Evidence map›Paper›PMID 34665689›Full record

ArticleThe American journal of bioethics : AJOB2021

Helpful Lessons and Cautionary Tales: How Should COVID-19 Drug Development and Access Inform Approaches to Non-Pandemic Diseases?

Holly Fernandez Lynch, Arthur Caplan, Patricia Furlong, Alison Bateman-House

Abstract read
PubMed Publisher
In one paragraph

Article in The American journal of bioethics : AJOB, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Change in effectiveness of sotrovimab for preventing hospitalization and mortality for at-risk COVID-19 outpatients during an Omicron BA.1 and BA.1.1-predominant phase.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2023
    Observational
  5. Observational
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Holly Fernandez LynchUniversity of Pennsylvania.
Arthur CaplanNYU Langone Health.
Patricia FurlongParent Project Muscular Dystrophy.
Alison Bateman-HouseNYU Langone Health.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

After witnessing extraordinary scientific and regulatory efforts to speed development of and access to new COVID-19 interventions, patients facing other serious diseases have begun to ask "where's our Operation Warp Speed?" and "why isn't Emergency Use Authorization an option for our health crises?" Although this pandemic bears a number of unique features, the response to COVID-19 offers translatable lessons, in both its successes and failures, for non-pandemic diseases. These include the importance of collaborating across sectors, supporting the highest-priority research efforts, adopting rigorous and innovative trial designs, and sharing reliable information quickly. In addition, the regulatory response to the pandemic demonstrates that lowering standards for marketing authorization can result in increased safety concerns, missed opportunities for research and treatment, and delays in determining what works. Accordingly, policymakers and patient advocates seeking to build on the COVID-19 experience for non-pandemic diseases with unmet treatment needs should focus their efforts on promoting robust and efficient research designs, improving access to clinical trials, and facilitating use of the Food and Drug Administration's existing Expanded Access pathway.

Indexed as

COVID-19PandemicsDrug DevelopmentHumansSARS-CoV-2clinical researchCOVID-19emergency use authorizationexpanded accessOperation Warp Speedpandemic response

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.