Postmarketing commitments for novel drugs and biologics approved by the US Food and Drug Administration: a cross-sectional analysis

Objective The US Food and Drug Administration (FDA) clears moderate-risk devices via the 510(k) process based on substantial equivalence to previously cleared devices; evidence of safety and effectiveness is not required. We characterized the premarket evidence supporting FDA clearance of otolaryngologic devices. Study Design Retrospective cross-sectional analysis. Setting Publicly available FDA documents. Subjects and Methods Recently cleared (1997-2016) moderate-risk otolaryngologic devices were categorized by type (diagnostic/therapeutic), subspecialty, implantable designation (yes/no), and recall history (yes/no). Supporting evidence was categorized by type (clinical/nonclinical/none; nonclinical and clinical mutually inclusive) and public availability of nonclinical and clinical performance data (available/not provided/not applicable). Results Between 1997 and 2016, the FDA cleared 377 moderate-risk otolaryngologic devices. The majority were therapeutic (n = 240/377 [63.7%]) and otologic (n = 311/377 [82.5%]); roughly one-third (n = 121/377 [32.1%]) were implantable. Few (n = 10/377 [2.7%]) devices were subject to recall. FDA documents summarizing premarket evidence were accessible for two-thirds (n = 247/377 [65.5%]) of devices. Among these devices, one-quarter (n = 66/247 [26.7%]) were supported by clinical evidence. The majority (n = 177/247 [71.7%]) were supported by nonclinical evidence, although nearly one-quarter (n = 58/247 [23.5%]) were cleared without supporting evidence. Therapeutic devices were more often cleared without supporting evidence (therapeutic: n = 53/170 [31.2%]; diagnostic: n = 5/77 [6.5%]; P < .0001). Nonclinical and clinical performance data were rarely available (nonclinical: n = 49/247 [19.8%]; clinical: n = 32/247 [13.0%]) within public summaries. Conclusion The FDA cleared most moderate-risk otolaryngologic devices for marketing via the 510(k) process without clinical evidence of safety and effectiveness. Otolaryngologists should be aware of limitations in premarket evidence when considering the adoption of new devices into clinical practice.

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Characterization of Pharmacogenetic Information in Food and Drug Administration Drug Labeling and the Table of Pharmacogenetic Associations

Annals of Pharmacotherapy ◽

10.1177/1060028020983049 ◽

2020 ◽

pp. 106002802098304

Author(s):

Christine M. Cheng ◽

Thomas W. So ◽

Jeff L. Bubp

Keyword(s):

Clinical Outcome ◽

Drug Administration ◽

Gene Pair ◽

Drug Disposition ◽

Food And Drug Administration ◽

Cross Sectional ◽

Drug Labeling ◽

Gene Pairs ◽

Genetic Test Results ◽

Sectional Analysis

Background: The US Food and Drug Administration (FDA) recommends using only FDA-reviewed pharmacogenetic information to make prescribing decisions based on genetic test results. Such information is available in drug labeling and in the Table of Pharmacogenetic Associations (“Associations table”). Objective: To compile a list of drug-gene pairs from drug labeling and the Associations table and categorize the pharmacogenetic information and clinical outcome associated with each drug-gene pair. Methods: This was a cross-sectional analysis of pharmacogenetic information in the Associations table and individual drug labeling in March 2020. We used the Table of Pharmacogenomic Biomarkers in Drug Labeling to identify drug labels to review. We categorized the pharmacogenetic information for each drug-gene pair according to whether the purpose was to describe (1) polymorphisms affecting drug disposition (metabolism or transport), (2) polymorphisms affecting a direct drug target, (3) variants associated with adverse drug reaction (ADR) susceptibility, (4) variants associated with therapeutic failure, (5) a biomarker-defined indication, or (6) a biomarker-defined ADR. We also categorized the clinical outcome—efficacy, safety, or unknown—associated with each drug-gene pair. We reported counts and proportions of drug-gene pairs in each pharmacogenetic information and clinical outcome category. Results: We identified 308 drug-gene pairs, of which 36% were associated with a biomarker-defined drug indication, 33% with polymorphic drug metabolism, and 28% with ADR susceptibility. Most drug-gene pairs (n = 267, 87%) were associated with an efficacy or safety-related outcome. Conclusion and Relevance: FDA-reviewed pharmacogenetic information is available for more than 300 drug-gene pairs and can help guide prescribing decisions.

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Obesity and health-related quality of life: a cross-sectional analysis of the US population

International Journal of Obesity ◽

10.1038/sj.ijo.0802396 ◽

2003 ◽

Vol 27 (10) ◽

pp. 1227-1232 ◽

Cited By ~ 182

Author(s):

M K Hassan ◽

A V Joshi ◽

S S Madhavan ◽

M M Amonkar

Keyword(s):

Quality Of Life ◽

Health Related Quality ◽

Cross Sectional ◽

Cross Sectional Analysis ◽

The Us ◽

Related Quality ◽

Health Related ◽

Sectional Analysis

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Missed Opportunities for Influenza and Pneumococcal Vaccinations in the Elderly in the US - A Cross-Sectional Analysis

Value in Health ◽

10.1016/j.jval.2018.04.1083 ◽

2018 ◽

Vol 21 ◽

pp. S158

Author(s):

OO Olasupo ◽

J Brown ◽

R Segal

Keyword(s):

The Elderly ◽

Cross Sectional ◽

Missed Opportunities ◽

Cross Sectional Analysis ◽

The Us ◽

Sectional Analysis

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Correlations Between Hospitals’ Social Media Presence and Reputation Score and Ranking: Cross-Sectional Analysis (Preprint)

10.2196/preprints.9713 ◽

2017 ◽

Author(s):

Justin D Triemstra ◽

Rachel Stork Poeppelman ◽

Vineet M Arora

Keyword(s):

Social Media ◽

Correlation Coefficients ◽

Children's Hospitals ◽

Cross Sectional ◽

Cross Sectional Analysis ◽

Children’S Hospitals ◽

Reputation Score ◽

The Us ◽

Social Media Presence ◽

Sectional Analysis

BACKGROUND The US News and World Report reputation score correlates strongly with overall rank in adult and pediatric hospital rankings. Social media affects how information is disseminated to physicians and is used by hospitals as a marketing tool to recruit patients. It is unclear whether the reputation score for adult and children’s hospitals relates to social media presence. OBJECTIVE The objective of our study was to analyze the association between a hospital’s social media metrics and the US News 2017-2018 Best Hospital Rankings for adult and children’s hospitals. METHODS We conducted a cross-sectional analysis of the reputation score, total score, and social media metrics (Twitter, Facebook, and Instagram) of hospitals who received at least one subspecialty ranking in the 2017-2018 US News publicly available annual rankings. Regression analysis was employed to analyze the partial correlation coefficients between social media metrics and a hospital’s total points (ie, rank) and reputation score for both adult and children’s hospitals while controlling for the bed size and time on Twitter. RESULTS We observed significant correlations for children’s hospitals’ reputation score and total points with the number of Twitter followers (total points: r=.465, P<.001; reputation: r=.524, P<.001) and Facebook followers (total points: r=.392, P=.002; reputation: r=.518, P<.001). Significant correlations for the adult hospitals reputation score were found with the number of Twitter followers (r=.848, P<.001), number of tweets (r=.535, P<.001), Klout score (r=.242, P=.02), and Facebook followers (r=.743, P<.001). In addition, significant correlations for adult hospitals total points were found with Twitter followers (r=.548, P<.001), number of tweets (r=.358, P<.001), Klout score (r=.203, P=.05), Facebook followers (r=.500, P<.001), and Instagram followers (r=.692, P<.001). CONCLUSIONS A statistically significant correlation exists between multiple social media metrics and both a hospital’s reputation score and total points (ie, overall rank). This association may indicate that a hospital’s reputation may be influenced by its social media presence or that the reputation or rank of a hospital drives social media followers.

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Evaluation, Treatment, and Insurance Coverage for Couples With Male Factor Infertility in the US: A Cross-Sectional Analysis of Survey Data

Urology ◽

10.1016/j.urology.2019.12.035 ◽

2020 ◽

Vol 139 ◽

pp. 97-103

Author(s):

Clara Helene Glazer ◽

Jake Anderson-Bialis ◽

Deborah Anderson-Bialis ◽

Michael L. Eisenberg

Keyword(s):

Survey Data ◽

Insurance Coverage ◽

Male Factor Infertility ◽

Male Factor ◽

Cross Sectional ◽

Cross Sectional Analysis ◽

The Us ◽

Sectional Analysis

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US Food and Drug Administration utilization of postmarketing requirements and postmarketing commitments, 2009–2018

Clinical Trials ◽

10.1177/17407745211005044 ◽

2021 ◽

pp. 174077452110050

Author(s):

Joshua J Skydel ◽

Audrey D Zhang ◽

Sanket S Dhruva ◽

Joseph S Ross ◽

Joshua D Wallach

Keyword(s):

Drug Administration ◽

Clinical Studies ◽

Clinical Evidence ◽

Food And Drug Administration ◽

Median Number ◽

Cross Sectional Study ◽

Interquartile Range ◽

New Drugs ◽

Cross Sectional ◽

The Us

Background/Aims The US Food and Drug Administration outlines clinical studies as postmarketing requirements and commitments to be fulfilled following approval of new drugs and biologics (“therapeutics”). Regulators have increasingly emphasized lifecycle evaluation of approved therapeutics, and postmarketing studies are intended to advance our understanding of therapeutic safety and efficacy. However, little is known about the indications that clinical studies outlined in postmarketing requirements and commitments investigate, including whether they are intended to generate evidence for approved or other clinical indications. Therefore, we characterized US Food and Drug Administration postmarketing requirements and commitments for new therapeutics approved from 2009 to 2018. Methods We conducted a cross-sectional study of all novel therapeutics, including small-molecule drugs and biologics, receiving original US Food and Drug Administration approval from 2009 to 2018, using approval letters accessed through the Drug@FDA database. Outcomes included the number and characteristics of US Food and Drug Administration postmarketing requirements and commitments for new therapeutics at original approval, including the types of studies outlined, the indications to be investigated, and the clinical evidence to be generated. Results From 2009 to 2018, the US Food and Drug Administration approved 343 new therapeutics with 1978 postmarketing requirements and commitments. Overall, 750 (37.9%) postmarketing requirements and commitments outlined clinical studies. For 71 of 343 (20.7%) therapeutics, no postmarketing requirements or commitments for clinical studies were outlined, while at least 1 was outlined for 272 (79.3%; median 2 (interquartile range: 1–4)). Among these 272 therapeutics, the number of postmarketing requirements and commitments for clinical studies per therapeutic did not change from 2009 (median: 2 (interquartile range: 1–4)) to 2018 (median: 2 (interquartile range: 1–3)). Among the 750 postmarketing requirements and commitments for clinical studies, 448 (59.7%) outlined new prospective cohort studies, registries, or clinical trials, while the remainder outlined retrospective studies, secondary analyses, or completion of ongoing studies. Although 455 (60.7%) clinical studies investigated only original approved therapeutic indications, 123 (16.4%) enrolled from an expansion of the approved disease population and 61 (8.1%) investigated diseases unrelated to approved indications. Conclusions The US Food and Drug Administration approves most new therapeutics with at least 1 postmarketing requirement or commitment for a clinical study, and outlines investigations of safety or efficacy for both approved and unapproved indications. The median number of 2 clinical studies outlined has remained relatively constant over the last decade. Given increasing emphasis by the US Food and Drug Administration on faster approval and lifecycle evaluation of therapeutics, these findings suggest that more postmarketing requirements and commitments may be necessary to address gaps in the clinical evidence available for therapeutics at approval.

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