Evidence map›Paper›PMID 35238173›Full record

ArticleAsia-Pacific journal of clinical oncology2022

Understanding mammographic breast density profile in China: A Sino-Australian comparative study of breast density using real-world data from cancer screening programs.

Tong Li, Jing Li, Rob Heard, Ziba Gandomkar, Jiansong Ren, Min Dai, Patrick Brennan

Abstract read
In one paragraph

Article in Asia-Pacific journal of clinical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
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  5. Article
  6. Breastfeeding and Mammographic Breast Density: A Cross-sectional Study.Cancer prevention research (Philadelphia, Pa.) · 2023
    Article
  7. Article
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  9. Review
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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

7 authors.

Tong LiMedical Imaging Science, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia.ORCID https://orcid.org/0000-0003-4956-765X
Jing LiDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Rob HeardSchool of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia.
Ziba GandomkarMedical Imaging Science, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia.
Jiansong RenOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Min DaiOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Patrick BrennanMedical Imaging Science, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis study aims at understanding mammographic density profile in China by comparing the density between women in China and Australia.

methodsData of 3250 women aged 45-69 were obtained from the Cancer Screening Program in Urban China and data of 1384 Australian counterparts at same age range were gathered from the Lifepool project. Demographic and reproductive details and mammograms for each cohort were collected. Mammographic density was assessed using AutoDensity, and two metrics, percentage density (PD) and dense area (DA), were applied. T-tests were used to compare the means of mammographic density between two populations of all, premenopausal, and postmenopausal women. Two-way ANOVA was conducted to examine interactions of population (Chinese/Australian) and each variable of interest upon mammographic density.

resultsChinese women had 9.61%, 8.20%, and 9.28% higher PD than their Australian counterparts in all, premenopausal, and postmenopausal women, respectively (all p < 0.001). The mean differences in DA between two population were 1.81 cm

conclusionsBoth PD and DA were found to be higher in Chinese women compared to Australian women. The density difference by menopause status was shown and breastfeeding history affected breast density differently in both populations.

Indexed as

Breast NeoplasmsNeoplasmsBreast DensityChinaEarly Detection of CancerFemaleHumansMammographyRisk Factorsbreast cancerbreast densitybreastfeedingmammographymenopause

Identifiers

PMID35238173
PMCPMC9790382

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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.