Evidence map›Paper›PMID 32128357›Full record

ArticleGynecologic oncology reports2020

Trametinib response in heavily pretreated high-grade ovarian cancer: One step towards precision medicine.

Serena Cappuccio, Maria Grazia Distefano, Viola Ghizzoni, Anna Fagotti, Giovanni Scambia

Open access · goldAbstract readCase Reports
In one paragraph

Article in Gynecologic oncology reports, 2020. 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
2.6field-weighted citation impact, top 11% of its field
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, 19 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Serena CappuccioUniversità Cattolica del Sacro Cuore, Istituto di Clinica Ostetrica e Ginecologica, Roma, Italy.
Maria Grazia DistefanoFondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy.
Viola GhizzoniUniversità Cattolica del Sacro Cuore, Istituto di Clinica Ostetrica e Ginecologica, Roma, Italy.
Anna FagottiUniversità Cattolica del Sacro Cuore, Istituto di Clinica Ostetrica e Ginecologica, Roma, Italy.
Giovanni ScambiaUniversità Cattolica del Sacro Cuore, Istituto di Clinica Ostetrica e Ginecologica, Roma, Italy.
Università Cattolica del Sacro Cuore · ITAgostino Gemelli University Polyclinic · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional treatment failure in recurrent ovarian cancer remains a challenge for clinicians. Tumor genetic testing is a promising tool which has been proved able to identify sensitivity profiles in patients affected by cancers. This may be helpful in choosing targeted systemic treatments, aiming to overcome histology boundaries and to avoid unnecessary toxicity. We describe the case of a patient affected by recurrent high-grade serous ovarian cancer responsive to MEK-inhibitors, who had undergone multiple lines of therapy. To our knowledge, this is the first reported case of recurrent high-grade ovarian cancer showing remarkable clinical, radiologic and biochemical response to trametinib. This report suggests that trametinib could be effective in high-grade serous ovarian cancer, although most of promising scientific data on this molecule have focused on low-grade ovarian cancer. Molecular profiling has gradually become part of care for patients affected by recurrent ovarian cancer, however further randomized studies are needed to prove its efficacy in everyday clinical practice.

Indexed as

Genetic testingOvarian epithelial cancerOvarian neoplasmPrecision medicineTarget therapyTrametinib

Identifiers

PMID32128357
PMCPMC7042411
OpenAlexW3006505133

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.