Evidence map›Paper›PMID 23071236›Full record

ReviewJournal of clinical oncology : official journal of the American Society of Clinical Oncology2012

Comparative effectiveness research, genomics-enabled personalized medicine, and rapid learning health care: a common bond.

Geoffrey S Ginsburg, Nicole M Kuderer

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Guideline
  2. Guideline
  3. Review
  4. Review
  5. Review
  6. Observational
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. An overview of recommendations and translational milestones for genomic tests in cancer.Genetics in medicine : official journal of the American College of Medical Genetics · 2015
    Review
  16. Article
  17. Article
  18. Rapid learning for precision oncology.Nature reviews. Clinical oncology · 2014
    Review
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Geoffrey S GinsburgDuke University Medical Center, Duke Center for Personalized Medicine, Institute for Genome Sciences and Policy, Durham, NC 27708, USA. Geoffrey.Ginsburg@duke.edu
Nicole M Kuderer

Funding

Inter-disciplinary Program for Training and Mentoring in CER Methods and PracticeKM1CA156687 · NCI · DUKE UNIVERSITY · PI ABERNETHY, AMY P., DELONG, ELIZABETH R. · 2010 to 2010
$2.4M
Programs in Clinical Effectiveness of Cancer PharmacogenomicsUC2CA148041 · NCI · DUKE UNIVERSITY · PI GINSBURG, GEOFFREY S · 2010 to 2010
$2.0M
NCI NIH HHS 1KM1CA156687-01NCI NIH HHS 5UC2CA148041-02NCI NIH HHS KM1 CA156687NCI NIH HHS UC2 CA148041
6 · The paper itself

Abstract

Despite stunning advances in our understanding of the genetics and the molecular basis for cancer, many patients with cancer are not yet receiving therapy tailored specifically to their tumor biology. The translation of these advances into clinical practice has been hindered, in part, by the lack of evidence for biomarkers supporting the personalized medicine approach. Most stakeholders agree that the translation of biomarkers into clinical care requires evidence of clinical utility. The highest level of evidence comes from randomized controlled clinical trials (RCTs). However, in many instances, there may be no RCTs that are feasible for assessing the clinical utility of potentially valuable genomic biomarkers. In the absence of RCTs, evidence generation will require well-designed cohort studies for comparative effectiveness research (CER) that link detailed clinical information to tumor biology and genomic data. CER also uses systematic reviews, evidence-quality appraisal, and health outcomes research to provide a methodologic framework for assessing biologic patient subgroups. Rapid learning health care (RLHC) is a model in which diverse data are made available, ideally in a robust and real-time fashion, potentially facilitating CER and personalized medicine. Nonetheless, to realize the full potential of personalized care using RLHC requires advances in CER and biostatistics methodology and the development of interoperable informatics systems, which has been recognized by the National Cancer Institute's program for CER and personalized medicine. The integration of CER methodology and genomics linked to RLHC should enhance, expedite, and expand the evidence generation required for fully realizing personalized cancer care.

Indexed as

Comparative Effectiveness ResearchDecision MakingGenomicsHumansNeoplasmsPrecision Medicine

Identifiers

PMID23071236
PMCPMC3504328

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.