The Regulatory Repercussions of Approving Muscular Dystrophy Medications on the Basis of Limited Evidence.

The U.S. Food and Drug Administration (FDA) approved eteplirsen (Exondys 51) for Duchenne muscular dystrophy in 2016 via its accelerated approval program on the basis of a study of 12 boys. After a contentious review process and a high-profile meeting of an external advisory committee, FDA leaders concluded that very small increases in treated patients' levels of dystrophin, a muscle protein, were reasonably likely to predict clinical benefit. The eteplirsen approval, which was followed by approvals of other drugs in the same class via the same pathway, has been controversial because of the questionable evidence underlying these decisions, delays in mandated postapproval testing, and high U.S. prices. Questions remain about the effectiveness and long-term safety of these products. Although the FDA initially set a November 2020 deadline for eteplirsen's manufacturer to complete a clinical trial determining whether the drug has clinical benefit, the company will not complete the trial until 2024 or later. The relationship between levels of truncated dystrophin, the muscle protein studied in eteplirsen's pivotal trial, and clinical outcomes remains uncertain. Despite recent legislative and regulatory changes to the FDA's accelerated approval pathway, the history of eteplirsen and similar drugs points to the need for additional reforms to better balance evidence generation with patient safety and access to promising medications. Lawmakers and regulators should take further action to limit excessive spending on unproven therapies and ensure that drug sponsors conduct robust and timely confirmatory trials after receiving accelerated approval.

Using informatics to guide public health policy during the COVID-19 pandemic in the USA.

BACKGROUND: Current and future pandemics will require informatics solutions to assess the risks, resources and policies to guide better public health decision-making. METHODS: Cross-sectional study of all COVID-19 cases and deaths in the USA on a population- and resource-adjusted basis (as of 24 April 2020) by applying biomedical informatics and data visualization tools to several public and federal government datasets, including analysis of the impact of statewide stay-at-home orders. RESULTS: There were 2753.2 cases and 158.0 deaths per million residents, respectively, in the USA with variable distributions throughout divisions, regions and states. Forty-two states and Washington, DC, (84.3%) had statewide stay-at-home orders, with the remaining states having population-adjusted characteristics in the highest risk quartile. CONCLUSIONS: Effective national preparedness requires clearly understanding states' ability to predict, manage and balance public health needs through all stages of a pandemic. This will require leveraging data quickly, correctly and responsibly into sound public health policies.

Diversity in Medical Device Clinical Trials: Do We Know What Works for Which Patients?

Policy Points: A 1993 law required the National Institutes of Health to include women and racial and ethnic minorities in relevant research studies. Most federal health agencies adopted the same policy, but the US Food and Drug Administration (FDA) did not. A 2012 law encouraged the FDA to ensure that new medical products be analyzed for safety and effectiveness for key demographic patient groups. Our study of high-risk medical devices reviewed by the FDA in 2014-2017 found that due to lack of patient diversity and publicly available data, clinicians and patients often cannot determine which devices are safe and effective for specific demographic groups. CONTEXT: Demographic differences can influence the safety and effectiveness of medical devices; however, clinical trials of devices for adults have historically underrepresented women, people of color, and patients over age 65. The US Food and Drug Administration (FDA) Safety and Innovation Act became law in 2012, encouraging greater diversity and subgroup analyses. In 2013, the FDA reported that there was diversity in clinical trials considered "pivotal" for approval decisions and that subgroup analyses were conducted for most applications for the highest-risk medical devices. However, the FDA's report did not specify whether analyses included sufficient numbers to be meaningful, whether analyses were conducted for most major subgroups, or whether analyses included safety, effectiveness, or accuracy. METHODS: We examined publicly available documents for all 22 medical devices that the FDA designated "highest risk" or "novel," were reviewed through the premarket approval pathway, and were scrutinized at FDA public meetings from 2014 to 2017. We evaluated patient demographics and subgroup analyses for all pivotal trials. FINDINGS: Only 3 (14%) of the devices provided subgroup analyses for both effectiveness and safety or both sensitivity and selectivity for gender, race, and age. However, 55% of the devices reported both of those subgroup analyses for at least 1 of the 3 subgroups. Whether analyses were reported or not, the number of patients in most subgroups was too small to draw meaningful conclusions. Subgroup analyses were more likely to be reported to the FDA's Advisory Committees than in the FDA's public reviews or labeling. CONCLUSIONS: Despite a law encouraging more diversity and subgroup analyses in pivotal trials used as the basis for FDA approval, the results of our study indicate relatively few subgroup analyses are publicly available for the highest-risk and novel medical devices. The lack of subgroup analyses makes it impossible to inform patients or physicians as to whether many newly approved medical devices are safe and effective for specific demographic subgroups defined by gender, race, and age.

Software-Related Recalls of Health Information Technology and Other Medical Devices: Implications for FDA Regulation of Digital Health.

Policy Points: Medical software has become an increasingly critical component of health care, yet the regulation of these devices is inconsistent and controversial. No studies of medical devices and software assess the impact on patient safety of the FDA's current regulatory safeguards and new legislative changes to those standards. Our analysis quantifies the impact of software problems in regulated medical devices and indicates that current regulations are necessary but not sufficient for ensuring patient safety by identifying and eliminating dangerous defects in software currently on the market. New legislative changes will further deregulate health IT, reducing safeguards that facilitate the reporting and timely recall of flawed medical software that could harm patients. CONTEXT: Medical software has become an increasingly critical component of health care, yet the regulatory landscape for digital health is inconsistent and controversial. To understand which policies might best protect patients, we examined the impact of the US Food and Drug Administration's (FDA's) regulatory safeguards on software-related technologies in recent years and the implications for newly passed legislative changes in regulatory policy. METHODS: Using FDA databases, we identified all medical devices that were recalled from 2011 through 2015 primarily because of software defects. We counted all software-related recalls for each FDA risk category and evaluated each high-risk and moderate-risk recall of electronic medical records to determine the manufacturer, device classification, submission type, number of units, and product details. FINDINGS: A total of 627 software devices (1.4 million units) were subject to recalls, with 12 of these devices (190,596 units) subject to the highest-risk recalls. Eleven of the devices recalled as high risk had entered the market through the FDA review process that does not require evidence of safety or effectiveness, and one device was completely exempt from regulatory review. The largest high-risk recall categories were anesthesiology and general hospital, with one each in cardiovascular and neurology. Five electronic medical record systems (9,347 units) were recalled for software defects classified as posing a moderate risk to patient safety. CONCLUSIONS: Software problems in medical devices are not rare and have the potential to negatively influence medical care. Premarket regulation has not captured all the software issues that could harm patients, evidenced by the potentially large number of patients exposed to software products later subject to high-risk and moderate-risk recalls. Provisions of the 21st Century Cures Act that became law in late 2016 will reduce safeguards further. Absent stronger regulations and implementation to create robust risk assessment and adverse event reporting, physicians and their patients are likely to be at risk from medical errors caused by software-related problems in medical devices.

Medical device recalls and the FDA approval process.

BACKGROUND: Unlike prescription drugs, medical devices are reviewed by the US Food and Drug Administration (FDA) using 2 alternative regulatory standards: (1) premarket approval (PMA), which requires clinical testing and inspections; or (2) the 510(k) process, which requires that the device be similar to a device already marketed (predicate device). The second standard is intended for devices that the FDA deems to involve low or moderate risk. METHODS: We analyzed the FDA's high-risk List of Device Recalls from 2005 through 2009. Using FDA data, we determined whether the recalled devices were approved by the more rigorous (PMA) process, the 510(k) process, or were exempt from FDA review. RESULTS: There were 113 recalls from 2005 through 2009 that the FDA determined could cause serious health problems or death. Only 21 of the 113 devices had been approved through the PMA process (19%). Eighty were cleared through the 510(k) process (71%), and an additional 8 were exempt from any FDA regulation (7%). Cardiovascular devices comprised the largest recall category, with 35 of the high-risk recalls (31%); two-thirds were cleared by the 510(k) process (66%; n = 23). Fifty-one percent of the high-risk recalls were in 5 other device categories: general hospital, anesthesiology, clinical chemistry, neurology, or ophthalmology. CONCLUSIONS: Most medical devices recalled for life-threatening or very serious hazards were originally cleared for market using the less stringent 510(k) process or were considered so low risk that they were exempt from review (78%). These findings suggest that reform of the regulatory process is needed to ensure the safety of medical devices.