US FDA Advisory Panel Members’ Assessment of Premarket Approval Process and Suggestions for Improvement
Bibliographic record
Abstract
Importance: The manufacturing and marketing of medical devices is regulated by the US Food and Drug Administration (FDA), and the FDA premarket approval (PMA) process evaluates the safety and effectiveness of medical devices. The PMA process includes a detailed scientific, regulatory and quality system review and is critical to ensure that novel devices are safe, effective, and meet the needs of patients. Objective: To survey current voting members serving on panels of the FDA's Medical Devices Advisory Committee to better characterize panel decision-making and identify steps for improvement. Design, Setting, and Participants: This qualitative survey study included 36 questions that were mailed to FDA device panelists regarding their opinions on the influence of sources of information, pivotal trial design, quality of evidence, panel composition and internal deliberative process, time allocation, and impartiality of the FDA. The survey was mailed to the members of all 18 FDA device panels in January and February 2017. Data were collected from January to May 2017 and analyzed from 2018 to 2019. Exposures: Respondents read and returned the aforementioned paper survey, while nonrespondents did not. Main Outcomes and Measures: The main outcomes included panel members' perceptions, and their implications for process improvement. χ2 or Fisher exact tests were used to test differences between subgroups. Results: Of 64 of 92 panel members who responded (69.6%), 38 of 64 (59.4%) were male, 3 of 63 (4.8%) were Black respondents, 46 of 63 (73.0%) were White respondents, and 36 of 60 (60.0%) were in academic practice. The mean (range) panel service was 6.8 (1-22) years with 3.9 (1-19) meetings attended. Overall, respondents considered information presented by the FDA unbiased, and 28 of 61 (45.9%) believed that pivotal trials were frequently well-designed, 55 of 62 respondents (88.7%) suggested FDA consult panel members preemptively regarding trial design and 54 of 64 (84.4%) regarding the device label. Most indicated that prior FDA approval of another device serving the same medical purpose (43 of 62 [69.4%]) or approval in other countries with comparable regulatory regimes, such as Canada and Europe (39 of 62 [62.9%]), would make them more likely to recommend approval. Respondents rated written information (50 of 60 [83.3%]), live presentations (43 of 58 [74.1%]), and prior professional knowledge (41 of 60 [68.3%]) as the most important sources of information in deciding whether to recommend approval. Additionally, 52 of 58 respondents (89.7%) recommended that a panel member-only executive session would allow more clarity and honesty in deliberations, and 33 of 59 (55.9%) believed a three-fourths majority appropriate for recommending approval, which would be a deviation from the current system in which an overall vote is reported without designation of a vote threshold. Conclusions and Relevance: In this survey study of FDA device panel members, respondents wanted improved study designs, more relevant clinical data, including from other countries, involvement of panelists in study design and device label development, and inclusion of an executive session. Demographically, panels could be made more diverse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".