Evidence map›Paper›PMID 35598300›Full record

Trial reportCancer medicine2022

Clinicopathological characteristics and prognosis of microinvasive breast cancer: A population-based analysis.

Hangcheng Xu, Yiqun Han, Yun Wu, Yan Wang, Jiayu Wang, Binghe Xu

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 47% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Review
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 1 institution in 1 country.

Hangcheng XuDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yiqun HanDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0001-5338-3058
Yun WuDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yan WangDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jiayu WangDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-1967-389X
Binghe XuDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-0234-2747
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMicroinvasive breast cancer (MIBC) is a special type of breast cancer with a relatively low prevalence, of which the understanding remains controversial. In this article, we aimed to clarify the clinicopathological characteristics and prognosis of MIBC in the setting of different molecular subtypes and give feasible suggestions on clinical practice in MIBC.

methodsThis study utilized the data from Surveillance, Epidemiology, and End Results (SEER) database. Patients were divided into subgroups based on the molecular subtypes, of which the clinicopathological characteristics were further undergone comparative analyses. Kaplan-Meier method and Cox proportional hazard regression analysis were employed to determine the prognosis of the subtypes, and to explore the prognostic factors. Patients were randomly assigned in a 7:3 ratio to the training and validation cohorts. The independent risk variables were then adopted to generate a nomogram to predict the 3- and 5-year survival probability.

resultsA total of 4301 MIBC patients between 2010 and 2016 were obtained from the SEER database, which were subsequently separated into HR+/HER2- (n = 2598), HR+/HER2+ (n = 723), HR-/HER2+ (n = 633), and HR-/HER2- (n = 347) groups. The HR+/HER2+ group showed the best overall survival (OS) (81.28 months, 95% CI 80.45-82.11) compared with other groups (p = 0.0089). The application of radiotherapy in HR+/HER2- and HR+/HER2+ MIBC patients brought out additional survival benefit compared with those without radiotherapy (p < 0.0001 and p = 0.024, respectively). The prognosis among four subgroups with or without chemotherapy showed no statistical difference. Based on the curated nomogram, the high-score group exhibited a better OS compared with patients from the low-score group.

conclusionsProfound heterogeneity was detected among different molecular subtypes in MIBC patients, of which HR+/HER2+ subtype presented the best prognosis. For HR-positive MIBC patients, increasing survival benefits could be retrieved from radiotherapy. Chemotherapy was not recommended for patients with MIBC. Individual-based protocols were introduced based on the nomogram which warranted further validation.

Indexed as

Breast NeoplasmsErb-b2 Receptor Tyrosine KinasesFemaleHumansNomogramsPrognosisErb-b2 Receptor Tyrosine Kinasesbreast cancerclinical featuresmicroinvasive carcinomamolecular subtypesnomogramprognosis

Identifiers

PMID35598300
PMCPMC9741986
OpenAlexW4281251531

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.