Evidence map›Paper›PMID 39061223›Full record

ArticleCancers2024

Impact of Robotic Assistance on Minimally Invasive Surgery for Type II Endometrial Cancer: A National Cancer Database Analysis.

Kelly Lamiman, Michael Silver, Nicole Goncalves, Michael Kim, Ioannis Alagkiozidis

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Cancer of the corpus uteri: A 2025 update.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
    Review
  2. 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.

Kelly LamimanDepartment of Gynecologic Oncology, Maimonides Medical Center, Brooklyn, NY 11220, USA.
Michael SilverDepartment of Gynecologic Oncology, Maimonides Medical Center, Brooklyn, NY 11220, USA.
Nicole GoncalvesDepartment of Gynecologic Oncology, Maimonides Medical Center, Brooklyn, NY 11220, USA.
Michael KimDepartment of Obstetrics and Gynecology, New York-Presbyterian Brooklyn Methodist Hospital, Brooklyn, NY 11215, USA.ORCID 0000-0002-2813-2123
Ioannis AlagkiozidisDepartment of Gynecologic Oncology, Maimonides Medical Center, Brooklyn, NY 11220, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study is to compare the overall survival (OS) and surgical outcomes between conventional laparoscopy and robot-assisted laparoscopy (RAL) in women with type II endometrial cancer. We identified a large cohort of women who underwent hysterectomy for type II endometrial cancer between January 2010 and December 2014 using the National Cancer Database (NCDB). The primary outcome was to compare the OS of conventional laparoscopy versus RAL. Secondary outcomes included the length of hospital stay, 30-day readmission rate, 90-day mortality, rates of lymph node retrieval, rates of node positivity, and rates of conversion to laparotomy. Cohorts were compared and multivariable logistic regression was used to determine characteristics with statistically significant predictors of outcome. We identified 7168 patients with stage I-III type II endometrial cancer who had minimally invasive surgery as primary treatment between 2010 and 2014. A total of 5074 patients underwent RAL. Women who underwent RAL were less likely to have stage III disease (26.4% vs. 29.9%,

Indexed as

conversion to laparotomyoverall survivalrobotic surgerytype II histologyuterine cancer

Identifiers

PMID39061223
PMCPMC11274470

What OpenQuestion holds

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LicenceCC BY
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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.