Evidence map›Paper›PMID 31245564›Full record

ArticleLearning health systems2017

Advancing the science of patient input throughout the regulatory decision-making process.

Million A Tegenge, Megan M Moncur, Robert Sokolic, Richard A Forshee, Telba Irony

Open access · goldAbstract read
In one paragraph

Article in Learning health systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
6.6field-weighted citation impact, top 3% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Quantifying patient preferences for treatments for refractory chronic spontaneous urticaria.The journal of allergy and clinical immunology. Global · 2025
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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

5 authors at 2 institutions in 1 country.

Million A TegengeOffice of Biostatistics and Epidemiology Center for Biologics Evaluation and Research (CBER) US Food and Drug Administration Silver Spring Maryland.
Megan M MoncurOffice of Biostatistics and Epidemiology Center for Biologics Evaluation and Research (CBER) US Food and Drug Administration Silver Spring Maryland.
Robert SokolicOffice of Tissues and Advanced Therapies CBER, US Food and Drug Administration Silver Spring Maryland.
Richard A ForsheeOffice of Biostatistics and Epidemiology Center for Biologics Evaluation and Research (CBER) US Food and Drug Administration Silver Spring Maryland.
Telba IronyOffice of Biostatistics and Epidemiology Center for Biologics Evaluation and Research (CBER) US Food and Drug Administration Silver Spring Maryland.
Center for Biologics Evaluation and Research · USUnited States Food and Drug Administration · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The US Food and Drug Administration (FDA) understands the value of patient input in the regulatory decision-making process and has worked to enhance meaningful engagement. In recent years, there has been an increased scientific demand for more systematic and quantitative approaches to incorporate patient input throughout the medical product lifecycle, including to inform regulatory benefit-risk assessments. The use of patient preference information (PPI), elicited using established scientific methods, is a promising strategy for accomplishing this. Although much of the science behind PPI is not new, its application in a regulatory setting will require adapting and advancing the science of identifying, collecting, and evaluating patient input for informing regulatory decision making. Patient input and empowerment are foundational to a learning healthcare system. A learning healthcare system paradigm can also help us better understand and continuously improve the incorporation of the patient perspective in regulatory decision making. In this article, we highlight the Food and Drug Administration's Center for Biologics Evaluation and Research experience and current initiatives on advancing the science of patient input in a regulatory setting, in particular, PPI. We provide a use case that explores how the principles and benefits of PPI applied in shared clinical decision making can be realized and leveraged to enhance regulatory evaluation of innovative therapies. To further advance the application of the science of patient input in our regulatory framework, we compiled a list of example resources that support stakeholders in designing and conducting PPI studies. More collaborative research among stakeholders is needed to establish best practice approaches, ensure scientific validity, and continuously learn and improve the systematic incorporation of scientific patient input throughout the regulatory decision-making process.

Indexed as

benefit riskpatient perspectivepatient preferencescience of patient input

Identifiers

PMID31245564
PMCPMC6508573
OpenAlexW2735183075

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.