Evidence map›Paper›PMID 34629491›Full record

ArticleGeburtshilfe und Frauenheilkunde2021

Targeted Removal of Axillary Lymph Nodes After Carbon Marking in Patients with Breast Cancer Treated with Primary Chemotherapy.

Steffi Hartmann, Angrit Stachs, Thorsten Kühn, Jana de Boniface, Maggie Banys-Paluchowski, Toralf Reimer

Open access · hybridAbstract read
In one paragraph

Article in Geburtshilfe und Frauenheilkunde, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 39% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. Review
  5. Article
  6. 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

6 authors at 4 institutions in 2 countries.

Steffi HartmannUniversitätsklinikum Rostock, Klinik für Gynäkologie und Geburtshilfe, Rostock, Germany.
Angrit StachsUniversitätsklinikum Rostock, Klinik für Gynäkologie und Geburtshilfe, Rostock, Germany.
Thorsten KühnKlinikum Esslingen, Klinik für Gynäkologie und Geburtshilfe, Esslingen, Germany.
Jana de BonifaceDepartment of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
Maggie Banys-PaluchowskiUniversitätsklinikum Schleswig-Holstein, Campus Lübeck, Klinik für Gynäkologie und Geburtshilfe, Lübeck, Germany.
Toralf ReimerUniversitätsklinikum Rostock, Klinik für Gynäkologie und Geburtshilfe, Rostock, Germany.
Universitätsmedizin Rostock · DEHeinrich Heine University Düsseldorf · DEKlinikum Esslingen · DESaint Göran Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In breast cancer patients who have received primary chemotherapy and then no longer have any suspicious lymph nodes clinically and/or on imaging, marking of initially suspicious axillary lymph nodes with targeted removal has recently been discussed and practised both in Germany and internationally as an alternative to complete axillary lymph node dissection. Tattooing of the suspicious lymph nodes with a highly purified carbon suspension is currently being investigated in clinical studies. Compared with other techniques, the advantages of this method are the high rate of intraoperative lymph node detection, avoidance of an immediately preoperative localisation procedure and the low costs. The practical aspects of lymph node tattooing and the current data regarding this method will be described.

Indexed as

breast cancercarbon markinglymph nodesprimary chemotherapyTADtargeted axillary dissection

Identifiers

PMID34629491
PMCPMC8494517
OpenAlexW3204363649

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.