Evidence map›Paper›PMID 23629504›Full record

ReviewNature reviews. Drug discovery2013

Implementing personalized cancer genomics in clinical trials.

Richard Simon, Sameek Roychowdhury

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Drug discovery, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
146citing 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

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

  1. Pooled it
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  7. AnGenes · 2026
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  18. Basket Trials: Past, Present, and Future.Annual review of cancer biology · 2024
    Article
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86 more citing papers are in PubMed but not listed here.

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.

Richard SimonBiometric Research Branch, US National Cancer Institute, Bethesda, Maryland 20892-7434, USA.
Sameek Roychowdhury

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent surge in high-throughput sequencing of cancer genomes has supported an expanding molecular classification of cancer. These studies have identified putative predictive biomarkers signifying aberrant oncogene pathway activation and may provide a rationale for matching patients with molecularly targeted therapies in clinical trials. Here, we discuss some of the challenges of adapting these data for rare cancers or molecular subsets of certain cancers, which will require aligning the availability of investigational agents, rapid turnaround of clinical grade sequencing, molecular eligibility and reconsidering clinical trial design and end points.

Indexed as

GenomicsAntineoplastic AgentsClassificationClinical Trials as TopicHumansMolecular BiologyMolecular Diagnostic TechniquesNeoplasmsPrecision MedicineResearch DesignAntineoplastic Agents

Identifiers

PMID23629504

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.