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We do not believe that the results of the FDA study should cause concern regarding the overall reliability of the agency's approval process for generic drugs, including the use of extrapolation, when scientifically appropriate. Technical aspects of the Budeprion formulation may have led to the failure of extrapolation in this case. More information on this issue will be generated by the other sponsors' bioequivalence studies. The other 300-mg generic bupropion products do not use the same technology as Budeprion. The use of extrapolation for the approval of multiple strengths of generic drugs, which incorporates science-based reasoning, has been generally successful, and the FDA will continue to refine its approach to this method. The agency will also move more aggressively to perform its own studies when data are urgently needed. We wish to assure the public that drug products that are approved for generic use will continue to be held to high standards of quality, safety, and efficacy.
The other major difference observed between Budeprion XL 300 mg and Wellbutrin XL 300 mg was in the time to peak drug concentration in the blood (Tmax) (see graph). Although FDA guidance does not include Tmax as a criterion for bioequivalence of bupropion hydrochloride products, the Tmax for Budeprion XL (4 hours) is shorter than that for Wellbutrin XL (5 hours). A similar difference in Tmax values was also observed in the bioequivalence study of the 150-mg products that was originally used for extrapolation of data for Budeprion XL 300 mg. But because the comparative area-under-the-curve and Cmax values for the 150-mg products fell within FDA parameters and were supported by data on the performance of the product in vitro, Budeprion XL 300 mg was approved.
The study by Ray et al. has limitations that are intrinsic to observational, nonrandomized clinical studies. In particular, nonrandomized studies cannot exclude the possibility that patients receiving a drug under evaluation differ from control patients in some important but undetected way, causing bias in the results. Such confounding may bias comparisons not only between patients receiving antibacterial drugs and those receiving no antibacterials but also between patients receiving different antibacterials. Although Ray et al. used appropriate analytic methods to address potential confounding, we cannot know for certain whether these methods were fully successful. Replication of the authors' results, through analysis of a distinct data set, would provide more confidence in the finding of increased cardiovascular mortality among patients receiving azithromycin.
In 2011, approximately 40.3 million people in the United States (roughly one eighth of the population) received an outpatient prescription for the macrolide azithromycin, according to IMS Health. During that year, we at the Food and Drug Administration (FDA) reviewed the labels of azithromycin and other approved macrolide antibacterials in view of cardiovascular risks that had become evident from published studies and reports emerging through postmarketing surveillance. On the basis of its review, the FDA approved revisions to azithromycin product labels regarding risks of QT-interval prolongation and the associated ventricular arrhythmia torsades de pointes. The revised labels advise against using azithromycin in patients with known risk factors such as QT-interval prolongation, hypokalemia, hypomagnesemia, bradycardia, or use of certain antiarrhythmic agents, including class IA (e.g., quinidine and procainamide) and class III (e.g., dofetilide, amiodarone, and sotalol) — drugs that can prolong the QT interval. In March 2013, the FDA announced that azithromycin labels had been further revised to reflect the results of a clinical study showing that azithromycin can prolong the corrected QT interval.
Second, an accurate comparison of time to market access requires measurement of the total time that elapses between application submission and market access. Previous studies have compared the chronologic dates of application submission and market access, but the date an application is submitted varies from country to country.
A new study by Svanström and colleagues (pages 1704–1712), using Danish national health care data, found no difference between azithromycin and penicillin V in the 5-day risk of cardiovascular death (relative risk, 0.93; 95% confidence interval <CI>- , 0.56 to 1.55). However, the upper bound of the 95% confidence interval does not exclude an increased risk of as much as 55%. As Svanström et al. point out, the population they studied differed from that studied by Ray et al. with respect to the baseline risk of death and cardiovascular risk factors. Overall, the Danish patients had better cardiovascular health than the Tennessee Medicaid patients. In a subgroup analysis of patients with a history of cardiovascular disease, the risk ratio for azithromycin versus penicillin V was greater than 1, though the difference was not statistically significant (relative risk, 1.35; 95% CI, 0.69 to 2.64). Svanström et al. conclude that their results do not conflict with those of Ray et al. Rather, the effect on cardiovascular mortality may be limited to patients with cardiovascular disease.
On July 2, 2012, the Department of Justice announced the largest settlement ever in a case of health care fraud in the United States. GlaxoSmithKline (GSK) agreed to plead guilty to three criminal counts and settle civil charges brought under various federal statutes; the company will pay a total of $3 billion to the federal government and participating states. Since 2009, the federal government has collected more than $11 billion in such settlements under the False Claims Act.
Medications commonly prescribed to treat other conditions that occur frequently in patients with the condition under study should be allowed to be used during clinical trials,5 either in the pivotal phase 3 trials or — if better recruitment results would be expected — in a separate trial. Excessive “confounder cleansing” may result in the study of nonrepresentative populations.
Analysis of the data submitted in support of recent applications for marketing authorization shows that the current regulatory environment has ensured reasonable representation of “younger old” patients, but drug-usage patterns reveal a high prevalence of use in “older old” patients (see graphThe Example of Cardiovascular Drugs: Percentages of All Patients in a Given Age Group Treated with Cardiovascular Drugs (Italy) versus Percentages in Each Age Group Included in Cardiovascular Drug Trials (Globally).). Patients who are 75 years old or older often present a complex picture involving coexisting conditions and frailty: they are the fastest-growing demographic group but are largely underrepresented in clinical trials given their disproportionately high actual use of drugs. This imbalance will make it increasingly difficult and potentially inappropriate to extrapolate data to these patients.2 Though trials are less likely to set unjustified age limits than they were a few decades ago, this improvement must be considered in the context of a rapidly aging population and the continued widespread use of exclusion criteria based on coexisting conditions. Corrective efforts must be maintained to ensure that a representative population of patients covering the entire age range is studied in the preauthorization phase, in accordance with international guidelines.3
For both private and public systems in the United States, the pathway to patient access to a device starts with the submission of an application to the FDA. The FDA reviews innovative, high-risk devices for safety and effectiveness (clinical benefit) under the premarket approval (PMA) process, and information on the duration of reviews is publicly available. In fiscal year 2011, the FDA approved 40 applications for PMA. The average review time was 13.1 months, with 8.4 months attributed to FDA review time, and 4.7 months to the time the agency waits for the sponsor to address deficiencies in the application (“sponsor time”).3 CMS provides reimbursement for the majority of devices when they earn FDA approval. For a limited number of devices each year, however, CMS conducts a national coverage determination in response to external requests for validation or for devices that have limited or conflicting evidence of clinical benefit. This process averaged 8.6 months over the past 5 fiscal years.4 Although it is difficult to obtain data on how long private insurers take to make coverage decisions, anecdotal information from private insurers suggests that decisions are made within a few weeks to a few months after FDA approval, depending on the amount and quality of evidence of clinical benefit.
To further illustrate this point, we compared the time to approval for five innovative, high-risk medical devices available in France, Italy, and the United States (see tableComparison of Time to Market Access for Five Innovative Devices in France, Italy, and the United States.). These case studies indicate that the average time to market access for these devices was 26.3 months in France, 30.8 months in Italy, and 15.3 months in the United States.
Renewed attention to comparative effectiveness research in the 21st century illustrates the consequences of sidelining Kefauver's initial demand for comparative data for evaluating the promotion of novel therapeutics. By 2000, pharmaceutical expenditures had become one of the fastest-growing parts of the budget of many U.S. states and third-party insurers. But the kind of knowledge required for entry into the U.S. drug market offers consumers and payers little information relevant to choosing between subtly different “me-too” drugs within the same therapeutic class — whose therapeutic effect may or may not be the same. Only in the past decade, through the action of the Reforming States Group, the Drug Effectiveness Review Project, and most recently funding of comparative effectiveness research through the American Recovery and Reinvestment Act, the Affordable Care Act, and now the Patient-Centered Outcomes Research Institute, have we begun to catch up on the vital project of comparing therapeutics so that American consumers and their physicians can make meaningful treatment decisions — the project that motivated Kefauver's original investigations a half century ago.
But questions remain about the efficacy of fines and corporate integrity agreements in deterring corporate misbehavior. The 2012 fines against Abbott Laboratories and GSK represent a modest percentage of those companies' revenue.1 Companies might well view such fines as merely a cost of doing business — a quite small percentage of their global revenue and often a manageable percentage of the revenue received from the particular product under scrutiny. If so, little has been done to change the system; the government merely recoups a portion of the financial fruit of firms' past misdeeds.
Going forward, the NIH strongly and unequivocally supports the importance of the role of the OHRP in the oversight of human subjects research. But the community will benefit from an explicit description of the process the OHRP follows for investigating complaints. For example, when questions are raised about reasonably foreseeable risks and the state of the science relevant to a particular clinical trial, appropriate independent experts might need to be consulted. Finally, we are pleased to see the DHHS plans to ensure that investigators and IRBs will have a fair and transparent process for appealing OHRP findings and compliance actions, in those situations in which reasonable people disagree about the actions taken.
Depending on patients' frailty and disability status, the desirable outcome and treatment choices might vary: different patients place different values on benefits and risks. Certain adverse events, such as dizziness leading to falls, may be of greater importance in the geriatric population. The design of a clinical trial should consider age-appropriate end points; for older people, functional outcomes may be most important, and an emphasis on such outcomes could lead to reduced costs for health care systems.
Inappropriate formulations and packaging may contribute to low adherence, medication errors, and safety and efficacy problems. Additional considerations for a largely elderly population will include the need for easy administration, possible dose reduction, the effects of visual and motor impairment, and the likelihood of polypharmacy. If appropriate, protocols should be designed for evaluating patients' ability to manage their own medications. Regulators should also look favorably on nondrug technologies such as information and communication technology systems for monitoring adherence or clinical signs.
The federal Office for Human Research Protections (OHRP), which is charged with providing leadership in the protection of the rights, welfare, and well-being of persons involved in research conducted or supported by the U.S. Department of Health and Human Services (DHHS), asserted in March 2013, on the basis of its own examination of the evidence, that the SUPPORT researchers failed to provide prospective parents sufficient information about the risks posed by the study. After a detailed review of the protocol, the relevant consent documents, and the research literature, we respectfully disagree with the conclusions of the OHRP, which we believe resulted from a fundamental difference in interpretations of how the regulations should apply to the state of scientific understanding when the SUPPORT study commenced. Moreover, there is a larger issue here: how risks should be conveyed in the informed-consent process when research is comparing interventions that are all considered to be the standard of care.
Although population aging is a mark of the success of public health policies, it also challenges the established way of implementing such policies. In the case of the European Medicines Agency (EMA), it has prompted an analysis of whether the regulatory system is adapted to taking the needs of older people into account in the development, approval, and use of medications.
The use of data extrapolation for the approval of Budeprion XL 300 mg should be considered in historical context. When applications for generic versions of Wellbutrin XL 300 mg began to come under FDA review in 2005, more than 11 million prescriptions for the brand-name product were being written each year. Programs to develop generic bupropion products, and the requisite bioequivalence studies, were important for addressing the widespread need for the treatment of major depressive disorder. At the same time, the FDA and sponsors recognized that bupropion conferred a dose-related risk of seizures, which the agency believed warranted a conservative approach to bioequivalence testing of bupropion in healthy volunteers. Bioequivalence studies that used only the lower strength (150 mg) reflected this conservative approach.
Kefauver's bill met strong resistance as it made its way through the Subcommittee on Antitrust and Monopoly.2 The American Medical Association firmly opposed the regulation of efficacy by a government agency, arguing that “the only possible final determination as to the efficacy and ultimate use of a drug is the extensive clinical use of that drug by large numbers of the medical profession over a long period of time.”3 The editors of the Journal, on the other hand, supported the efficacy provision and the expansion of generic drug names but opposed the patent provisions (considering them an “arbitrary discrimination” against the pharmaceutical industry) and the comparative effectiveness provisions (considering “proof of superiority” necessary only if superiority was actually being “claimed by the manufacturer”).4 The pharmaceutical industry amplified such concerns about comparative effectiveness, arguing that any a priori determination of which medicines were “me-too” and which were true innovations would be arbitrary. Efficacy was hard enough to prove, they suggested; proving comparative efficacy would be “completely impracticable.”3

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