and the urinary albumin-to-creatinine ratio (1.20). Persons with "multimarker" scores (based on regression coefficients of significant biomarkers) in the highest quintile as compared with those with scores in the lowest two quintiles had elevated risks of death (adjusted hazard ratio, 4.08; P<0.001) and major cardiovascular events (adjusted hazard ratio, 1.84; P = 0.02). However, the addition of multimarker scores to conventional risk factors resulted in only small increases in the ability to classify risk, as measured by the C statistic.

The authors conclude that "for assessing risk in individual persons, the use of the 10 contemporary biomarkers that we studied adds only moderately to standard risk factors."

These authors explore the likely consequences of allowing individuals to deduct health expenses from their federal income tax. Although they admit that this is a "second best policy" they argue that it is a definite improvement on the status quo.

As Mark Pauly's (1986) classic review shows, virtually all observers of health policy since Martin Feldstein's (1973) seminal article have agreed that the tax preference for employer-provided health insurance—under which employer contributions to employee health insurance are deductible to the employer and non–taxable to the employee—encourages overconsumption of health services in the United States. By making health spending in general, and insured health spending in particular, appear less costly than they are, the tax preference gives employees the incentive to take compensation as health insurance rather than cash, even if they would otherwise prefer not to...

In this paper, we show that extending deductibility to out–of–pocket spending, while a second–best policy change, is nonetheless likely to lead to significant improvements in efficiency under a range of assumptions about demand for health care and health insurance.

...Also, while not emphasized here, expanding deductibility may also significantly reduce rates of uninsurance by lowering the cost of health insurance. Finally, we view as an important topic for future work more analysis of the relationship between tax deductibility and Health Savings Accounts.

This article, reporting findings from this week's issue of the New England Journal of Medicine, shows that survival rates for patients with Chronic Myeloid Leukemia, or CML, have reached an all time high thanks to the use if the targeted cancer drug, Gleevec.

Data from the 5-year follow-up of patients taking imatinib (Gleevec, Novartis) for chronic myeloid leukemia (CML), published in the December 7 issue of the New England Journalof Medicine, show the best–ever survival with this disease.

"The 5–year estimated overall survival rate for patients who received imatinib as initial therapy (89%) is higher than that reported in any previously published prospective study of the treatment of CML," the authors write. Lead author Brian Drucker, MD, from the Oregon Health & Science University Cancer Institute, in Portland, had previously commented to Medscape that "imatinib has revolutionized the treatment of CML," pointing out that in the past 5-year survival rates were around 50%.

Previously, the most successful therapy was the combination of interferon–alpha and cytarabine, and 2 trials conducted before imatinib was available showed 5–year survival rates of 68% and 70%. Use of these historical comparisons shows a survival advantage for imatinib, the authors comment.

The 5–year data come from a study that evolved into a long–term follow–up, the team explains. Originally, the study had compared imatinib with interferon-alfa plus cytarabine (with 553 patients in each group). However, when the superiority of imatinib was demonstrated at a median 19 months of follow–up, a large proportion of patients on in the other group switched over, while others left the study after imatinib was approved by the FDA

…

"These results are very reassuring in that 72% of the original patients randomized to imatinib remain on therapy, " Dr. Stone commented. "Second, 82% of patients achieved a complete cryogenic response, and virtually all achieved a complete hematological response. Progression to accelerated and blast phase occurred in only 7% of the patients, with the progression rate actually decreasing over time."

"Front–line therapy with imatinib 400 mg orally daily is now the standard of care for newly diagnosed patients with CML," Dr. Stone concluded. "Long–term tolerance is good, and allogenic stem-–ell transplantation should be reserved for extremely young patients and/or those who fail to respond well to imatinib."