Evidence map›Paper›PMID 34377936›Full record

ArticleJNCI cancer spectrum2021

Using Risk Stratification to Optimize Mammography Screening in Chinese Women.

Kathy Leung, Joseph T Wu, Irene Oi-Ling Wong, Xiao-Ou Shu, Wei Zheng, Wanqing Wen, Ui-Soon Khoo, Roger Ngan, Ava Kwong, Gabriel M Leung

Abstract readValidation Study
In one paragraph

Article in JNCI cancer spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. 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

10 authors.

Kathy LeungDivision of Epidemiology and Biostatistics, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.ORCID 0000-0003-4777-388X
Joseph T WuDivision of Epidemiology and Biostatistics, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.ORCID 0000-0002-3155-5987
Irene Oi-Ling WongDivision of Epidemiology and Biostatistics, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, and Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Wei ZhengDivision of Epidemiology, Department of Medicine, and Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Wanqing WenDivision of Epidemiology, Department of Medicine, and Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Ui-Soon KhooDepartment of Pathology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.ORCID 0000-0003-2200-7505
Roger NganDepartment of Clinical Oncology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.
Ava KwongDepartment of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.ORCID 0000-0002-6968-9489
Gabriel M LeungDivision of Epidemiology and Biostatistics, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

Background: The cost-effectiveness of mammography screening among Chinese women remains contentious. Here, we characterized breast cancer (BC) epidemiology in Hong Kong and evaluated the cost-effectiveness of personalized risk-based screening. Methods: We used the Hong Kong Breast Cancer Study (a case-control study with 3501 cases and 3610 controls) and Hong Kong Cancer Registry to develop a risk stratification model based on well-documented risk factors. We used the Shanghai Breast Cancer Study to validate the model. We considered risk-based programs with different screening age ranges and risk thresholds under which women were eligible to join if their remaining BC risk at the starting age exceeded the threshold. Results: The lifetime risk (15-99 years) of BC ranged from 1.8% to 26.6% with a mean of 6.8%. Biennial screening was most cost-effective when the starting age was 44 years, and screening from age 44 to 69 years would reduce breast cancer mortality by 25.4% (95% credible interval [CrI] = 20.5%-29.4%) for all risk strata. If the risk threshold for this screening program was 8.4% (the average remaining BC risk among US women at their recommended starting age of 50 years), the coverage was 25.8%, and the incremental cost-effectiveness ratio (ICER) was US$18 151 (95% CrI = $10 408-$27 663) per quality-of-life-year (QALY) compared with no screening. The ICER of universal screening was $34 953 (95% CrI = $22 820-$50 268) and $48 303 (95% CrI = $32 210-$68 000) per QALY compared with no screening and risk-based screening with 8.4% threshold, respectively. Conclusion: Organized BC screening in Chinese women should commence as risk-based programs. Outcome data (e.g., QALY loss because of false-positive mammograms) should be systemically collected for optimizing the risk threshold.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsBreast NeoplasmsCase-Control StudiesChinaCost-Benefit AnalysisFemaleHong KongHumansMammographyMass ScreeningMiddle AgedProportional Hazards Models

Identifiers

PMID34377936
PMCPMC8346705

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.