ArticleJAMA2023
Association Between Regulatory Submission Characteristics and Recalls of Medical Devices Receiving 510(k) Clearance.
Article in JAMA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Two decades of growth and trends in the FDA authorization of digital medical devices.NPJ digital medicine · 2026Article
- Clinical Evidence and FDA Recalls of Artificial Intelligence-Enabled Medical Devices.JAMA network open · 2026Article
- Device malfunctions and patient harm in robotic-assisted prostatectomy: a 17-year review of the FDA MAUDE database.Journal of robotic surgery · 2026Article
- Regulatory Challenges and Opportunities: A Review of U.S. Food and Drug Administration-Approved Artificial Intelligence and Machine Learning-Enabled Cardiovascular Devices.Therapeutic innovation & regulatory science · 2026Review
- Scaling medical device regulatory science using large language models.NPJ digital medicine · 2026Article
- Risk of Recall Among Plastic Surgery Devices Cleared Through the FDA 510(k) Pathway.Aesthetic surgery journal. Open forum · 2026Article
- Multiscale Design of Dental Restorative Materials: Mechanistic Foundations, Technological Innovations, and Clinical Translation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Competitive value of acquiring novel FDA product codes for medical device manufacturers: an original investigation.npj health systems · 2025Article
- Benefit-Risk Reporting for FDA-Cleared Artificial Intelligence-Enabled Medical Devices.JAMA health forum · 2025Article
- Generalizability of FDA-Approved AI-Enabled Medical Devices for Clinical Use.JAMA network open · 2025Article
- Late adverse event reporting from medical device manufacturers to the US Food and Drug Administration: cross sectional study.BMJ (Clinical research ed.) · 2025Article
- Scoping review on regulation, implementation and postmarket surveillance of medical devices.PloS one · 2025Article
- Leveraging natural language processing to aggregate field safety notices of medical devices across the EU.NPJ digital medicine · 2024Article
- The lucent yet opaque challenge of regulating artificial intelligence in radiology.NPJ digital medicine · 2024Article
- Beyond the 510(k): The regulation of novel moderate-risk medical devices, intellectual property considerations, and innovation incentives in the FDA's De Novo pathway.NPJ digital medicine · 2024Article
- Identification of predicate creep under the 510(k) process: A case study of a robotic surgical device.PloS one · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Most regulated medical devices enter the US market via the 510(k) regulatory submission pathway, wherein manufacturers demonstrate that applicant devices are "substantially equivalent" to 1 or more "predicate" devices (legally marketed medical devices with similar intended use). Most recalled medical devices are 510(k) devices. Objective: To examine the association between characteristics of predicate medical devices and recall probability for 510(k) devices. Design, Setting, and Participants: In this exploratory cross-sectional analysis of medical devices cleared by the US Food and Drug Administration (FDA) between 2003 and 2018 via the 510(k) regulatory submission pathway, linear probability models were used to examine associations between a 510(k) device's recall status and characteristics of its predicate medical devices. Public documents for the 510(k) medical devices were collected using FDA databases. A text extraction algorithm was applied to identify predicate medical devices cited in 510(k) regulatory submissions. Algorithm-derived metadata were combined with 2003-2020 FDA recall data. Exposures: Citation of predicate medical devices with certain characteristics in 510(k) regulatory submissions, including the total number of predicate medical devices cited by the applicant device, the age of the predicate medical devices, the lack of similarity of the predicate medical devices to the applicant device, and the recall status of the predicate medical devices. Main Outcomes and Measures: Class I or class II recall of a 510(k) medical device between its FDA regulatory clearance date and December 31, 2020. Results: The sample included 35 176 medical devices, of which 4007 (11.4%) were recalled. The applicant devices cited a mean of 2.6 predicate medical devices, with mean ages of 3.6 years and 7.4 years for the newest and oldest, respectively, predicate medical devices. Of the applicant devices, 93.9% cited predicate medical devices with no ongoing recalls, 4.3% cited predicate medical devices with 1 ongoing class I or class II recall, 1.0% cited predicate medical devices with 2 ongoing recalls, and 0.8% cited predicate medical devices with 3 or more ongoing recalls. Applicant devices citing predicate medical devices with 3 or more ongoing recalls were significantly associated with a 9.31-percentage-point increase (95% CI, 2.84-15.77 percentage points) in recall probability compared with devices without ongoing recalls of predicate medical devices, or an 81.2% increase in recall probability relative to the mean recall probability. A 1-SD increase in the total number of predicate medical devices cited by the applicant device was significantly associated with a 1.25-percentage-point increase (95% CI, 0.62-1.87 percentage points) in recall probability, or an 11.0% increase in recall probability relative to the mean recall probability. A 1-SD increase in the newest age of a predicate medical device was significantly associated with a 0.78-percentage-point decrease (95% CI, 1.29-0.30 percentage points) in recall probability, or a 6.8% decrease in recall probability relative to the mean recall probability. Conclusions and Relevance: This exploratory cross-sectional study of 510(k) medical devices cleared by the FDA between 2003 and 2018 demonstrated significant associations between 510(k) submission characteristics and recalls of medical devices. Further research is needed to understand the implications of these associations.
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