ReviewPrzeglad menopauzalny = Menopause review2022
Sentinel lymph node mapping in endometrial cancer to reduce surgical morbidity: always, sometimes, or never.
Review in Przeglad menopauzalny = Menopause review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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
5 citing papers in PubMed, 9 citations in OpenAlex.
- Robot-Assisted Hysterectomy Provides Higher Sentinel Node Detection and Lower Conversion Rates Compared to Laparoscopy in Endometrial Cancer.Life (Basel, Switzerland) · 2026Article
- Complication rates and management in sentinel lymph node biopsy for endometrial cancer: a retrospective cohort study.Frontiers in medicine · 2026Article
- Laparoscopy in the Surgical Management of Gynecological Cancer: A Comprehensive Update.Journal of clinical medicine · 2025Review
- Review
- The impact of lymphovascular space invasion on survival in early stage low-grade endometrioid endometrial cancer.European journal of medical research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Surgical staging of nodal status is of utmost significance to determine the stage of endometrial cancer and construct a targeted treatment plan. Systematic lymphadenectomy has for years been the procedure of choice for staging purposes, enabling thorough assessment of lymph nodes. Nevertheless, it is associated with increased morbidity and severe postoperative complications. In an attempt to avoid the disadvantages of lymphadenectomy, the use of sentinel lymph node (SLN) biopsy has been examined as an alternative staging procedure.The purpose of the present review is to summarize and provide up-to-date evidence about the role of SLN biopsy in the staging and management of endometrial cancer cases in the terms of optimal technique, efficacy, safety, and postoperative morbidity, as an alternative approach to regional lymphadenectomy. Material and methods: A thorough literature search was conducted in MEDLINE and SCOPUS to identify recent primary research and previous review articles that explore the use of SLN mapping as a staging procedure in patients with endometrial cancer. Results: There is increasing evidence that SLN mapping is efficient in identifying metastatic nodal disease without compromising oncological safety, achieving comparable or even superior detection rates to those of lymphadenectomy, when optimal technique and careful intraoperative nodal assessment are applied. Conclusions: Sentinel lymph node mapping can safely replace lymphadenectomy as an acceptable alternative staging method for endometrial cancer; however, future research might further strengthen this suggestion by resolving potential areas of doubt and debate, especially for high-risk endometrial cancer cases.
Indexed as
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What OpenQuestion holds
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.