Evidence map›Paper›PMID 31269987›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2019

Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?

Hongli Wang, Jianguo Lai, Jiao Li, Ran Gu, Fengtao Liu, Yue Hu, Jingsi Mei, Xiaofang Jiang, Shiyu Shen, Fengyan Yu and 1 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2019. 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
0.9field-weighted citation impact, top 25% 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, 9 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Hongli WangGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Jianguo LaiGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Jiao LiDepartment of Radiology, Sun Yat-sen University Cancer Center, Dongfeng East Road No.651, Yuexiu District, Guangzhou, Guangdong, 510060, People's Republic of China.
Ran GuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Fengtao LiuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Yue HuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Jingsi MeiGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Xiaofang JiangGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Shiyu ShenGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China.
Fengyan YuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China. sakya.vir@foxmail.com.
Fengxi SuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yanjiang Road. west No.107, YueXiu district, Guangzhou, Guangdong, 510120, People's Republic of China. fengxisu@vip.163.com.ORCID http://orcid.org/0000-0002-7371-8764
Sun Yat-sen University · CN

Funding

National Natural Science Foundation of China 81372817
6 · The paper itself

Abstract

backgroundMammography (MG) is highly sensitive for detecting microcalcifications, but has low specificity. This study investigates whether establishing a preoperative nomogram including ultrasonographic findings can help predict the likelihood of malignancy in patients with mammographic microcalcification.

methodsBetween May 2012 and January 2017, 475 patients with suspicious microcalcifications detected on MG underwent ultrasonography (US). The χ

resultsAmong the cases, 68.2% (324/475) were pathologically diagnosed as breast cancer and 31.8% (151/475) were benign lesions. Based on multivariate logistic regression analysis, age, clinical manifestation, morphology and distribution of microcalcifications on MG and lesions associated with microcalcifications on US were confirmed as independent predictors of malignant microcalcifications. In terms of discrimination ability, the C-index of the M-U nomogram was significantly higher than that of the M nomogram (0.917 vs 0.897, p = 0.006). The bias-corrected curve was close to the ideal line in the calibration curve. Decision curve analysis suggested that the M-U nomogram was superior to M nomogram.

conclusionsCombining mammographic parameters with ultrasonographic findings in a nomogram provided better performance than an M nomogram alone, especially for dense breasts, which suggests the value of ultrasonographic finding for individualized prediction of malignancy in patients with microcalcifications.

Indexed as

AdultAgedBreast NeoplasmsCalcinosisFemaleHumansMammographyMiddle AgedNomogramsPreoperative PeriodSensitivity and SpecificityUltrasonographyBreastMammographyMicrocalcificationNomogramUltrasonography

Identifiers

PMID31269987
PMCPMC6610836
OpenAlexW2954154858

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.