Evidence map›Paper›PMID 35780471›Full record

ArticlePharmaceutical medicine2022

Global Landscape of Benefit-Risk Considerations for Medicinal Products: Current State and Future Directions.

Max Waschbusch, Lisa Rodriguez, Andreas Brueckner, Kerry Jo Lee, Xuefeng Li, Oksana Mokliatchouk, Lothar Tremmel, Shuai S Yuan

Abstract read
PubMed Publisher
In one paragraph

Article in Pharmaceutical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

8 authors.

Max WaschbuschGlobal Clinical Safety and Pharmacovigilance, CSL Behring, King of Prussia, PA, USA. max.waschbusch@cslbehring.com.ORCID 0000-0002-3281-3538
Lisa RodriguezCenter for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA.
Andreas BruecknerQuantitative Safety and Epidemiology, Novartis, Basel, Switzerland.
Kerry Jo LeeCenter for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA.
Xuefeng LiCenter for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA.
Oksana MokliatchoukAnalytics and Data Sciences, Biostatistics, Biogen, Cambridge, MA, USA.
Lothar TremmelQuantitative Sciences and Reporting, CSL Behring, King of Prussia, PA, USA.
Shuai S YuanOncology Statistics, GlaxoSmithKline Plc, Upper Province, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last decade there has been a significant increase in the literature discussing the use of benefit-risk methods in medical product (including devices) development. Government agencies, medical product industry groups, academia, and collaborative consortia have extensively discussed the advantages of structured benefit-risk assessments. However, the abundance of information has not resulted in a consistent way to utilize these findings in medical product development. Guidelines and papers on methods, even though well structured, have not led to a firm consensus on a clear and consistent approach. This paper summarizes the global landscape of benefit-risk considerations for product- or program-level decisions from available literature and regulatory guidance, providing the perspectives of three stakeholder groups-regulators, collaborative groups and consortia, and patients. The paper identifies key themes, potential impact on benefit-risk assessments, and significant future trends.

Indexed as

Government AgenciesIndustryForecastingHumansRisk Assessment

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.