Researchers at the Yale School of Medicine and Harvard Medical School found that a loophole in existing regulations allowed manufacturers to gain approval from the US Food and Drug Administration for unsafe medical devices.
US Food and Drug Administration
A recent study led by researchers at the Yale School of Medicine and Harvard Medical School found that a loophole in existing regulations allowed manufacturers to gain approval from the US Food and Drug Administration for unsafe medical devices.
This work was led by Kushal Kadakia, first author and MD candidate at Harvard Medical School, and Harlan Krumholz ’80, senior author, Harold H. Hines, Jr. Professor of Medicine and director of the Center for Research and Evaluation of Outcomes. Their study found empirical evidence that medical devices approved based on a device previously recalled through the 510(k) regulatory pathway were significantly more likely to be subject to a Class I Recall, the FDA’s most stringent designation for recalls.
“The 510(k) path does not require medical devices to undergo further testing as long as they can show that they are substantially related to previously approved devices, known as predicates,” said Kadakia.
This path streamlines the approval of medical devices that may have only minor changes from previously approved iterations and are being used for the same purpose. Actually, more than 95 percent of new devices are cleared by the FDA through this route.
But due to a regulatory loophole, the predicates themselves may not actually be safe for human use.
“As the law is written, if the FDA took it off the market, it can’t be used as a predicate, but if the company took it off the market, you retain the ability to reintroduce a new one that is substantially equivalent. and still be used for this unsafe purpose,” says Krumholz.
The study focused on medical devices subject to a Class I recall. This type of recall is issued when a medical device has a reasonable likelihood of causing serious adverse health consequences, including death.
Previous studies have provided case studies showing harm caused by approved devices using collapsed predicates. Kadakia worked on two such studies of a sleep apnea catheter and device that were subsequently subjected to Class I Recalls. This new study is unique, however, in its scope.
“We were able to go through several years and identify all the devices that had these recalls, instead of picking one or two,” Krumholz said. “We were able to look at a comprehensive group and give a more representative view.”
This approach was made possible by recent advances in machine learning and data science. Because the FDA database only contains decision letters, which list the reasoning behind an authorization, it can be difficult to find out which devices have been authorized using a specific device as a predicate. Without the use of new computational tools, it would be time consuming to map medical device lineages. However, the researchers were able to build these strains in partnership with an AI company and manually confirm the results from the AI database.
The researchers found a 6.4-fold increase in recall rates of approved medical devices using collapsed predicates when compared to non-collapsed predicates. Given that each device can have tens of thousands of units and be used throughout the medical process, these recalls can have widespread effects.
The New and Untested Devices Safety Act of 2012 was an earlier attempt to fix this problem, but it didn’t get enough votes. The researchers hope that this new study can reinvigorate the US Congress to at least start discussing the 510(k) path again.
“The remembered predicate gap is not an unknown quantity in Washington,” Kadakia said. “We now provide empirical evidence in a systematic way of how this loophole is being used to cause harm.”
The study authors also acknowledge that more work can be done using these new computational methods.
“We limited the analysis to one generation, but it would be interesting to look at children of children of remembered predicates and so on,” said César Caraballo, a postdoctoral associate at the Yale School of Medicine.
Krumholz hopes that more evidence will strengthen Congress’ ability to enact wise and empirically sound legislation. This is especially critical as medical devices receive far less research attention than drugs because they are incorporated throughout the medical process rather than at the point of care, Kadakia explained.
“If we could add unique device identifiers to claim forms, we could quantify the amount of spend that was authorized through the predicate recall loophole,” said Kadakia. “We could also determine whether the reasons for new recalls and predicate recalls are similar.”
In fiscal year 2022, 149 medical device products were subject to Class I recalls.