Evidence map›Paper›PMID 32042678›Full record

ArticleGland surgery2019

Diagnostic value of an automated breast volume scanner compared with a hand-held ultrasound: a meta-analysis.

Xiaohui Zhang, Juan Chen, Yidong Zhou, Feng Mao, Yan Lin, Songjie Shen, Qiang Sun, Zhaolian Ouyang

Open access · diamondAbstract read
In one paragraph

Article in Gland surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 12% 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, 22 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

8 authors at 2 institutions in 1 country.

Xiaohui ZhangDepartment of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, Beijing 100032, China.
Juan ChenInstitute of Medical Information/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100020, China.
Yidong ZhouDepartment of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, Beijing 100032, China.
Feng MaoDepartment of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, Beijing 100032, China.
Yan LinDepartment of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, Beijing 100032, China.
Songjie ShenDepartment of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, Beijing 100032, China.
Qiang SunDepartment of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, Beijing 100032, China.
Zhaolian OuyangInstitute of Medical Information/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100020, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNPeking Union Medical College Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe diagnostic performance of an automated breast volume scanner (ABVS) compared with that of a hand-held ultrasound (HHUS) for breast cancer remains unclear. We performed a meta-analysis to compare the diagnostic performances of the ABVS and HHUS for breast cancer.

methodsWe searched PubMed, EMBASE, Cochrane, and SinoMed databases to identify eligible studies up until November 14, 2018. Studies comparing ABVS and HHUS for differentiating benign and malignant breast tumors were included. A meta-analysis was performed to generate pooled diagnostic accuracy parameters [sensitivity, specificity, diagnostic odds ratio (DOR), area under the curve (AUC), and the Q* index] and detection rates for ABVS and HHUS.

resultsNine studies involving 1,376 patients and 1,527 lesions were included in the meta-analysis for diagnostic accuracy. The pooled sensitivity was 0.93 [95% confidence interval (CI), 0.91-0.95] for ABVS and 0.90 (95% CI, 0.88-0.92) for HHUS, and the pooled specificity was 0.86 (95% CI, 0.83-0.88) for ABVS and 0.82 (95% CI, 0.79-0.84) for HHUS. The pooled DOR was 88.66 (95% CI, 51.44-152.78) for ABVS and 41.06 for HHUS (95% CI, 26.58-63.42). The AUC of the summary receiver operating characteristic (SROC) was 0.9496 for ABVS and 0.9143 for HHUS, and the Q* index was 0.8899 for ABVS and 0.8469 for HHUS. Meta-regression showed no significant difference between the diagnostic accuracy of ABVS and HHUS (P=0.0771). No publication bias was found. Thirteen published studies involving 1,047 pathologically confirmed malignant lesions were included to generate a pooled detection rate. The pooled detection rate was 1.00 (95% CI, 1.00-1.00) for both ABVS and HHUS, for which a publication bias was found.

conclusionsABVS can be used as an appropriate screening tool for breast cancer as well as HHUS in diagnostic accuracy and detection rate. Considering other advantages of ABVS including non-radioactivity, sensitivity to dense breast, three-dimensional reconstruction, time-saving and repeatability, it might be a promising screening tool for young or dense-breast women in the future.

Indexed as

Automated breast volume scanner (ABVS)breast cancerhand-held ultrasound (HHUS)meta-analysis

Identifiers

PMID32042678
PMCPMC6989916
OpenAlexW2995935516

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.