Evidence map›Paper›PMID 31480647›Full record

ReviewJournal of clinical medicine2019

Towards Circulating-Tumor DNA-Based Precision Medicine.

Ai Hironaka-Mitsuhashi, Anna Sanchez Calle, Takahiro Ochiya, Shin Takayama, Akihiko Suto

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. 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

5 authors.

Ai Hironaka-MitsuhashiDivision of Molecular and Cellular Medicine, National Cancer Centre Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan. ahironak@ncc.go.jp.
Anna Sanchez CalleDivision of Molecular and Cellular Medicine, National Cancer Centre Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.
Takahiro OchiyaDivision of Molecular and Cellular Medicine, National Cancer Centre Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.
Shin TakayamaDepartment of Breast Surgery, National Cancer Centre Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.
Akihiko SutoDepartment of Breast Surgery, National Cancer Centre Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.ORCID 0000-0003-1458-2593

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of precision medicine, targeted therapies have been implemented for various diseases. Genomic information guides decision-making in cancer treatment. The improvements in next-generation sequencing and polymerase chain reaction have made it possible to access the genetic information using circulating-tumor DNAs (ctDNAs). Molecular characteristics of individual tumors can be obtained by analysis of ctDNAs, thus making them excellent tools to guide decision-making during treatment. In oncology, the use of ctDNAs in clinical practice is now gaining importance. Molecular analysis of ctDNAs has potential for multiple clinical applications, including early diagnosis, prognosis of disease, prognostic and/or predictive biomarkers, and monitoring response to therapy and clonal evolution. In this paper, we highlight the applications of ctDNAs in cancer management, especially in metastatic setting, and summarize recent studies about the use of ctDNAs as predictive biomarkers for the therapeutic adaptation/response in lung cancer, breast cancer, and colorectal cancer. These studies offer the evidence to use ctDNAs as a promising approach to solve unmet clinical needs.

Indexed as

biomarkerbreast cancercirculating-tumor DNAcolorectal cancerlung cancerprecision medicinetargeted therapy

Identifiers

PMID31480647
PMCPMC6780195

What OpenQuestion holds

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Registered trials

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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.