A model-based approach to device evaluation may offer decision-changing insights into medical device efficacy and durability, according to a perspective published Oct. 20 New England Journal of Medicine.
Lisa G. Suter, MD, of the Yale School of Medicine, and colleagues, used a “state-transition” computer-simulation model to evaluate the likelihood of having to repair or replace a knee arthroplasty. According to the article, more than 600,000 total knee arthroplasty procedures are performed each year, with 85 percent of recipients reporting functional improvement against an annual failure rate of 0.5 to 1.6 percent. Each year, the FDA approves more than 35 new systems or components for the procedure.
According to Suter’s model, after 20 years, 19 percent of patients who were healthy and between ages 50 and 59 at the time of a total knee arthroplasty would have died, as would 86 percent of those who were between ages 70 and 79 who had coexisting conditions. Of the former group, 65 percent would have been alive with their original implant, and 11 percent of the latter would as well.
The risk of requiring revision surgery, they wrote, would be higher among younger patients, which can partly be attributed to the higher likelihood of death among older patients.
“Our findings suggest that there can be no one-size-fits-all approach to the use of innovative devices,” wrote Suter et al. “In the case of total knee arthroplasty, a patient’s life expectancy has a marked effect on his or her anticipated benefit from improvements in durability over existing implants, whose survival rates are already excellent.”
Though lowering the risk of device failure is beneficial, even if minutely, the improvements are not likely to equally benefit all patients, the authors wrote, and innovative technologies could increase the risk of short-term complications. “Furthermore, these technologies typically cost more than their predecessors,” they added. “These considerations may further restrict the populations in which an innovative device offers good value.”
While the Institute of Medicine has called for the replacement of the 510(k) process, the Yale researchers suggested traditional approaches to clinical investigation don’t evaluate all the necessary considerations, such as likely improvements in efficacy and durability. A model-based approach may bring important clarifications to light.
“Model-based evaluations could help define the thresholds for complication and efficacy rates and costs that would be required to improve on existing device performance while maintaining acceptable economic value,” the authors concluded. “This information could then inform postmarketing surveillance efforts, triggering reviews at prespecified efficacy or complication thresholds and facilitating rapid application of new data as they become available.”