Evidence map›Paper›PMID 38410226›Full record

ReviewTranslational cancer research2024

Current status of robot-assisted total pelvic exenteration focusing on the field of urology: a clinical practice review.

Jun Kamei, Tetsuya Fujimura

Open access · diamondAbstract readReview
In one paragraph

Review in Translational cancer research, 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
0.3field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. 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

2 authors at 1 institution in 1 country.

Jun KameiDepartment of Urology, Jichi Medical University, Tochigi, Japan.
Tetsuya FujimuraDepartment of Urology, Jichi Medical University, Tochigi, Japan.
Jichi Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Total pelvic exenteration (TPE) is a highly invasive surgery associated with high rates of perioperative morbidity and mortality and is commonly performed for several types of locally advanced or recurrent pelvic cancers. It involves multivisceral resection, including the rectum, sigmoid colon, bladder, prostate, uterus, vagina, or ovaries, and urologists normally perform radical cystectomy or radical prostatectomy and urinary diversion in collaboration with colorectal surgeons and gynecologists. In the urological field, robot-assisted surgeries have been widely performed as one of the main minimally invasive procedures because of their superior perioperative or oncological outcomes compared to open or laparoscopic surgeries. In pelvic exenteration (PE) surgery, laparoscopic surgeries have shown superior rates of mortality, morbidity, and R0 resection compared to open surgeries. Robot-assisted TPE for the treatment of locally advanced rectal cancer was first reported in 2014, and reports of its safety and usefulness have gradually increased. Robot-assisted PE, in which multivisceral resection in a narrow pelvic space is easier, will eventually be a standard minimally invasive procedure, although evidence has been limited to date. This clinical practice review summarizes the indications for surgery, perioperative complications, and oncological outcomes of robot-assisted TPE and highlights the current status of robot-assisted TPE for patients with urological malignancies and its surgical technique, focusing on the manipulation of urological organs.

Indexed as

Cystectomypelvic exenteration (PE)prostatectomyrobotic surgery

Identifiers

PMID38410226
PMCPMC10894324
OpenAlexW4391390269

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.