Publications by Year: 2014

IMPORTANCE: The US Food and Drug Administration (FDA) evaluates high-risk medical devices such as cardiac implantable electronic devices (CIEDs), including pacemakers, implantable cardioverter-defibrillators, and cardiac resynchronization therapy devices, via the premarket approval (PMA) process, during which manufacturers submit clinical data demonstrating safety and effectiveness. Subsequent changes to approved high-risk devices are implemented via "supplements," which may not require additional clinical testing.

OBJECTIVE: To characterize the prevalence and characteristics of changes to CIEDs made through the PMA supplement process.

DESIGN: Using the FDA's PMA database, we reviewed all CIEDs approved as original PMAs or supplements from 1979 through 2012. For each supplement, we collected the date approved, type of supplement (panel-track, 180-day, real-time, special, and 30-day notice), and the nature of the changes. We calculated the number of supplements approved per PMA and analyzed trends relating to different supplement regulatory categories over time. For supplements approved via the 180-day regulatory pathway, which often involve significant design changes, from 2010-2012, we identified how often additional clinical data were collected.

RESULTS: From 1979-2012, the FDA approved 77 original and 5829 supplement PMA applications for CIEDs, with a median of 50 supplements per original PMA (interquartile range [IQR], 23-87). Excluding manufacturing changes that do not alter device design, the number of supplements approved each year was stable around a mean (SD) of 2.6 (0.9) supplements per PMA per year. Premarket approvals remained active via successive supplements over a median period of 15 years (IQR, 8-20), and 79% of the 77 original PMAs approved during our study period were the subject of at least 1 supplement in 2012. Thirty-seven percent of approved supplements involved a change to the device's design. Among 180-day supplements approved from 2010-2012, 23% (15/64) included new clinical data to support safety and effectiveness.

CONCLUSIONS AND RELEVANCE: Many CIED models currently used by clinicians were approved via the PMA supplement process, not as original PMAs. Most new device models are deemed safe and effective without requiring new clinical data, reinforcing the importance of rigorous postapproval surveillance of these devices.

Since 1976, the US Food and Drug Administration (FDA) has used the premarket approval (PMA) process to approve high-risk medical devices, including implantable cardioverter defibrillators (ICDs), coronary stents, and artificial heart valves. The PMA process is widely viewed as a rigorous evaluation of device safety and effectiveness, though recent recalls-most notably related to underperforming ICD leads-have raised concerns about whether physicians and patients should sometimes be more wary about devices approved via this pathway. The FDA must utilize a "least burdensome" approach to approve new medical devices, and many widely used device models have been approved as supplements to existing PMA-approved devices with limited clinical testing. A recent Supreme Court ruling has made it difficult for patients harmed by unsafe PMA-approved devices to seek damages in court. Cardiologists who utilize high-risk medical devices should be aware that FDA approval of new devices relies on variable levels of evidence and does not necessarily indicate improved effectiveness over existing models. Clinician and patient engagement in postmarket surveillance and comparative effectiveness research remains imperative.

BACKGROUND: Implantable cardioverter-defibrillator (ICD) generator replacement at the end of expected battery life accounts for a substantial proportion of all ICD implant procedures. However, little is known about the predictors of mortality following ICD generator replacement.

OBJECTIVE: The purpose of this study was to identify clinical and procedural factors associated with death following ICD generator replacement.

METHODS: Patients from the National Cardiovascular Data Registry (NCDR) ICD Registry receiving ICD generator replacements at the end of device battery life between January 1, 2005, and March 30, 2010, were eligible. Predictors of mortality were determined using multivariable Cox regression.

RESULTS: Analysis of 111,826 patients (mean age 70.7 ± 12.4, 75.5% male) revealed 1-, 3-, and 5-year mortality of 9.8%, 27.0%, and 41.2%, respectively. After adjustment, atrial fibrillation (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.20-1.27) and congestive heart failure (HR 1.21, 95% CI 1.16-1.27) predicted worse survival. In addition to older age (HR 1.43, 95% CI 1.41-1.45), several noncardiac conditions were also associated with poorer survival, including chronic lung disease (HR 1.53, 95% CI 1.49-1.57), cerebrovascular disease (HR 1.28, 95% CI 1.24-1.32), diabetes (HR 1.27, 95% CI 1.23-1.30), and lower glomerular filtration rate (HR 1.15 for each 10-unit increment decline, 95% CI 1.14-1.16). In the absence of a non-ICD control group, risk reduction provided by ICD therapy in this cohort is not known.

CONCLUSION: In addition to age, atrial fibrillation, and congestive heart failure, noncardiac comorbidities are associated with higher mortality following ICD replacement, which should be considered in the decision to undergo this procedure.

Agent-based models (ABMs) have been widely used to study socioecological systems. They are useful for studying such systems because of their ability to incorporate micro-level behaviors among interacting agents, and to understand emergent phenomena due to these interactions. However, ABMs are inherently stochastic and require proper handling of uncertainty. We propose a simulation framework based on quantitative uncertainty and sensitivity analyses to build parsimonious ABMs that serve two purposes: exploration of the outcome space to simulate low-probability but high-consequence events that may have significant policy implications, and explanation of model behavior to describe the system with higher accuracy. The proposed framework is applied to the problem of modeling farmland conservation resulting in land use change. We employ output variance decomposition based on quasi-random sampling of the input space and perform three computational experiments. First, we perform uncertainty analysis to improve model legitimacy, where the distribution of results informs us about the expected value that can be validated against independent data, and provides information on the variance around this mean as well as the extreme results. In our last two computational experiments, we employ sensitivity analysis to produce two simpler versions of the ABM. First, input space is reduced only to inputs that produced the variance of the initial ABM, resulting in a model with output distribution similar to the initial model. Second, we refine the value of the most influential input, producing a model that maintains the mean of the output of initial ABM but with less spread. These simplifications can be used to 1) efficiently explore model outcomes, including outliers that may be important considerations in the design of robust policies, and 2) conduct explanatory analysis that exposes the smallest number of inputs influencing the steady state of the modeled system.

Regulatory bodies weighing market approval for novel medical devices must balance the benefits and potential hazards carefully. We performed a legal and policy review of appraoches in the US, EU, Japan, and China to device regulation with a focus on postmarket surveillance. These markets share broad features such as a heavy reliance on passive adverse event collection, reflected by growing enthusiasm for more active and dynamic mechanisms such as unique device identification. More immediately, US and EU systems might benefit from scheduled, compulsory, and consequential re-examination of select devices, as is done in Japan and China, in order to strengthen post-market protection of patients and bolster public health.