Evidence map›Paper›PMID 31723211›Full record

ReviewGene therapy2019

A rare disease patient/caregiver perspective on fair pricing and access to gene-based therapies.

Wendy White

Abstract readReview
PubMed Publisher
In one paragraph

Review in Gene therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Price determinants and pricing policies concerning potentially innovative health technologies: a scoping review.The European journal of health economics : HEPAC : health economics in prevention and care · 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

1 author at 1 institution in 1 country.

Wendy WhiteGlobal Genes, Oak Park, IL, USA. Chair@globalgenes.org.
GE Global Research (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene-based therapies are changing the landscape of medicine for patients with rare diseases. These one-time, potentially curative treatments pose a challenge in the US healthcare model, where high prices and insurance coverage variation may prevent patients from receiving life-altering therapies. Questioning of high prices occurs when patients, payers, and policy makers hold divergent views on the value and uncertainty of therapies. The key for patients is that high prices need to be justified, and companies need to partner authentically with patients. Companies should not automatically assume that the combination of the "gene therapy" label and a small patient population justifies high prices. To speed up the development process and potentially reduce costs, patients want the industry to improve clinical trial efficiency by sharing data, including natural history studies and failed trial results. From the patient perspective, current value assessment frameworks disadvantage people with disabilities, may not accurately reflect patients' and societal views, and omit necessary factors such as impact on caregivers, lost productivity, and the future value of innovation. Value determination methods need to provide fair incentives and outcomes to industry, payers, regulators, and especially patients-the courageous pioneers who need equitable and sustainable access to life-changing gene-based therapies.

Indexed as

CaregiversRare DiseasesCosts and Cost AnalysisDrug CostsGenetic TherapyHumans

Identifiers

PMID31723211
OpenAlexW2983706326

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.