Evidence map›Paper›PMID 27471406›Full record

ReviewPharmacogenomics and personalized medicine2016

Cancer pharmacogenomics, challenges in implementation, and patient-focused perspectives.

Jai N Patel

Abstract readReview
In one paragraph

Review in Pharmacogenomics and personalized medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
–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

20 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Article
  7. Evolution of predictive risk factor analysis for chemotherapy-related toxicity.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Cardiovascular and Cancer Risk: The Role of Cardio-oncology.Journal of the advanced practitioner in oncology · 2018
    Review
  19. Article
  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

1 author.

Jai N PatelDepartment of Cancer Pharmacology, Levine Cancer Institute, Carolinas HealthCare System, Charlotte, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer pharmacogenomics is an evolving landscape and has the potential to significantly impact cancer care and precision medicine. Harnessing and understanding the genetic code of both the patient (germline) and the tumor (somatic) provides the opportunity for personalized dose and therapy selection for cancer patients. While germline DNA is useful in understanding the pharmacokinetic and pharmacodynamic disposition of a drug, somatic DNA is particularly useful in identifying drug targets and predicting drug response. Molecular profiling of somatic DNA has resulted in the current breadth of targeted therapies available, expanding the armamentarium to battle cancer. This review provides an update on cancer pharmacogenomics and genomics-based medicine, challenges in applying pharmacogenomics to the clinical setting, and patient perspectives on the use of pharmacogenomics to personalize cancer therapy.

Indexed as

biomarkerDNAgermlineoncologypersonalizedpharmacogeneticssomatic

Identifiers

PMID27471406
PMCPMC4948716

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.