Evidence map›Paper›PMID 32315070›Full record

ArticleJAMA network open2020

Assessment of Clinical Trials Supporting US Food and Drug Administration Approval of Novel Therapeutic Agents, 1995-2017.

Audrey D Zhang, Jeremy Puthumana, Nicholas S Downing, Nilay D Shah, Harlan M Krumholz, Joseph S Ross

Abstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Navigating the Prescription Drug Information System.Clinical pharmacology and therapeutics · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Audrey D ZhangNew York University School of Medicine, New York.
Jeremy PuthumanaYale School of Medicine, New Haven, Connecticut.
Nicholas S DowningBrigham and Women's Hospital, Boston, Massachusetts.
Nilay D ShahDivision of Health Care Policy and Research and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota.
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut.
Joseph S RossCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Importance: Since the introduction of the Fast Track designation in 1988, the number of special regulatory programs available for the approval of new drugs and biologics by the US Food and Drug Administration (FDA) has increased, offering the agency flexibility with respect to evidentiary requirements. Objective: To characterize pivotal efficacy trials supporting the approval of new drugs and biologics during the past 3 decades. Design, Setting, and Participants: This cross-sectional study included 273 new drugs and biologics approved by the FDA for 339 indications from 1995 to 1997, from 2005 to 2007, and from 2015 to 2017. Main Outcomes and Measures: Therapeutics were classified by product type and therapeutic area as well as orphan designation and use of special regulatory programs, such as Priority Review and Accelerated Approval. Pivotal trials were characterized by use of randomization, blinding, types of comparators, primary end points, number of treated patients, and trial duration, both individually and aggregated by each indication approval. Results: A total of 273 new drugs and biologics were approved by the FDA in these 3 periods (107 [39.2%] in 1995-1997; 57 [20.9%] in 2005-2007; and 109 [39.9%] in 2015-2017), representing 339 indications (157 [46.3%], 64 [18.9%], and 118 [34.8%], respectively). The proportion of therapeutic approvals using at least 1 special regulatory program increased (37 [34.6%] in 1995-1997; 33 [57.9%] in 2005-2007; and 70 [64.2%] in 2015-2017), as did indication approvals receiving an orphan designation (20 [12.7%] in 1995-1997; 17 [26.6%] in 2005-2007, and 45 [38.1%] in 2015-2017). The most common therapeutic areas differed over time (infectious disease, 53 [33.8%] in 1995-1997 vs cancer, 32 [27.1%] in 2015-2017). When considering the aggregate pivotal trials supporting each indication approval, the proportion of indications supported by at least 2 pivotal trials decreased (80.6% [95% CI, 72.6%-87.2%] in 1995-1997; 60.3% [95% CI, 47.2%-72.4%] in 2005-2007; and 52.8% [95% CI, 42.9%-62.6%] in 2015-2017; P < .001). The proportion of indications supported by only single-group pivotal trials increased (4.0% [95% CI, 1.3%-9.2%] in 1995-1997; 12.7% [95% CI, 5.6%-23.5%] in 2005-2007; and 17.0% [95% CI, 10.4%-25.5%] in 2015-2017; P = .001), whereas the proportion supported by at least 1 pivotal trial of 6 months' duration increased (25.8% [95% CI, 18.4%-34.4%] in 1995-1997; 34.9% [95% CI, 23.3%-48.0%] in 2005-2007; and 46.2% [95% CI, 36.5%-56.2%] in 2015-2017; P = .001). Conclusions and Relevance: In this study, more recent FDA approvals of new drugs and biologics were based on fewer pivotal trials, which, when aggregated by indication, had less rigorous designs but longer trial durations, suggesting an ongoing need for continued evaluation of therapeutic safety and efficacy after approval.

Indexed as

Pharmaceutical PreparationsBiological ProductsClinical Trials as TopicCross-Sectional StudiesDrug ApprovalHumansUnited StatesUnited States Food and Drug AdministrationBiological ProductsPharmaceutical Preparations

Identifiers

PMID32315070
PMCPMC7175081

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.