Evidence map›Paper›PMID 35341111›Full record

ArticleJournal of cytology

Intraoperative Sentinel Lymph Node Imprint Cytology Diagnosis in Breast Cancer Patients by General Surgical Pathologists: A Single-Institution Experience of 4327 Cases.

Yi-Chin Chang, Chi-Yuan Tzen

Abstract read
In one paragraph

Article in Journal of cytology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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.

Yi-Chin ChangDepartment of Pathology, Taipei City Hospital, Zhongxiao Branch, Taipei, Taiwan.
Chi-Yuan TzenDepartment of Pathology, MacKay Memorial Hospital, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Context: Sentinel lymph node (SLN) biopsy is the standard of care for breast cancer (BC) patient staging. The axillary node status can be evaluated by frozen section (FS) or imprint cytology (IC). Despite the major disadvantages of tissue loss and freezing artifact in FS, many pathologists consider SLN IC a more difficult task requiring special expertise and prefer FS to IC. Aims: To conduct a large cohort study to evaluate the results of intraoperative SLN IC, compare them with those of FS and permanent section (PS), and determine the best method for general pathologists. Settings and Design: A very large cohort study with many pathologists engaged was designed and the diagnostic results were compared. Materials and Methods: With 12 pathologists engaged, we conducted the largest patient cohort study of SLN IC to date, including 4,327 consecutive BC patients undergoing SLN biopsy during the past 15 years. The touch imprints were stained using three different methods and evaluated. The PS was used as the gold standard for evaluation. Statistical Analysis: The false positivity, false negativity, accuracy, sensitivity, and specificity of the IC and FS for each pathologist were evaluated and compared. Results: Our results showed an overall sensitivity of 82.7%, specificity of 99.3%, and an accuracy rate of 95.9% for SLN IC, which were comparable to those of FS. The accuracy rate did not correlate with the length of working experience and the staining method. Conclusions: Intraoperative hematoxylin and eosin (H&E)-stained IC preparation was found to be the best SLN examination method for general pathologists.

Indexed as

Breast cancerfrozen sectionimprint cytologypathologistsentinel lymph node

Identifiers

PMID35341111
PMCPMC8955698

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Registered trials

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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.