Evidence map›Paper›PMID 31930048›Full record

ArticleAnnals of translational medicine2019

Factors influencing the performance of a diagnostic model including contrast-enhanced ultrasound in 1023 breast lesions: comparison with histopathology.

Yijie Chen, Lina Tang, Zhongshi Du, Zhaoming Zhong, Jun Luo, Lichun Yang, Ruoxia Shen, Yan Cheng, Zizhen Zhang, Ehui Han and 8 more

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. 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

18 authors at 8 institutions in 1 country.

Yijie ChenDepartment of Ultrasound, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350014, China.
Lina TangDepartment of Ultrasound, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350014, China.
Zhongshi DuDepartment of Ultrasound, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350014, China.
Zhaoming ZhongDepartment of Ultrasound, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350014, China.
Jun LuoDepartment of Ultrasound, Sichuan Provincial People's Hospital, Chengdu 610072, China.
Lichun YangDepartment of Ultrasound, the Third Affiliated Hospital of Kunming Medical University & Yunnan Cancer Hospital, Kunming 650118, China.
Ruoxia ShenDepartment of Ultrasound, the Third Affiliated Hospital of Kunming Medical University & Yunnan Cancer Hospital, Kunming 650118, China.
Yan ChengDepartment of Ultrasound, Qujing City First People's Hospital, Qujing 655000, China.
Zizhen ZhangDepartment of Ultrasound, Qujing City First People's Hospital, Qujing 655000, China.
Ehui HanDepartment of Ultrasound, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi 435000, China.
Zhihong LvDepartment of Ultrasound, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi 435000, China.
Lijun YuanDepartments of Ultrasound, Tangdu Hospital, Fourth Military Medical University, Xi'an 710032, China.
Yong YangDepartments of Ultrasound, Tangdu Hospital, Fourth Military Medical University, Xi'an 710032, China.
Yinrong ChengDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu 610000, China.
Lei YangDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu 610000, China.
Shengli WangDepartment of Ultrasound, Yanan University Affiliated Hospital, Yan'an 716000, China.
Baoyan BaiDepartment of Ultrasound, Yanan University Affiliated Hospital, Yan'an 716000, China.
Qin ChenDepartment of Ultrasound, Sichuan Provincial People's Hospital, Chengdu 610072, China.
Fujian Medical University · CNAir Force Medical University · CNFirst Affiliated Hospital of Chengdu Medical College · CNHuangshi Central Hospital · CNKunming Medical University · CNQujing Normal University · CNYanan University Affiliated Hospital · CNFujian Provincial Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to investigate the influence of patient and lesion characteristics on our diagnostic model for contrast-enhanced ultrasound (CEUS) of the breast, comparing its accuracy with that of histopathology.

methodsConducting a study with eight medical centers, we compared 1,023 breast lesions categorized as BI-RADS 4 or 5 with the score from our newly-established CEUS-based diagnostic model, comparing the results with pathological outcomes. Univariate and multivariate logistic regression analyses were conducted to determine the influence of clinicopathological characteristics on the performance of this CEUS model.

resultsLogistic regression analysis showed that patients' age, maximum lesion diameter, and distance from the lesion's deep edge to the pectoralis major were significant independent influencing factors. The model's diagnostic accuracy was greater for patients >35 y (P=0.005), for maximum lesion diameter >20 mm, and for distance from the lesion's deep edge to the pectoralis major ≤3.05 mm. There was no significant difference in accuracy between lesions with maximum lesion diameter 10-20 and <10 mm (P=0.393).

conclusionsThe diagnostic performance of the proposed CEUS model for breast lesions is influenced by patients' age, maximum lesion diameter, and distance from the lesion's deep edge to the pectoralis major. Consideration of influencing factors is required to optimize clinical use of the CEUS model.

Indexed as

Breast cancercontrast-enhanced ultrasoundultrasonography

Identifiers

PMID31930048
PMCPMC6944552
OpenAlexW2989823340

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.