Publications

IMPORTANCE

Postmarketing surveillance is critical to evaluating the safety and effectiveness of medical devices. The US Food and Drug Administration (FDA) may order the manufacturer of a high-risk device to conduct postmarketing surveillance studies, known as postapproval studies (PASs), at the time of approval.

OBJECTIVES

To understand the characteristics of PASs ordered in recent years and inform discussions about the direction of the PASs program.

DESIGN

Descriptive study of the PASs ordered for medical devices using the FDA's PASs website, the Premarket Approval database, and supplemental information provided by the FDA.

MAIN OUTCOMES AND MEASURES

The proportion of medical devices that received a PAS order and study characteristics.

RESULTS

Between January 1, 2005, and December 31, 2011, the FDA ordered 223 studies of 158 medical devices, including studies for 93 (48%) new high-risk devices approved during this period. The median required sample size for a study was 350 patients (interquartile range, 160-1500). If the protocol of a study was not in place at the time the device was approved, which occurred frequently, a median of 180 days elapsed until the protocol was agreed on. The FDA has never issued a warning letter or penalty owing to study delays, inadequate progress, or any other issue related to a PAS. Of the approved protocols, 41 (19%) were subsequently revised, including 29 (21%) protocols in place by application approval. Some studies generated significant clinical findings. The most common effect of a PAS finding after study completion was that the FDA requested a labeling change for 31 studies (53%).

CONCLUSIONS AND RELEVANCE

Postapproval studies have the potential to provide additional information to better understand medical device performance. However, small sample sizes, delays in reaching protocol agreement, and lack of availability of findings may hinder their ability to be clinically useful. Owing to the lack of information on the effect of studies, it is unclear whether the program achieves its aims. Improved completion and accessibility of PASs could help answer important questions of safety and effectiveness about medical devices. To better understand the real-world performance of these products, they should be better integrated with other sources of information about device performance.

Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB), is an intracellular pathogen of mononuclear phagocytes. Although M. tuberculosis has traditionally been thought to survive and replicate in macrophages, recent work in our laboratory and others has revealed that M. tuberculosis infects multiple subsets of mononuclear phagocytes in vivo and in vitro. In experimental animals, M. tuberculosis infects no fewer than five distinct cell subsets in the lungs, including resident alveolar macrophages and 4 types of cells that recruited to the lungs in response to inflammatory signals: neutrophils, monocytes, interstitial macrophages, and dendritic cells. A characteristic of the adaptive immune response in TB is that it is delayed for several weeks following infection, and we have determined that this delay is due to prolonged residence of the bacteria in lung phagocytes prior to acquisition of the bacteria by dendritic cells. Among the mechanisms used by M. tuberculosis to delay acquisition by dendritic cells is to inhibit apoptosis of alveolar macrophages and neutrophils, which sequester the bacteria and prevent their acquisition by dendritic cells in the early stages of infection. We hypothesize that each infected cell subset makes a distinct contribution to the overall biology of M. tuberculosis and allows the bacteria to evade elimination by T-cell responses and to avoid rapid killing by antimycobacterial drugs.

BACKGROUND

Low SES is associated with risk and protective factors for osteoporosis. However, there has been little examination of SES and osteoporosis in the U.S. Methods: We conducted a cross-sectional study of adults aged 50 or older in 2007–2008 NHANES, examining two predictors of SES: income and food insecurity. Our outcome was osteoporosis assessed from bone scans. Adjusted regression models (overall and gender-stratified) controlled for age, gender, race/ethnicity, education, BMI, smoking, alcohol consumption, physical activity, calcium and vitamin D, and medication use.

RESULTS

Of 2403 participants, 5% had osteoporosis. In adjusted models, there was a higher risk of osteoporosis in low-income (OR; 95% CI: 1.90;1.07–3.37) and food-insecure populations (3.48;1.43–8.48). There was a stronger association with food insecurity among women (4.91;2.40–10.0) than men (0.46;0.07–3.01).

CONCLUSIONS

Income and food insecurity may have significant implications not just for immediate nutritional outcomes, but also for conditions such as osteoporosis that develop over the lifespan.

Food insecurity has recently emerged as an important risk factor for HIV acquisition among women worldwide. No previous studies have used linked data that would permit investigation of the extent to which food insecurity may have differential associations with HIV transmission risk behaviors or symptoms of sexually transmitted infections (STIs) among men and women in the same households. We used nationally representative data on linked couples from the Nepal 2011 Demographic and Health Survey. The primary explanatory variable of interest was food insecurity, measured with a modified version of the Household Food Insecurity Access Scale. In multivariable logistic regression models, women in food insecure households were less likely to report recent condom use and more likely to report symptoms consistent with STIs. These patterns were absent among men. Interventions targeting food insecurity may have beneficial implications for both HIV prevention and gender equity in Nepal.

Antibiotic resistance is a global crisis driven by appropriate and inappropriate antibiotic use to treat human illness and promote animal growth. The antimicrobial resistance epidemic continues to spread due to the triple threat of unfettered access, minimal product regulation and oversight of antibiotic prescription, and lack of clinical diagnostic tools to support antibiotic de-escalation in low-resource settings. In high-resource settings, evidence-based strategies have improved the appropriateness of antibiotic use, limiting the spread of drug-resistant organisms and reducing hospital-associated infections, strategies which may also be effective to stop the spread of resistance in resource-poor countries. Current research and surveillance efforts on antimicrobial resistance and hospital-associated infections in low-resource settings are extremely limited and largely focused on intensive care units. Many challenges exist to improving antibiotic use and infection control in resource-limited settings, and turning the tide requires intensifying research and surveillance, antimicrobial stewardship, and developing new bedside diagnostic tools for bacterial infections and antimicrobial susceptibility.