Evidence map›Paper›PMID 35223725›Full record

ReviewFrontiers in public health2022

Gene Therapy Evidence Generation and Economic Analysis: Pragmatic Considerations to Facilitate Fit-for-Purpose Health Technology Assessment.

Tingting Qiu, Michal Pochopien, Shuyao Liang, Gauri Saal, Ewelina Paterak, Justyna Janik, Mondher Toumi

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

7 authors at 2 institutions in 2 countries.

Tingting QiuDépartement de Santé Publique, Aix-Marseille Université, Marseille, France.
Michal PochopienDepartment of Health Economics and Outcomes Research, Creativ-Ceutical, Warsaw, Poland.
Shuyao LiangDépartement de Santé Publique, Aix-Marseille Université, Marseille, France.
Gauri SaalDepartment of Health Economics and Outcomes Research, Apothecom, London, United Kingdom.
Ewelina PaterakDepartment of Health Economics and Outcomes Research, Creativ-Ceutical, Warsaw, Poland.
Justyna JanikDepartment of Health Economics and Outcomes Research, Creativ-Ceutical, Warsaw, Poland.
Mondher ToumiDépartement de Santé Publique, Aix-Marseille Université, Marseille, France.
Aix-Marseille Université · FRHealth Economics and Outcomes Research (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene therapies (GTs) are considered to be a paradigm-shifting class of treatments with the potential to treat previously incurable diseases or those with significant unmet treatment needs. However, considerable challenges remain in their health technology assessment (HTA), mainly stemming from the inability to perform robust clinical trials to convince decision-makers to pay the high prices for the potential long-term treatment benefits provided. This article aims to review the recommendations that have been published for evidence generation and economic analysis for GTs against the feasibility of their implementation within current HTA decision analysis frameworks. After reviewing the systematically identified literature, we found that questions remain on the appropriateness of GT evidence generation, considering that additional, broader values brought by GTs seem insufficiently incorporated within proposed analytic methods. In cases where innovative methods are proposed, HTA organizations remain highly conservative and resistant to change their reference case and decision analysis framework. Such resistances are largely attributed to the substantial evidence uncertainty, resource-consuming administration process, and the absence of consensus on the optimized methodology to balance all the advantages and potential pitfalls of GTs.

Indexed as

Genetic TherapyTechnology Assessment, BiomedicalUncertaintyaffordabilityeconomic analysisgene therapieshealth technology assessmentrecommendations

Identifiers

PMID35223725
PMCPMC8863657
OpenAlexW4210972660

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.