Evidence map›Paper›PMID 39229469›Full record

ArticleTherapeutic advances in medical oncology2024

Criteria for assessing evidence for biomarker-targeted therapies in rare cancers-an extrapolation framework.

Doah Cho, Sarah J Lord, Robyn Ward, Maarten IJzerman, Andrew Mitchell, David M Thomas, Saskia Cheyne, Andrew Martin, Rachael L Morton, John Simes and 1 more

Abstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2024. 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. Article
  2. Review
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

11 authors.

Doah ChoNational Health and Medical Research Council Clinical Trials Centre, Faculty of Medicine and Health, University of Sydney, Australia.ORCID https://orcid.org/0000-0002-8045-0751
Sarah J LordFaculty of Medicine and Health, National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia.ORCID https://orcid.org/0000-0003-2763-5949
Robyn WardFaculty of Medicine and Health, University of Sydney, Camperdown, NSW, Australia.
Maarten IJzermanFaculty of Medicine, Dentistry and Health Sciences, Centre for Health Policy, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia.
Andrew MitchellDepartment of Health Economics Wellbeing and Society, The Australian National University, Canberra, ACT, Australia.
David M ThomasCentre for Molecular Oncology, University of New South Wales, Sydney, NSW, Australia.
Saskia CheyneFaculty of Medicine and Health, National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia.
Andrew MartinFaculty of Medicine and Health, National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia.
Rachael L MortonFaculty of Medicine and Health, National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia.
John SimesFaculty of Medicine and Health, National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia.
Chee Khoon LeeFaculty of Medicine and Health, National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Advances in targeted therapy development and tumor sequencing technology are reclassifying cancers into smaller biomarker-defined diseases. Randomized controlled trials (RCTs) are often impractical in rare diseases, leading to calls for single-arm studies to be sufficient to inform clinical practice based on a strong biological rationale. However, without RCTs, favorable outcomes are often attributed to therapy but may be due to a more indolent disease course or other biases. When the clinical benefit of targeted therapy in a common cancer is established in RCTs, this benefit may extend to rarer cancers sharing the same biomarker. However, careful consideration of the appropriateness of extending the existing trial evidence beyond specific cancer types is required. A framework for extrapolating evidence for biomarker-targeted therapies to rare cancers is needed to support transparent decision-making. Objectives: To construct a framework outlining the breadth of criteria essential for extrapolating evidence for a biomarker-targeted therapy generated from RCTs in common cancers to different rare cancers sharing the same biomarker. Design: A series of questions articulating essential criteria for extrapolation. Methods: The framework was developed from the core topics for extrapolation identified from a previous scoping review of methodological guidance. Principles for extrapolation outlined in guidance documents from the European Medicines Agency, the US Food and Drug Administration, and Australia's Medical Services Advisory Committee were incorporated. Results: We propose a framework for assessing key assumptions of similarity of the disease and treatment outcomes between the common and rare cancer for five essential components: prognosis of the biomarker-defined cancer, biomarker test analytical validity, biomarker actionability, treatment efficacy, and safety. Knowledge gaps identified can be used to prioritize future studies. Conclusion: This framework will allow systematic assessment, standardize regulatory, reimbursement and clinical decision-making, and facilitate transparent discussions between key stakeholders in drug assessment for rare biomarker-defined cancers.

Indexed as

biomarker-driven trialsbiomarker-guided therapybiomarkersclinical trialscompanion diagnosticspredictive biomarkersprognostic biomarkersresponse biomarkerstargeted therapy

Identifiers

PMID39229469
PMCPMC11369883

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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.