Evidence map›Paper›PMID 24761218›Full record

ReviewJournal of gynecologic oncology2014

Adjuvant therapy for endometrial cancer.

Maria C Deleon, Natraj R Ammakkanavar, Daniela Matei

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of gynecologic oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  3. Frontiers in oncology · 2025
    Review
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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

3 authors at 2 institutions in 1 country.

Maria C DeleonDepartment of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN, USA.
Natraj R AmmakkanavarDepartment of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Daniela MateiDepartment of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN, USA. ; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. ; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA. ; Melvin and Bren Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA. ; VA Roudebush Hospital, Indiana University School of Medicine, Indianapolis, IN, USA.
Indiana University – Purdue University Indianapolis · USIndiana University School of Medicine

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endometrial cancer is a common gynecologic malignancy typically diagnosed at early stage and cured with surgery alone. Adjuvant therapy is tailored according to the risk of recurrence, estimated based on the International Federation of Gynecology and Obstetrics (FIGO) stage and other histological factors. The objective of this manuscript is to review the evidence guiding adjuvant therapy for early stage and locally advanced uterine cancer. For patients with early stage disease, minimizing toxicity, while preserving outstanding cure rates remains the major goal. For patients with locally advanced endometrial cancer optimal combined regimens are being defined. Risk stratification based on molecular traits is under development and may aid refine the current risk prediction model and permit personalized approaches for women with endometrial cancer.

Indexed as

Adjuvant therapyEarly stageEndometrial cancerLocally advancedRisk stratification

Identifiers

PMID24761218
PMCPMC3996264
OpenAlexW1990272636

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.