Evidence map›Paper›PMID 34108561›Full record

ArticleScientific reports2021

Prognostic implications of regression of metastatic axillary lymph nodes after neoadjuvant chemotherapy in patients with breast cancer.

Yul Ri Chung, Ji Won Woo, Soomin Ahn, Eunyoung Kang, Eun-Kyu Kim, Mijung Jang, Sun Mi Kim, Se Hyun Kim, Jee Hyun Kim, So Yeon Park

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. 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

10 authors at 1 institution in 1 country.

Yul Ri ChungDepartment of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, 13620, Gyeonggi, Republic of Korea.
Ji Won WooDepartment of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, 13620, Gyeonggi, Republic of Korea.
Soomin AhnDepartment of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, 13620, Gyeonggi, Republic of Korea.
Eunyoung KangDepartment of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
Eun-Kyu KimDepartment of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
Mijung JangDepartment of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
Sun Mi KimDepartment of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
Se Hyun KimDivision of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
Jee Hyun KimDivision of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
So Yeon ParkDepartment of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, 13620, Gyeonggi, Republic of Korea. sypmd@snu.ac.kr.
Seoul National University Bundang Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognostic implications of therapeutic response of metastatic lymph nodes (LNs) to neoadjuvant chemotherapy (NAC) remain unclear in patients with breast cancer. We aimed to evaluate the prognostic value of axillary LN regression after NAC in locally-advanced breast cancer patients. Therapeutic response of the LNs was evaluated in 563 breast cancer patients and classified into four grades according to the regression pattern. Initial pathologic N stage was estimated from the sum of the metastatic LNs and those with complete regression. In survival analyses, LN regression grade, pathologic N stage after NAC, and presumed initial pathologic N stage stratified clinical outcome of the patients in the whole group, in both ER-positive and ER-negative subgroups, and in those with residual breast disease. On multivariate analysis, LN regression grade and presumed initial pathologic N stage were revealed as independent prognostic factors. The number of completely-responsive LNs and the ratio of non-responsive LNs also revealed a prognostic value. In conclusion, regression grade of axillary LNs and presumed initial pathologic N stage have prognostic values in breast cancer patients who receive NAC. Thus, regression of axillary LNs should be evaluated and included in pathologic reporting of post-NAC resection specimens.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsAxillaBreast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, LobularChemotherapy, AdjuvantErb-b2 Receptor Tyrosine KinasesFemaleFollow-Up StudiesHumansLymphatic MetastasisLymph NodesMiddle AgedNeoadjuvant TherapyPrognosisReceptors, EstrogenERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, Progesterone

Identifiers

PMID34108561
PMCPMC8190075
OpenAlexW3169732074

What OpenQuestion holds

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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.