ArticleGynecologic oncology reports2018
Pelvic exenteration by robotically-assisted laparoscopy: A feasibility series of 6 cases.
Article in Gynecologic oncology reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Robotic Pelvic Exenteration for Gynecologic Malignancies, Anatomic Landmarks, and Surgical Steps: A Systematic Review.Frontiers in surgery · 2021Pooled it
- Robotic Multivisceral Resection (RMVR) of the Pelvis for Locally Advanced Colorectal Carcinoma: Single Oncosurgical Center Experience.South Asian journal of cancer · 2024Article
- Robotic-Assisted Pelvic Exenteration for Cervical Cancer: A Systematic Review and Novel Insights into Compartment-Based Imaging.Journal of clinical medicine · 2024Review
- Robotic or laparoscopic pelvic exenteration for gynecological malignancies: feasible options to open surgery.Journal of gynecologic oncology · 2024Article
- Review
- Long-term outcomes of pelvic exenterations for gynecological malignancies: a single-center retrospective cohort study.BMC cancer · 2024Article
- Article
- Salvage robotic anterior pelvic exenteration for cervical cancer: technique and feasibility.Journal of robotic surgery · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
After concomitant chemo-radiation therapy, 20 to 30% of advanced cervical cancers recur in irradiated territory. Pelvic exenteration remains a therapeutic option for selected patients. However, this procedure remains complex because of tissue fragility after radiotherapy and their associated co-morbidities. Minimally invasive surgery such as robotically assisted laparoscopy may overcome these surgical challenges. The objective of this study was to evaluate the feasibility of pelvic exenteration with robotically assisted laparoscopy. Patients who underwent this procedure between 2015 and 2016 were included. Patients characteristics, treatment indication, intraoperative events, immediate and late complications, and histological outcomes were recorded. The data of 6 patients were analyzed. The primary cancer staging ranged from IB1 to IIB. All cases were loco-regional recurrence and 2 cases presented with with vesico-vaginal fistula. All patients had a history of pelvic irradiation. The mean operative time was 6.7 h. No complications occurred during surgery. The average hospital stay was 11.5 days. Immediate complications were mostly represented by urinary tract infections (4/5). Histological margins were clear in 67% (4/6), and a focal involvement was found in 33% (2/6) of cases. Late complications occurred within 82 days on average and included stenosis of ileal anastomosis, wound infection, acute renal failure, and pulmonary embolism. Revision surgery was necessary in 2 cases. There were 3 local recurrences occurring within an average of 215 days. In the light of these results, pelvic exenteration by robotically assisted laparoscopy may represent a valuable treatment modality of recurrent cervical cancer with low immediate postoperative morbidity.
Identifiers
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Registered trials
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.