Evidence map›Paper›PMID 30044653›Full record

ReviewExpert review of clinical pharmacology2018

Overview of precision oncology trials: challenges and opportunities.

Elena Fountzilas, Apostolia M Tsimberidou

Registry-linked trialAbstract readReview
In one paragraph

Review in Expert review of clinical pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05025098 (Precision Therapy Versus Standard Therapy in Acute Myeloid Leukaemia and Myelodysplastic Syndrome in Elderly), which is not on this map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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.

NCT05025098 phase2recruitingnot on this mapstarted 2021, after this paper: background citation

Precision Therapy Versus Standard Therapy in Acute Myeloid Leukaemia and Myelodysplastic Syndrome in Elderly

TypeinterventionalSponsorUniversity Hospital, AkershusRan2021 to 2027Enrolled36ConditionsAML, Adult, MDSArmsStandard therapy, Precision therapy
3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Making In Vitro Tumor Models Whole Again.Advanced healthcare materials · 2023
    Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Review
  19. Machine learning in the prediction of cancer therapy.Computational and structural biotechnology journal · 2021
    Review
  20. 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

2 authors.

Elena Fountzilasa Department of Investigational Cancer Therapeutics , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.
Apostolia M Tsimberidoua Department of Investigational Cancer Therapeutics , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

introductionIn recent years, the therapeutic management of selected patients with cancer has shifted toward the 'precision medicine' approach based on patient's mechanisms of tumorigenesis, and their baseline characteristics and comorbidities. Complete tumor and cell-free DNA profiling using next-generation sequencing, proteomic and RNA analysis, and immune mechanisms should to be taken into consideration and accurate bioinformatic analysis is essential to optimize patient's treatment. Areas covered: The challenges and opportunities of conducting clinical trials in precision oncology are summarized. Expert commentary: Precision medicine has significantly changed the diagnostic and therapeutic landscape of cancer. Successful implementation of precision medicine requires translational and bioinformatics infrastructure to support optimization of treatment selection. Targeted therapy, immunotherapy, T-cell therapy alone or in combination with cytotoxic or other effective therapeutic strategies and innovative clinical trials with adaptive design should be offered to all patients. Data sharing and 'N-of-1' models hold the promise to optimize the treatment of individual patients and expedite drug approval for rare alterations and tumor types. Artificial intelligence will facilitate accurate utilization of sequencing data to perform algorithm analysis. Collaboration of healthcare providers with pharmaceutical and biotechnical companies, scientific organizations, and governmental regulatory agencies have a crucial role in curing cancer.

Indexed as

Antineoplastic AgentsClinical Trials as TopicDrug DesignHigh-Throughput Nucleotide SequencingHumansImmunotherapyMolecular Targeted TherapyNeoplasmsPrecision MedicineAntineoplastic AgentsctDNAimmunotherapymolecularmutationN-of-1personalizedprecisiontargetedtrial

Identifiers

PMID30044653
PMCPMC6330881

What OpenQuestion holds

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Registered trials

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.