Evidence map›Paper›PMID 25081646›Full record

ReviewMolecular oncology2015

Optimal design of trials to demonstrate the utility of genomically-guided therapy: Putting Precision Cancer Medicine to the test.

Rodrigo Dienstmann, Jordi Rodon, Josep Tabernero

Abstract readReview
In one paragraph

Review in Molecular oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Genomics and the History of Precision Oncology.Surgical oncology clinics of North America · 2020
    Review
  6. Review
  7. Bloom Syndrome Protein Activates AKT and PRAS40 in Prostate Cancer Cells.Oxidative medicine and cellular longevity · 2019
    Article
  8. Review
  9. Circulating Tumor DNA as Biomarkers for Cancer Detection.Genomics, proteomics & bioinformatics · 2017
    Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
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

3 authors.

Rodrigo DienstmannSage Bionetworks, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109-1024, USA. Electronic address: rodrigo.dienstmann@sagebase.org.
Jordi RodonMedical Oncology Department, Vall d'Hebron University Hospital and Institute of Oncology, Universitat Autònoma de Barcelona, Barcelona, Spain.
Josep TaberneroMedical Oncology Department, Vall d'Hebron University Hospital and Institute of Oncology, Universitat Autònoma de Barcelona, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The new age of Precision Cancer Medicine, with specific biomarkers being used to direct targeted agents, generally concerns only a subset of patients within a certain histopathologically defined tumor type. This paradigm is challenged by the need to perform widespread molecular screening in certified laboratories, with results available to clinicians within reasonable timeframe. Tumor heterogeneity and clonal evolution must be considered in the decision making process. Adaptive and innovative clinical trial designs exploring predictive algorithms and reconsideration of traditional efficacy endpoints are required to rapidly translate scientific discoveries into patient care. Furthermore, international collaboration in cancer research and open discussions on the availability of investigational agents will likely redefine the drug development and approval process in the coming years.

Indexed as

Clinical Trials as TopicGenomicsGenetic TherapyHumansNeoplasmsClinical trial designPrecision Cancer MedicineTargeted therapy

Identifiers

PMID25081646
PMCPMC5528747

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.