Evidence map›Paper›PMID 31919403›Full record

ArticleBritish journal of cancer2020

Patient-derived xenograft models-the future of personalised cancer treatment.

Jenna Bhimani, Katie Ball, Justin Stebbing

Abstract readEditorialComment
In one paragraph

Article in British journal of cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Review
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  3. Article
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  9. Review
  10. Review
  11. PROBABILISTIC LEARNING OF TREATMENT TREES IN CANCER.The annals of applied statistics · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 3D cancer models: One step closer toFrontiers in immunology · 2023
    Review
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jenna BhimaniDepartment of Oncology, Charing Cross Hospital, Imperial College and Imperial College Healthcare NHS Trust, Fulham Palace Road, London, W6 8RF, UK. j.bhimani@nhs.net.
Katie BallDepartment of Oncology, Charing Cross Hospital, Imperial College and Imperial College Healthcare NHS Trust, Fulham Palace Road, London, W6 8RF, UK.
Justin StebbingDepartment of Oncology, Charing Cross Hospital, Imperial College and Imperial College Healthcare NHS Trust, Fulham Palace Road, London, W6 8RF, UK.

Funding

Department of Health NIHR-RP-011-053
6 · The paper itself

Abstract

For many tumours there is a lack of randomised data from which we can guide systemic treatments. Although gene expression profiling along with proteomics has led to advances in diagnosis, classification and prognosis, our ability to target many cancers has been further limited due to a lack of therapeutic options. The use of patient-derived xenograft (PDX) models in the setting of a rare malignancy is discussed here by Kamili et al, with the successful establishment of new model systems.

Indexed as

NeuroblastomaAnimalsDisease Models, AnimalHeterograftsHumansPrognosisXenograft Model Antitumor Assays

Identifiers

PMID31919403
PMCPMC7054515

What OpenQuestion holds

Textmetadata
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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.