Evidence map›Paper›PMID 28415815›Full record

ArticleOncotarget2017

BI-RADS 3-5 microcalcifications: prediction of lymph node metastasis of breast cancer.

Dongzhi Cen, Li Xu, Siwei Zhang, Shuqin Zhou, Yan Huang, Zhiguang Chen, Ningna Li, Yuan Wang, Qun Wang

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

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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

9 authors.

Dongzhi CenDepartment of Radiation Oncology and Department of Nuclear Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, Guangdong, P.R. China.
Li XuDepartment of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong Province 510120, P.R. China.
Siwei ZhangDepartment of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong Province 510120, P.R. China.
Shuqin ZhouDepartment of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong Province 510120, P.R. China.
Yan HuangDepartment of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong Province 510120, P.R. China.
Zhiguang ChenDepartment of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong Province 510120, P.R. China.
Ningna LiDepartment of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong Province 510120, P.R. China.
Yuan WangJishou University, Jishou, Hunan 427200, P.R. China.
Qun WangJishou University, Jishou, Hunan 427200, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine whether the clinicopathological parameters and Breast Imaging Reporting and Data System (BI-RADS) 3-5 microcalcifications differed between lymph node positive (LN (+)) and lymph node negative (LN (-)) invasive ductal carcinoma (IDC).

resultsFor microcalcification-associated breast cancers, seven selected features (age, tumor size, Ki-67 status, lymphovascular invasion, calcification range, calcification diameter and calcification density) were significantly associated with LN status (all P < 0.05). Multivariate logistic regression analysis found that three risk factors (age: older vs. younger OR: 0.973 P = 0.006, tumor size: larger vs. smaller OR: 1.671, P < 0.001 and calcification density: calcifications > 20/cm2 vs. calcifications ≤ 20/cm2 OR: 1.698, P < 0.001) were significant independent predictors. This model had an area under the receiver operating characteristic curve (AUC) of 0.701. The nodal staging (N0 and N1 χ2 = 5.701, P = 0.017; N0 and N2 χ2 = 6.614, P = 0.013) was significantly positively associated with calcification density. The luminal B subtype had the highest risk of LN metastasis. Multivariate analysis demonstrated that calcification > 2 cm in range (OR: 2.209) and larger tumor size (OR: 1.882) were independently predictive of LN metastasis in the luminal B subtype (AUC = 0.667). MATERIALS AND

methodsMammographic images of 419 female breast cancer patients were included. Associations between the risk factors and LN status were evaluated using a Chi-square test, ANOVA and binary logistic regression analysis.

conclusionsThis study found that age, tumor size and calcifications density can be conveniently used to facilitate the preoperative prediction of LN metastasis. The luminal B subtype has the highest risk of LN metastasis among the microcalcification-associated breast cancers.

Indexed as

AdultAgedAged, 80 and overArea Under CurveBiomarkers, TumorBreast NeoplasmsCalcinosisFemaleHumansImmunohistochemistryLymphatic MetastasisLymph NodesMammographyMiddle AgedPrognosisROC CurveBiomarkers, Tumorcalcificationinfiltrating ductal carcinomalogistic regressionlymph node metastasismammography

Identifiers

PMID28415815
PMCPMC5444736

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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.