Evidence map›Paper›PMID 29479951›Full record

ReviewAsian Pacific journal of cancer prevention : APJCP2018

The Complementary Role of Imaging and Tumor Biomarkers in Gynecological Cancers: An Update of the Literature

Emanuela Anastasi, Silvia Gigli, Laura Ballesio, Antonio Angeloni, Lucia Manganaro

Open access · greenAbstract readReview
In one paragraph

Review in Asian Pacific journal of cancer prevention : APJCP, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Promising predictive molecular biomarkers for cervical cancer (Review).International journal of molecular medicine · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Success ofOncoTargets and therapy · 2020
    Article
  8. Article
  9. Article
  10. Article
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 1 institution in 1 country.

Emanuela AnastasiDepartment of Molecular Medicine, Sapienza University, Viale Regina Elena 324, 00161 Roma, Italy. Email: emanuela.anastasi@uniroma1.it
Silvia Gigli
Laura Ballesio
Antonio Angeloni
Lucia Manganaro
Sapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gynecological tumors, including endometrial, cervical and ovarian cancer, have increased in incidence over time. The widespread introduction of screening programs and advances in diagnostic imaging methods has lead to a progressive increase in gynecological cancer detection. Accurate diagnosis and proper monitoring of disease remain the primary target for a successful treatment. In the last years, knowledge about cancer biomarkers has considerably increased providing great opportunities for improving cancer detection and treatment. In addition, in the last few years there has been an important development of imaging techniques. Nowadays, a multimodal approach including the evaluation of serum tumor biomarkers combined with imaging techniques, seems to be the best strategy for assessing tumor presence, spread, recurrence, and/or the response to treatment in female cancer patients In this review we provide an overview of the application of biomarkers combined with novel imaging methods and highlight their roles in female cancer diagnosis and follow-up.

Indexed as

Biomarkers, TumorDiagnostic ImagingFemaleGenital Neoplasms, FemaleHumansPrognosisBiomarkers, TumorCervical cancerEndometrial cancerImagingOvarian cancerTumor markers

Identifiers

PMID29479951
PMCPMC5980913
OpenAlexW2784753274

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.